Biomanus/experiments/supplementary_info/mcp_server_table.md

MCP server	Category	Description	Tool count	LAB-Bench subgraph	BioAgent-Bench graph
abnumber	single_cell	AbNumber - Antibody numbering using ANARCI.	1	no	no
abricate	transcriptomics	MCP wrapper for abricate.	6	no	yes
abundancebin	single_cell	MCP wrapper for abundancebin.	1	no	no
abyss	transcriptomics	MCP wrapper for abyss.	4	no	no
adapterremoval	single_cell	The AdapterRemoval v2 tool for merging and clipping reads.	3	no	no
alfred	genomics	BAM alignment statistics, feature counting and feature annotation.	7	no	no
anansescanpy	single_cell	implementation of scANANSE for scanpy objects in Python.	4	no	no
anarci	single_cell	ANARCI: Antibody Numbering and Antigen Receptor ClassIfication.	3	no	no
aragorn	single_cell	MCP wrapper for aragorn.	1	no	no
aria2	transcriptomics	aria2 is a lightweight multi-protocol & multi-source, cross platform download utility operated in command-line. It supports HTTP/HTTPS, FTP, SFTP, BitTorrent and Metalink.	5	no	no
ariba	genomics	ARIBA: Antibiotic Resistance Identification By Assembly.	7	no	no
arriba	transcriptomics	Fast and accurate gene fusion detection from RNA-Seq data.	2	no	no
art	single_cell	MCP wrapper for art.	4	no	no
arvados-cwl-runner	single_cell	Arvados Common Workflow Language runner.	5	no	no
arvados-python-client	single_cell	Arvados client library; Python API for Arvados, an open source platform for managing and.	5	no	no
atropos	single_cell	trim adapters from high-throughput sequencing reads.	1	no	no
augur	genomics	Process pathogen genome data for the Nextstrain platform.	1	no	no
augustus	transcriptomics	MCP wrapper for augustus.	1	no	no
auspice	transcriptomics	MCP wrapper for auspice.	7	no	no
bactopia	single_cell	Bactopia is a flexible pipeline for complete analysis of bacterial genomes.	5	no	no
bamtools	genomics	MCP wrapper for bamtools.	13	no	no
barrnap	transcriptomics	MCP wrapper for barrnap.	1	no	no
bbmap	genomics	MCP wrapper for bbmap.	2	no	no
bcbio-gff	single_cell	A Python library to read and write Generic Feature Format (GFF).	4	no	no
bcbio-nextgen	genomics	Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis.	5	no	no
bcftools	genomics	MCP wrapper for bcftools.	15	yes	yes
bedops	transcriptomics	MCP wrapper for bedops.	10	no	no
bedtools	genomics	MCP wrapper for bedtools.	9	yes	yes
bin2cell	transcriptomics	Join subcellular Visium HD bins into cells.	4	no	no
bioawk	single_cell	MCP wrapper for bioawk.	1	no	no
biobambam	single_cell	Tools for early stage alignment file processing.	11	no	no
bioconductor-affy	single_cell	MCP wrapper for Bioconductor affy.	2	no	no
bioconductor-affyio	single_cell	MCP wrapper for Bioconductor affyio.	5	no	no
bioconductor-affyio copy	general	Auto-indexed MCP server for bioconductor-affyio copy.	1	no	no
bioconductor-alabaster	single_cell	Umbrella for the Alabaster Framework; Umbrella for the alabaster suite, providing a single-line import for all alabaster.* packages. Installing this package ensures that all known alabaster.* packages are also installed, avoiding problems with missing packages when a staging method or loading function is dynamically requested. Obviously, this comes at the cost of needing to install more packages, so advanced users and application developers may prefer to install the required alabaster.* packages individually.	1	no	no
bioconductor-alabaster.sfe	single_cell	Language agnostic on disk serialization of SpatialFeatureExperiment; Builds upon the existing ArtifactDB project, expending alabaster.spatial for language agnostic on disk serialization of SpatialFeatureExperiment.	2	no	no
bioconductor-alabaster.spatial	single_cell	Save and Load Spatial 'Omics Data to/from File; Save SpatialExperiment objects and their images into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.	2	no	no
bioconductor-ancombc	single_cell	Microbiome differential abudance and correlation analyses with bias correction; ANCOMBC is a package containing differential abundance (DA) and correlation analyses for microbiome data. Specifically, the package includes Analysis of Compositions of Microbiomes with Bias Correction 2 (ANCOM-BC2), Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC), and Analysis of Composition of Microbiomes (ANCOM) for DA analysis, and Sparse Estimation of Correlations among Microbiomes (SECOM) for correlation analysis. Microbiome data are typically subject to two sources of biases: unequal sampling fractions (sample-specific biases) and differential sequencing efficiencies (taxon-specific biases). Methodologies included in the ANCOMBC package are designed to correct these biases and construct statistically consistent estimators.	2	no	no
bioconductor-annotate	single_cell	MCP wrapper for Bioconductor annotate.	1	no	no
bioconductor-annotationdbi	single_cell	MCP wrapper for Bioconductor annotationdbi.	5	no	no
bioconductor-annotationfilter	single_cell	Facilities for Filtering Bioconductor Annotation Resources; This package provides class and other infrastructure to implement filters for manipulating Bioconductor annotation resources. The filters will be used by ensembldb, Organism.dplyr, and other packages.	6	no	no
bioconductor-annotationhub	single_cell	Client to access AnnotationHub resources; This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.	1	no	no
bioconductor-apeglm	single_cell	MCP wrapper for Bioconductor apeglm.	1	no	no
bioconductor-apl	single_cell	Association Plots; APL is a package developed for computation of Association Plots (AP), a method for visualization and analysis of single cell transcriptomics data. The main focus of APL is the identification of genes characteristic for individual clusters of cells from input data. The package performs correspondence analysis (CA) and allows to identify cluster-specific genes using Association Plots. Additionally, APL computes the cluster-specificity scores for all genes which allows to rank the genes by their specificity for a selected cell cluster of interest.	1	no	no
bioconductor-awaggregator	single_cell	Attribute-Weighted Aggregation; This package implements an attribute-weighted aggregation algorithm which leverages peptide-spectrum match (PSM) attributes to provide a more accurate estimate of protein abundance compared to conventional aggregation methods. This algorithm employs pre-trained random forest models to predict the quantitative inaccuracy of PSMs based on their attributes. PSMs are then aggregated to the protein level using a weighted average, taking the predicted inaccuracy into account. Additionally, the package allows users to construct their own training sets that are more relevant to their specific experimental conditions if desired.	3	no	no
bioconductor-banksy	single_cell	Spatial transcriptomic clustering; Banksy is an R package that incorporates spatial information to cluster cells in a feature space (e.g. gene expression). To incorporate spatial information, BANKSY computes the mean neighborhood expression and azimuthal Gabor filters that capture gene expression gradients. These features are combined with the cell's own expression to embed cells in a neighbor-augmented product space which can then be clustered, allowing for accurate and spatially-aware cell typing and tissue domain segmentation.	4	no	no
bioconductor-beachmat	single_cell	MCP wrapper for Bioconductor beachmat.	4	no	no
bioconductor-benchdamic	transcriptomics	Benchmark of differential abundance methods on microbiome data; Starting from a microbiome dataset (16S or WMS with absolute count values) it is possible to perform several analysis to assess the performances of many differential abundance detection methods. A basic and standardized version of the main differential abundance analysis methods is supplied but the user can also add his method to the benchmark. The analyses focus on 4 main aspects: i) the goodness of fit of each method's distributional assumptions on the observed count data, ii) the ability to control the false discovery rate, iii) the within and between method concordances, iv) the truthfulness of the findings if any apriori knowledge is given. Several graphical functions are available for result visualization.	5	no	no
bioconductor-biobase	single_cell	MCP wrapper for Bioconductor biobase.	2	no	no
bioconductor-biocbaseutils	single_cell	General utility functions for developing Bioconductor packages; The package provides utility functions related to package development. These include functions that replace slots, and selectors for show methods. It aims to coalesce the various helper functions often re-used throughout the Bioconductor ecosystem.	1	no	no
bioconductor-biocfilecache	single_cell	Manage Files Across Sessions; This package creates a persistent on-disk cache of files that the user can add, update, and retrieve. It is useful for managing resources (such as custom Txdb objects) that are costly or difficult to create, web resources, and data files used across sessions.	9	no	no
bioconductor-biocgenerics	single_cell	MCP wrapper for Bioconductor biocgenerics.	2	no	no
bioconductor-biocio	single_cell	Standard Input and Output for Bioconductor Packages; The BiocIO package contains high-level abstract classes and generics used by developers to build IO funcionality within the Bioconductor suite of packages. Implements import() and export() standard generics for importing and exporting biological data formats. import() supports whole-file as well as chunk-wise iterative import. The import() interface optionally provides a standard mechanism for 'lazy' access via filter() (on row or element-like components of the file resource), select() (on column-like components of the file resource) and collect(). The import() interface optionally provides transparent access to remote (e.g. via https) as well as local access. Developers can register a file extension, e.g., .loom for dispatch from character-based URIs to specific import() / export() methods based on classes representing file types, e.g., LoomFile().	2	no	no
bioconductor-biocneighbors	single_cell	MCP wrapper for Bioconductor biocneighbors.	1	no	no
bioconductor-biocparallel	single_cell	MCP wrapper for Bioconductor biocparallel.	7	no	no
bioconductor-biocsingular	single_cell	MCP wrapper for Bioconductor biocsingular.	3	no	no
bioconductor-biomart	single_cell	MCP wrapper for Bioconductor biomart.	3	no	no
bioconductor-biomformat	single_cell	MCP wrapper for Bioconductor biomformat.	2	no	no
bioconductor-biostrings	single_cell	MCP wrapper for Bioconductor biostrings.	1	no	no
bioconductor-biovizbase	single_cell	Basic graphic utilities for visualization of genomic data; The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and encourages consistency.	7	no	no
bioconductor-blase	single_cell	Bulk Linking Analysis for Single-cell Experiments; BLASE is a method for finding where bulk RNA-seq data lies on a single-cell pseudotime trajectory. It uses a fast and understandable approach based on Spearman correlation, with bootstrapping to provide confidence. BLASE can be used to "date" bulk RNA-seq data, annotate cell types in scRNA-seq, and help correct for developmental phenotype differences in bulk RNA-seq experiments.	1	no	no
bioconductor-bluster	single_cell	Clustering Algorithms for Bioconductor; Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.	5	no	no
bioconductor-bsgenome	single_cell	MCP wrapper for Bioconductor bsgenome.	2	no	no
bioconductor-bulksignalr	single_cell	Infer Ligand-Receptor Interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics; Inference of ligand-receptor (LR) interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics. BulkSignalR bases its inferences on the LRdb database included in our other package, SingleCellSignalR available from Bioconductor. It relies on a statistical model that is specific to bulk data sets. Different visualization and data summary functions are proposed to help navigating prediction results.	3	no	no
bioconductor-cardspa	single_cell	Spatially Informed Cell Type Deconvolution for Spatial Transcriptomics; CARD is a reference-based deconvolution method that estimates cell type composition in spatial transcriptomics based on cell type specific expression information obtained from a reference scRNA-seq data. A key feature of CARD is its ability to accommodate spatial correlation in the cell type composition across tissue locations, enabling accurate and spatially informed cell type deconvolution as well as refined spatial map construction. CARD relies on an efficient optimization algorithm for constrained maximum likelihood estimation and is scalable to spatial transcriptomics with tens of thousands of spatial locations and tens of thousands of genes.	1	no	no
bioconductor-catscradle	single_cell	This package provides methods for analysing spatial transcriptomics data and for discovering gene clusters; This package addresses two broad areas. It allows for in-depth analysis of spatial transcriptomic data by identifying tissue neighbourhoods. These are contiguous regions of tissue surrounding individual cells. 'CatsCradle' allows for the categorisation of neighbourhoods by the cell types contained in them and the genes expressed in them. In particular, it produces Seurat objects whose individual elements are neighbourhoods rather than cells. In addition, it enables the categorisation and annotation of genes by producing Seurat objects whose elements are genes.	4	no	no
bioconductor-cdi	single_cell	Clustering Deviation Index (CDI); Single-cell RNA-sequencing (scRNA-seq) is widely used to explore cellular variation. The analysis of scRNA-seq data often starts from clustering cells into subpopulations. This initial step has a high impact on downstream analyses, and hence it is important to be accurate. However, there have not been unsupervised metric designed for scRNA-seq to evaluate clustering performance. Hence, we propose clustering deviation index (CDI), an unsupervised metric based on the modeling of scRNA-seq UMI counts to evaluate clustering of cells.	4	no	no
bioconductor-cellhashr	single_cell	An R package designed to demultiplex cell hashing data.	6	no	no
bioconductor-cellid	single_cell	Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis; CelliD is a clustering-free multivariate statistical method for the robust extraction of per-cell gene signatures from single-cell RNA-seq. CelliD allows unbiased cell identity recognition across different donors, tissues-of-origin, model organisms and single-cell omics protocols. The package can also be used to explore functional pathways enrichment in single cell data.	6	no	no
bioconductor-cellmigration	single_cell	Track Cells, Analyze Cell Trajectories and Compute Migration Statistics; Import TIFF images of fluorescently labeled cells, and track cell movements over time. Parallelization is supported for image processing and for fast computation of cell trajectories. In-depth analysis of cell trajectories is enabled by 15 trajectory analysis functions.	1	no	no
bioconductor-clusterfoldsimilarity	single_cell	Calculate similarity of clusters from different single cell samples using foldchanges; This package calculates a similarity coefficient using the fold changes of shared features (e.g. genes) among clusters of different samples The similarity coefficient is calculated using the dot-product (Hadamard product) of every pairwise combination of Fold Changes between a source cluster i of sample/dataset n and all the target clusters j in sample/dataset m.	2	no	no
bioconductor-clusterprofiler	pathway_enrichment	A universal enrichment tool for interpreting omics data; This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a universal interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct gene clusters.	5	yes	no
bioconductor-clustifyr	single_cell	MCP wrapper for Bioconductor clustifyr.	1	no	no
bioconductor-clustsignal	single_cell	ClustSIGNAL: a spatial clustering method; clustSIGNAL: clustering of Spatially Informed Gene expression with Neighbourhood Adapted Learning. A tool for adaptively smoothing and clustering gene expression data. clustSIGNAL uses entropy to measure heterogeneity of cell neighbourhoods and performs a weighted, adaptive smoothing, where homogeneous neighbourhoods are smoothed more and heterogeneous neighbourhoods are smoothed less. This not only overcomes data sparsity but also incorporates spatial context into the gene expression data. The resulting smoothed gene expression data is used for clustering and could be used for other downstream analyses.	4	no	no
bioconductor-complexheatmap	single_cell	Make Complex Heatmaps; Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various annotation graphics.	2	no	no
bioconductor-concordexr	transcriptomics	Identify Spatial Homogeneous Regions with concordex; Spatial homogeneous regions (SHRs) in tissues are domains that are homogenous with respect to cell type composition. We present a method for identifying SHRs using spatial transcriptomics data, and demonstrate that it is efficient and effective at finding SHRs for a wide variety of tissue types. concordex relies on analysis of k-nearest-neighbor (kNN) graphs. The tool is also useful for analysis of non-spatial transcriptomics data, and can elucidate the extent of concordance between partitions of cells derived from clustering algorithms, and transcriptomic similarity as represented in kNN graphs.	2	no	no
bioconductor-cotan	single_cell	COexpression Tables ANalysis; Statistical and computational method to analyze the co-expression of gene pairs at single cell level. It provides the foundation for single-cell gene interactome analysis. The basic idea is studying the zero UMI counts' distribution instead of focusing on positive counts; this is done with a generalized contingency tables framework. COTAN can effectively assess the correlated or anti-correlated expression of gene pairs. It provides a numerical index related to the correlation and an approximate p-value for the associated independence test. COTAN can also evaluate whether single genes are differentially expressed, scoring them with a newly defined global differentiation index. Moreover, this approach provides ways to plot and cluster genes according to their co-expression pattern with other genes, effectively helping the study of gene interactions and becoming a new tool to identify cell-identity marker genes.	1	no	no
bioconductor-csoa	single_cell	Calculate per-cell gene signature scores in scRNA-seq data using cell set overlaps; Cell Set Overlap Analysis (CSOA) is a tool for calculating per-cell gene signature scores in an scRNA-seq dataset. CSOA constructs a set for each gene in the signature, consisting of the cells that highly express the gene. Next, all overlaps of pairs of cell sets are computed, ranked, filtered and scored. The CSOA per-cell score is calculated by summing up all products of the overlap scores and the min-max-normalized expression of the two involved genes. CSOA can run on a Seurat object, a SingleCellExperiment object, a matrix and a dgCMatrix.	1	no	no
bioconductor-ctsv	single_cell	Identification of cell-type-specific spatially variable genes accounting for excess zeros; The R package CTSV implements the CTSV approach developed by Jinge Yu and Xiangyu Luo that detects cell-type-specific spatially variable genes accounting for excess zeros. CTSV directly models sparse raw count data through a zero-inflated negative binomial regression model, incorporates cell-type proportions, and performs hypothesis testing based on R package pscl. The package outputs p-values and q-values for genes in each cell type, and CTSV is scalable to datasets with tens of thousands of genes measured on hundreds of spots. CTSV can be installed in Windows, Linux, and Mac OS.	2	no	no
bioconductor-curatedatlasqueryr	single_cell	Queries the Human Cell Atlas; Provides access to a copy of the Human Cell Atlas, but with harmonised metadata. This allows for uniform querying across numerous datasets within the Atlas using common fields such as cell type, tissue type, and patient ethnicity. Usage involves first querying the metadata table for cells of interest, and then downloading the corresponding cells into a SingleCellExperiment object.	6	yes	no
bioconductor-cytomapper	single_cell	MCP wrapper for Bioconductor cytomapper.	2	no	no
bioconductor-dada2	genomics	Accurate, high-resolution sample inference from amplicon sequencing data; The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.	9	yes	no
bioconductor-data-packages	single_cell	A package to enable downloading and installation of Bioconductor data packages.	6	no	no
bioconductor-decipher	single_cell	Tools for curating, analyzing, and manipulating biological sequences; A toolset for deciphering and managing biological sequences.	5	no	no
bioconductor-decontam	single_cell	Identify Contaminants in Marker-gene and Metagenomics Sequencing Data; Simple statistical identification of contaminating sequence features in marker-gene or metagenomics data. Works on any kind of feature derived from environmental sequencing data (e.g. ASVs, OTUs, taxonomic groups, MAGs,...). Requires DNA quantitation data or sequenced negative control samples.	1	no	no
bioconductor-decontx	single_cell	Decontamination of single cell genomics data; This package contains implementation of DecontX (Yang et al. 2020), a decontamination algorithm for single-cell RNA-seq, and DecontPro (Yin et al. 2023), a decontamination algorithm for single cell protein expression data. DecontX is a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. DecontPro is a Bayesian method that estimates the level of contamination from ambient and background sources in CITE-seq ADT dataset and decontaminate the dataset.	2	no	no
bioconductor-deconvobuddies	single_cell	Helper Functions for LIBD Deconvolution; Funtions helpful for LIBD deconvolution project. Includes tools for marker finding with mean ratio, expression plotting, and plotting deconvolution results. Working to include DLPFC datasets.	6	no	no
bioconductor-delayedarray	general	A unified framework for working transparently with on-disk and in-memory array-like datasets; Wrapping an array-like object (typically an on-disk object) in a DelayedArray object allows one to perform common array operations on it without loading the object in memory. In order to reduce memory usage and optimize performance, operations on the object are either delayed or executed using a block processing mechanism. Note that this also works on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, ordinary arrays and, data frames.	1	no	no
bioconductor-delayedmatrixstats	transcriptomics	Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects; A port of the 'matrixStats' API for use with DelayedMatrix objects from the 'DelayedArray' package. High-performing functions operating on rows and columns of DelayedMatrix objects, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.	1	no	no
bioconductor-deseq2	transcriptomics	Differential gene expression analysis based on the negative binomial distribution; Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.	4	no	yes
bioconductor-despace	transcriptomics	DESpace: a framework to discover spatially variable genes and differential spatial patterns across conditions; Intuitive framework for identifying spatially variable genes (SVGs) and differential spatial variable pattern (DSP) between conditions via edgeR, a popular method for performing differential expression analyses. Based on pre-annotated spatial clusters as summarized spatial information, DESpace models gene expression using a negative binomial (NB), via edgeR, with spatial clusters as covariates. SVGs are then identified by testing the significance of spatial clusters. For multi-sample, multi-condition datasets, we again fit a NB model via edgeR, incorporating spatial clusters, conditions and their interactions as covariates. DSP genes-representing differences in spatial gene expression patterns across experimental conditions-are identified by testing the interaction between spatial clusters and conditions.	3	no	no
bioconductor-diffbind	transcriptomics	Differential Binding Analysis of ChIP-Seq Peak Data; Compute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions.	1	no	no
bioconductor-dino	single_cell	Normalization of Single-Cell mRNA Sequencing Data; Dino normalizes single-cell, mRNA sequencing data to correct for technical variation, particularly sequencing depth, prior to downstream analysis. The approach produces a matrix of corrected expression for which the dependency between sequencing depth and the full distribution of normalized expression; many existing methods aim to remove only the dependency between sequencing depth and the mean of the normalized expression. This is particuarly useful in the context of highly sparse datasets such as those produced by 10X genomics and other uninque molecular identifier (UMI) based microfluidics protocols for which the depth-dependent proportion of zeros in the raw expression data can otherwise present a challenge.	1	no	no
bioconductor-dirichletmultinomial	single_cell	MCP wrapper for Bioconductor dirichletmultinomial.	2	no	no
bioconductor-dnacopy	single_cell	MCP wrapper for Bioconductor dnacopy.	2	no	no
bioconductor-dose	pathway_enrichment	Disease Ontology Semantic and Enrichment analysis; This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.	6	yes	no
bioconductor-ebseq	general	An R package for gene and isoform differential expression analysis of RNA-seq data; Differential Expression analysis at both gene and isoform level using RNA-seq data.	1	no	no
bioconductor-edger	single_cell	MCP wrapper for Bioconductor edger.	2	no	no
bioconductor-ensembldb	genomics	Utilities to create and use Ensembl-based annotation databases; The package provides functions to create and use transcript centric annotation databases/packages. The annotation for the databases are directly fetched from Ensembl using their Perl API. The functionality and data is similar to that of the TxDb packages from the GenomicFeatures package, but, in addition to retrieve all gene/transcript models and annotations from the database, ensembldb provides a filter framework allowing to retrieve annotations for specific entries like genes encoded on a chromosome region or transcript models of lincRNA genes. EnsDb databases built with ensembldb contain also protein annotations and mappings between proteins and their encoding transcripts. Finally, ensembldb provides functions to map between genomic, transcript and protein coordinates.	6	yes	no
bioconductor-erma	single_cell	epigenomic road map adventures; Software and data to support epigenomic road map adventures.	1	no	no
bioconductor-escher	single_cell	Unified multi-dimensional visualizations with Gestalt principles; The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide this open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.	4	no	no
bioconductor-experimentsubset	single_cell	Manages subsets of data with Bioconductor Experiment objects; Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for one or more matrix-like assays along with the associated row and column data. Often only a subset of the original data is needed for down-stream analysis. For example, filtering out poor quality samples will require excluding some columns before analysis. The ExperimentSubset object is a container to efficiently manage different subsets of the same data without having to make separate objects for each new subset.	2	no	no
bioconductor-fgsea	pathway_enrichment	Fast Gene Set Enrichment Analysis; The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm allows to make more permutations and get more fine grained p-values, which allows to use accurate stantard approaches to multiple hypothesis correction.	3	yes	no
bioconductor-genefilter	single_cell	MCP wrapper for Bioconductor genefilter.	3	no	no
bioconductor-geneplotter	single_cell	MCP wrapper for Bioconductor geneplotter.	3	no	no
bioconductor-genomeinfodb	single_cell	Utilities for manipulating chromosome names, including modifying them to follow a particular naming style; Contains data and functions that define and allow translation between different chromosome sequence naming conventions (e.g., "chr1" versus "1"), including a function that attempts to place sequence names in their natural, rather than lexicographic, order.	4	no	no
bioconductor-genomeinfodbdata	single_cell	MCP wrapper for Bioconductor genomeinfodbdata.	2	no	no
bioconductor-genomicalignments	single_cell	MCP wrapper for Bioconductor genomicalignments.	1	no	no
bioconductor-genomicfeatures	single_cell	MCP wrapper for Bioconductor genomicfeatures.	1	no	no
bioconductor-genomicranges	transcriptomics	Representation and manipulation of genomic intervals; The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages, respectively. Both packages build on top of the GenomicRanges infrastructure.	11	no	no
bioconductor-geomxtools	single_cell	NanoString GeoMx Tools; Tools for NanoString Technologies GeoMx Technology. Package provides functions for reading in DCC and PKC files based on an ExpressionSet derived object. Normalization and QC functions are also included.	7	no	no
bioconductor-ggsc	single_cell	Visualizing Single Cell and Spatial Transcriptomics; Useful functions to visualize single cell and spatial data. It supports visualizing 'Seurat', 'SingleCellExperiment' and 'SpatialExperiment' objects through grammar of graphics syntax implemented in 'ggplot2'.	5	no	no
bioconductor-ggspavis	single_cell	Visualization functions for spatial transcriptomics data; Visualization functions for spatial transcriptomics data. Includes functions to generate several types of plots, including spot plots, feature (molecule) plots, reduced dimension plots, spot-level quality control (QC) plots, and feature-level QC plots, for datasets from the 10x Genomics Visium and other technological platforms. Datasets are assumed to be in either SpatialExperiment or SingleCellExperiment format.	4	no	no
bioconductor-ggtree	single_cell	an R package for visualization of tree and annotation data; 'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.	1	no	no
bioconductor-glmgampoi	single_cell	Fit a Gamma-Poisson Generalized Linear Model; Fit linear models to overdispersed count data. The package can estimate the overdispersion and fit repeated models for matrix input. It is designed to handle large input datasets as they typically occur in single cell RNA-seq experiments.	4	no	no
bioconductor-go.db	pathway_enrichment	MCP wrapper for Bioconductor go.db.	2	no	no
bioconductor-gosemsim	single_cell	MCP wrapper for Bioconductor gosemsim.	7	no	no
bioconductor-graph	single_cell	MCP wrapper for Bioconductor graph.	1	no	no
bioconductor-gsva	pathway_enrichment	MCP wrapper for Bioconductor gsva.	1	no	no
bioconductor-hcatonsildata	single_cell	Provide programmatic access to the tonsil cell atlas datasets; This package provides access to the scRNA-seq, scATAC-seq, multiome, CITE-seq and spatial transcriptomics (Visium) data generated by the tonsil cell atlas in the context of the Human Cell Atlas (HCA). The data is provided via the Bioconductor project in the form of SingleCellExperiments. Additionally, information on the whole compendium of identified cell types is provided in form of a glossary.	1	no	no
bioconductor-hdf5array	transcriptomics	HDF5 datasets as array-like objects in R; The HDF5Array package is an HDF5 backend for DelayedArray objects. It implements the HDF5Array, H5SparseMatrix, H5ADMatrix, and TENxMatrix classes, 4 convenient and memory-efficient array-like containers for representing and manipulating either: (1) a conventional (a.k.a. dense) HDF5 dataset, (2) an HDF5 sparse matrix (stored in CSR format), (3) the central matrix of an h5ad file (or any matrix in the /layers group), or (4) a 10x Genomics sparse matrix. All these containers are DelayedArray extensions and thus support all operations (delayed or block-processed) supported by DelayedArray objects.	4	no	no
bioconductor-hoodscanr	single_cell	Spatial cellular neighbourhood scanning in R; hoodscanR is an user-friendly R package providing functions to assist cellular neighborhood analysis of any spatial transcriptomics data with single-cell resolution. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. The package can result in cell-level neighborhood annotation output, along with funtions to perform neighborhood colocalization analysis and neighborhood-based cell clustering.	6	no	no
bioconductor-humanhippocampus2024	single_cell	Access to SRT and snRNA-seq data from spatial_HPC project; This is an ExperimentHub Data package that helps to access the spatially-resolved transcriptomics and single-nucleus RNA sequencing data. The datasets are generated from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. The datasets are based on [spatial_hpc](https: project by Lieber Institute for Brain Development (LIBD) researchers and collaborators.	2	no	no
bioconductor-imcdatasets	single_cell	Collection of publicly available imaging mass cytometry (IMC) datasets; The imcdatasets package provides access to publicly available IMC datasets. IMC is a technology that enables measurement of > 40 proteins from tissue sections. The generated images can be segmented to extract single cell data. Datasets typically consist of three elements: a SingleCellExperiment object containing single cell data, a CytoImageList object containing multichannel images and a CytoImageList object containing the cell masks that were used to extract the single cell data from the images.	2	no	no
bioconductor-imcrtools	single_cell	Methods for imaging mass cytometry data analysis; This R package supports the handling and analysis of imaging mass cytometry and other highly multiplexed imaging data. The main functionality includes reading in single-cell data after image segmentation and measurement, data formatting to perform channel spillover correction and a number of spatial analysis approaches. First, cell-cell interactions are detected via spatial graph construction; these graphs can be visualized with cells representing nodes and interactions representing edges. Furthermore, per cell, its direct neighbours are summarized to allow spatial clustering. Per image/grouping level, interactions between types of cells are counted, averaged and compared against random permutations. In that way, types of cells that interact more (attraction) or less (avoidance) frequently than expected by chance are detected.	4	no	no
bioconductor-impute	single_cell	MCP wrapper for Bioconductor impute.	2	no	no
bioconductor-infercnv	single_cell	MCP wrapper for Bioconductor infercnv.	3	no	no
bioconductor-interactivedisplaybase	single_cell	Base package for enabling powerful shiny web displays of Bioconductor objects; The interactiveDisplayBase package contains the the basic methods needed to generate interactive Shiny based display methods for Bioconductor objects.	1	no	no
bioconductor-iranges	single_cell	MCP wrapper for Bioconductor iranges.	5	no	no
bioconductor-irisfgm	single_cell	Comprehensive Analysis of Gene Interactivity Networks Based on Single-Cell RNA-Seq; Single-cell RNA-Seq data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically, the investigation of functional gene modules (FGM) can help to understand gene interactive networks and complex biological processes. QUBIC2 is recognized as one of the most efficient and effective tools for FGM identification from scRNA-Seq data. However, its availability is limited to a C implementation, and its applicative power is affected by only a few downstream analyses functionalities. We developed an R package named IRIS-FGM (integrative scRNA-Seq interpretation system for functional gene module analysis) to support the investigation of FGMs and cell clustering using scRNA-Seq data. Empowered by QUBIC2, IRIS-FGM can identify co-expressed and co-regulated FGMs, predict types/clusters, identify differentially expressed genes, and perform functional enrichment analysis. It is noteworthy that IRIS-FGM also applies Seurat objects that can be easily used in the Seurat vignettes.	1	no	no
bioconductor-jazzpanda	single_cell	Finding spatially relevant marker genes in image based spatial transcriptomics data; This package contains the function to find marker genes for image-based spatial transcriptomics data. There are functions to create spatial vectors from the cell and transcript coordiantes, which are passed as inputs to find marker genes. Marker genes are detected for every cluster by two approaches. The first approach is by permtuation testing, which is implmented in parallel for finding marker genes for one sample study. The other approach is to build a linear model for every gene. This approach can account for multiple samples and backgound noise.	3	no	no
bioconductor-keggrest	single_cell	MCP wrapper for Bioconductor keggrest.	6	no	no
bioconductor-limma	single_cell	MCP wrapper for Bioconductor limma.	1	no	no
bioconductor-lisaclust	single_cell	lisaClust: Clustering of Local Indicators of Spatial Association; lisaClust provides a series of functions to identify and visualise regions of tissue where spatial associations between cell-types is similar. This package can be used to provide a high-level summary of cell-type colocalization in multiplexed imaging data that has been segmented at a single-cell resolution.	5	no	no
bioconductor-mastr	pathway_enrichment	Markers Automated Screening Tool in R; mastR is an R package designed for automated screening of signatures of interest for specific research questions. The package is developed for generating refined lists of signature genes from multiple group comparisons based on the results from edgeR and limma differential expression (DE) analysis workflow. It also takes into account the background noise of tissue-specificity, which is often ignored by other marker generation tools. This package is particularly useful for the identification of group markers in various biological and medical applications, including cancer research and developmental biology.	3	no	no
bioconductor-matrixgenerics	single_cell	S4 Generic Summary Statistic Functions that Operate on Matrix-Like Objects; S4 generic functions modeled after the 'matrixStats' API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.	2	no	no
bioconductor-merfishdata	single_cell	Collection of public MERFISH datasets; MerfishData is an ExperimentHub package that serves publicly available datasets obtained with Multiplexed Error-Robust Fluorescence in situ Hybridization (MERFISH). MERFISH is a massively multiplexed single-molecule imaging technology capable of simultaneously measuring the copy number and spatial distribution of hundreds to tens of thousands of RNA species in individual cells. The scope of the package is to provide MERFISH data for benchmarking and analysis.	2	no	no
bioconductor-metabolomicsworkbenchr	single_cell	MCP wrapper for Bioconductor metabolomicsworkbenchr.	1	no	no
bioconductor-metapod	genomics	Meta-Analyses on P-Values of Differential Analyses; Implements a variety of methods for combining p-values in differential analyses of genome-scale datasets. Functions can combine p-values across different tests in the same analysis (e.g., genomic windows in ChIP-seq, exons in RNA-seq) or for corresponding tests across separate analyses (e.g., replicated comparisons, effect of different treatment conditions). Support is provided for handling log-transformed input p-values, missing values and weighting where appropriate.	2	no	no
bioconductor-mia	single_cell	Microbiome analysis; mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.	1	no	no
bioconductor-moleculeexperiment	utility	Prioritising a molecule-level storage of Spatial Transcriptomics Data; MoleculeExperiment contains functions to create and work with objects from the new MoleculeExperiment class. We introduce this class for analysing molecule-based spatial transcriptomics data (e.g., Xenium by 10X, Cosmx SMI by Nanostring, and Merscope by Vizgen). This allows researchers to analyse spatial transcriptomics data at the molecule level, and to have standardised data formats accross vendors.	7	no	no
bioconductor-mosim	transcriptomics	MCP wrapper for Bioconductor mosim.	1	no	no
bioconductor-mousegastrulationdata	single_cell	Single-Cell -omics Data across Mouse Gastrulation and Early Organogenesis; Provides processed and raw count data for single-cell RNA sequencing, single-cell ATAC-seq, and seqFISH (spatial transcriptomic) experiments performed along a timecourse of mouse gastrulation and early organogenesis.	3	no	no
bioconductor-mspurity	single_cell	Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics; msPurity R package was developed to: 1) Assess the spectral quality of fragmentation spectra by evaluating the "precursor ion purity". 2) Process fragmentation spectra. 3) Perform spectral matching. What is precursor ion purity? -What we call "Precursor ion purity" is a measure of the contribution of a selected precursor peak in an isolation window used for fragmentation. The simple calculation involves dividing the intensity of the selected precursor peak by the total intensity of the isolation window. When assessing MS/MS spectra this calculation is done before and after the MS/MS scan of interest and the purity is interpolated at the recorded time of the MS/MS acquisition. Additionally, isotopic peaks can be removed, low abundance peaks are removed that are thought to have limited contribution to the resulting MS/MS spectra and the isolation efficiency of the mass spectrometer can be used to normalise the intensities used for the calculation.	6	no	no
bioconductor-multiassayexperiment	single_cell	Software for the integration of multi-omics experiments in Bioconductor; Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.	5	no	no
bioconductor-multtest	single_cell	MCP wrapper for Bioconductor multtest.	2	no	no
bioconductor-mzr	general	parser for netCDF, mzXML and mzML and mzIdentML files (mass spectrometry data); mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a subset of the proteowizard library for mzXML, mzML and mzIdentML. The netCDF reading code has previously been used in XCMS.	1	no	no
bioconductor-nebulosa	single_cell	MCP wrapper for Bioconductor nebulosa.	2	no	no
bioconductor-nnsvg	single_cell	Scalable identification of spatially variable genes in spatially-resolved transcriptomics data; Method for scalable identification of spatially variable genes (SVGs) in spatially-resolved transcriptomics data. The method is based on nearest-neighbor Gaussian processes and uses the BRISC algorithm for model fitting and parameter estimation. Allows identification and ranking of SVGs with flexible length scales across a tissue slide or within spatial domains defined by covariates. Scales linearly with the number of spatial locations and can be applied to datasets containing thousands or more spatial locations.	1	no	no
bioconductor-noiseq	single_cell	MCP wrapper for Bioconductor noiseq.	2	no	no
bioconductor-orfhunter	single_cell	Predict open reading frames in nucleotide sequences; The ORFhunteR package is a R and C++ library for an automatic determination and annotation of open reading frames (ORF) in a large set of RNA molecules. It efficiently implements the machine learning model based on vectorization of nucleotide sequences and the random forest classification algorithm. The ORFhunteR package consists of a set of functions written in the R language in conjunction with C++. The efficiency of the package was confirmed by the examples of the analysis of RNA molecules from the NCBI RefSeq and Ensembl databases. The package can be used in basic and applied biomedical research related to the study of the transcriptome of normal as well as altered (for example, cancer) human cells.	5	no	no
bioconductor-org.ce.eg.db	single_cell	MCP wrapper for Bioconductor org.ce.eg.db.	6	no	no
bioconductor-org.hs.eg.db	single_cell	MCP wrapper for Bioconductor org.hs.eg.db.	8	no	no
bioconductor-org.mm.eg.db	single_cell	MCP wrapper for Bioconductor org.mm.eg.db.	5	no	no
bioconductor-partcnv	single_cell	Infer locally aneuploid cells using single cell RNA-seq data; This package uses a statistical framework for rapid and accurate detection of aneuploid cells with local copy number deletion or amplification. Our method uses an EM algorithm with mixtures of Poisson distributions while incorporating cytogenetics information (e.g., regional deletion or amplification) to guide the classification (partCNV). When applicable, we further improve the accuracy by integrating a Hidden Markov Model for feature selection (partCNVH).	3	no	no
bioconductor-phemd	single_cell	MCP wrapper for Bioconductor phemd.	1	no	no
bioconductor-phyloseq	single_cell	Handling and analysis of high-throughput microbiome census data; phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.	5	no	no
bioconductor-pipecomp	single_cell	pipeComp pipeline benchmarking framework; A simple framework to facilitate the comparison of pipelines involving various steps and parameters. The pipelineDefinition class represents pipelines as, minimally, a set of functions consecutively executed on the output of the previous one, and optionally accompanied by step-wise evaluation and aggregation functions. Given such an object, a set of alternative parameters/methods, and benchmark datasets, the runPipeline function then proceeds through all combinations arguments, avoiding recomputing the same step twice and compiling evaluations on the fly to avoid storing potentially large intermediate data.	1	no	no
bioconductor-poem	single_cell	POpulation-based Evaluation Metrics; This package provides a comprehensive set of external and internal evaluation metrics. It includes metrics for assessing partitions or fuzzy partitions derived from clustering results, as well as for evaluating subpopulation identification results within embeddings or graph representations. Additionally, it provides metrics for comparing spatial domain detection results against ground truth labels, and tools for visualizing spatial errors.	1	no	no
bioconductor-preprocesscore	single_cell	MCP wrapper for Bioconductor preprocesscore.	8	no	no
bioconductor-proteomicsannotationhubdata	single_cell	MCP wrapper for Bioconductor proteomicsannotationhubdata.	2	no	no
bioconductor-protgenerics	single_cell	MCP wrapper for Bioconductor protgenerics.	1	no	no
bioconductor-qvalue	single_cell	Q-value estimation for false discovery rate control; This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values and local FDR values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. The local FDR measures the posterior probability the null hypothesis is true given the test's p-value. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.	2	no	no
bioconductor-rbgl	single_cell	MCP wrapper for Bioconductor rbgl.	1	no	no
bioconductor-reactomegsa.data	single_cell	Companion data package for the ReactomeGSA package; Companion data sets to showcase the functionality of the ReactomeGSA package. This package contains proteomics and RNA-seq data of the melanoma B-cell induction study by Griss et al. and scRNA-seq data from Jerby-Arnon et al.	1	no	no
bioconductor-regionalst	pathway_enrichment	Investigating regions of interest and performing regional cell type-specific analysis with spatial transcriptomics data; This package analyze spatial transcriptomics data through cross-regional cell type-specific analysis. It selects regions of interest (ROIs) and identifys cross-regional cell type-specific differential signals. The ROIs can be selected using automatic algorithm or through manual selection. It facilitates manual selection of ROIs using a shiny application.	4	no	no
bioconductor-rforproteomics	single_cell	MCP wrapper for Bioconductor rforproteomics.	1	no	no
bioconductor-rgraphviz	single_cell	MCP wrapper for Bioconductor rgraphviz.	1	no	no
bioconductor-rhdf5	single_cell	MCP wrapper for Bioconductor rhdf5.	1	no	no
bioconductor-rhdf5filters	single_cell	HDF5 Compression Filters; Provides a collection of additional compression filters for HDF5 datasets. The package is intended to provide seemless integration with rhdf5, however the compiled filters can also be used with external applications.	1	no	no
bioconductor-rhdf5lib	single_cell	hdf5 library as an R package; Provides C and C++ hdf5 libraries.	1	no	no
bioconductor-rhtslib	single_cell	MCP wrapper for Bioconductor rhtslib.	1	no	no
bioconductor-rsamtools	single_cell	MCP wrapper for Bioconductor rsamtools.	5	yes	no
bioconductor-rsubread	transcriptomics	MCP wrapper for Bioconductor rsubread.	8	no	yes
bioconductor-rtracklayer	single_cell	MCP wrapper for Bioconductor rtracklayer.	4	no	no
bioconductor-rtracklayer copy	general	Auto-indexed MCP server for bioconductor-rtracklayer copy.	1	no	no
bioconductor-s4vectors	single_cell	Auto-indexed MCP server for bioconductor-s4vectors.	1	no	no
bioconductor-scaledmatrix	single_cell	Creating a DelayedMatrix of Scaled and Centered Values; Provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale() function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.	6	no	no
bioconductor-scalign	single_cell	An alignment and integration method for single cell genomics; An unsupervised deep learning method for data alignment, integration and estimation of per-cell differences in -omic data (e.g. gene expression) across datasets (conditions, tissues, species). See Johansen and Quon (2019) doi:10.1101/504944 for more details.	1	no	no
bioconductor-scarray.sat	single_cell	Large-scale single-cell RNA-seq data analysis using GDS files and Seurat; Extends the Seurat classes and functions to support Genomic Data Structure (GDS) files as a DelayedArray backend for data representation. It relies on the implementation of GDS-based DelayedMatrix in the SCArray package to represent single cell RNA-seq data. The common optimized algorithms leveraging GDS-based and single cell-specific DelayedMatrix (SC_GDSMatrix) are implemented in the SCArray package. SCArray.sat introduces a new SCArrayAssay class (derived from the Seurat Assay), which wraps raw counts, normalized expressions and scaled data matrix based on GDS-specific DelayedMatrix. It is designed to integrate seamlessly with the Seurat package to provide common data analysis in the SeuratObject-based workflow. Compared with Seurat, SCArray.sat significantly reduces the memory usage without downsampling and can be applied to very large datasets.	1	no	no
bioconductor-scater	single_cell	Single-Cell Analysis Toolkit for Gene Expression Data in R; A collection of tools for doing various analyses of single-cell RNA-seq gene expression data, with a focus on quality control and visualization.	1	no	no
bioconductor-scbfa	single_cell	MCP wrapper for Bioconductor scbfa.	2	no	no
bioconductor-scbubbletree	single_cell	Quantitative visual exploration of scRNA-seq data; scBubbletree is a quantitative method for the visual exploration of scRNA-seq data, preserving key biological properties such as local and global cell distances and cell density distributions across samples. It effectively resolves overplotting and enables the visualization of diverse cell attributes from multiomic single-cell experiments. Additionally, scBubbletree is user-friendly and integrates seamlessly with popular scRNA-seq analysis tools, facilitating comprehensive and intuitive data interpretation.	1	no	no
bioconductor-sccb2	single_cell	MCP wrapper for Bioconductor sccb2.	1	no	no
bioconductor-scclassifr	single_cell	Pretrained learning models for cell type prediction on single cell RNA-sequencing data; The package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables all users to quickly get a first annotation of the cell types present in their dataset without requiring prior knowledge. scClassifR also allows users to train their own models to predict new cell types based on specific research needs.	3	no	no
bioconductor-scdataviz	single_cell	MCP wrapper for Bioconductor scdataviz.	3	no	no
bioconductor-scdotplot	single_cell	Cluster a Single-cell RNA-seq Dot Plot; Dot plots of single-cell RNA-seq data allow for an examination of the relationships between cell groupings (e.g. clusters) and marker gene expression. The scDotPlot package offers a unified approach to perform a hierarchical clustering analysis and add annotations to the columns and/or rows of a scRNA-seq dot plot. It works with SingleCellExperiment and Seurat objects as well as data frames.	3	no	no
bioconductor-scfeatures	pathway_enrichment	scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction; scFeatures constructs multi-view representations of single-cell and spatial data. scFeatures is a tool that generates multi-view representations of single-cell and spatial data through the construction of a total of 17 feature types. These features can then be used for a variety of analyses using other software in Biocondutor.	2	no	no
bioconductor-scider	single_cell	Spatial cell-type inter-correlation by density in R; scider is an user-friendly R package providing functions to model the global density of cells in a slide of spatial transcriptomics data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. After modelling density, the package allows for serveral downstream analysis, including colocalization analysis, boundary detection analysis and differential density analysis.	5	no	no
bioconductor-scmageck	single_cell	MCP wrapper for Bioconductor scmageck.	4	no	no
bioconductor-scqtltools	single_cell	scQTLtools: an R/Bioconductor package for comprehensive identification and visualization of single-cell eQTLs; scQTLtools is a comprehensive R/Bioconductor package that facilitates end-to-end single-cell eQTL analysis, from preprocessing to visualization.	1	no	no
bioconductor-scran	single_cell	Methods for Single-Cell RNA-Seq Data Analysis; Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and other common tasks in routine single-cell analysis workflows.	1	no	no
bioconductor-screpertoire	single_cell	MCP wrapper for Bioconductor screpertoire.	1	no	no
bioconductor-scrnaseq	transcriptomics	MCP wrapper for Bioconductor scrnaseq.	1	no	no
bioconductor-sctreeviz	single_cell	R/Bioconductor package to interactively explore and visualize single cell RNA-seq datasets with hierarhical annotations; scTreeViz provides classes to support interactive data aggregation and visualization of single cell RNA-seq datasets with hierarchies for e.g. cell clusters at different resolutions. The TreeIndex class provides methods to manage hierarchy and split the tree at a given resolution or across resolutions. The TreeViz class extends SummarizedExperiment and can performs quick aggregations on the count matrix defined by clusters.	2	no	no
bioconductor-scuttle	single_cell	Single-Cell RNA-Seq Analysis Utilities; Provides basic utility functions for performing single-cell analyses, focusing on simple normalization, quality control and data transformations. Also provides some helper functions to assist development of other packages.	3	no	no
bioconductor-scvir	single_cell	experimental inferface from R to scvi-tools; This package defines interfaces from R to scvi-tools. A vignette works through the totalVI tutorial for analyzing CITE-seq data. Another vignette compares outputs of Chapter 12 of the OSCA book with analogous outputs based on totalVI quantifications. Future work will address other components of scvi-tools, with a focus on building understanding of probabilistic methods based on variational autoencoders.	5	no	no
bioconductor-seraster	single_cell	Rasterization Preprocessing Framework for Scalable Spatial Omics Data Analysis; SEraster is a rasterization preprocessing framework that aggregates cellular information into spatial pixels to reduce resource requirements for spatial omics data analysis. SEraster reduces the number of spatial points in spatial omics datasets for downstream analysis through a process of rasterization where single cells’ gene expression or cell-type labels are aggregated into equally sized pixels based on a user-defined resolution. SEraster is built on an R/Bioconductor S4 class called SpatialExperiment. SEraster can be incorporated with other packages to conduct downstream analyses for spatial omics datasets, such as detecting spatially variable genes.	3	no	no
bioconductor-shortread	single_cell	MCP wrapper for Bioconductor shortread.	6	no	no
bioconductor-signifinder	pathway_enrichment	Collection and implementation of public transcriptional cancer signatures; signifinder is an R package for computing and exploring a compendium of tumor signatures. It allows to compute a variety of signatures coming from public literature, based on gene expression values, and return single-sample (-cell/-spot) scores. Currently, signifinder collects more than 70 distinct signatures, relating to multiple tumors and multiple cancer processes.	1	no	no
bioconductor-singlecellexperiment	single_cell	S4 Classes for Single Cell Data; Defines a S4 class for storing data from single-cell experiments. This includes specialized methods to store and retrieve spike-in information, dimensionality reduction coordinates and size factors for each cell, along with the usual metadata for genes and libraries.	1	no	no
bioconductor-singlecellmultimodal	single_cell	MCP wrapper for Bioconductor singlecellmultimodal.	1	no	no
bioconductor-smoothclust	single_cell	smoothclust; Method for identification of spatial domains and spatially-aware clustering in spatial transcriptomics data. The method generates spatial domains with smooth boundaries by smoothing gene expression profiles across neighboring spatial locations, followed by unsupervised clustering. Spatial domains consisting of consistent mixtures of cell types may then be further investigated by applying cell type compositional analyses or differential analyses.	1	no	no
bioconductor-smoppix	single_cell	Analyze Single Molecule Spatial Omics Data Using the Probabilistic Index; Test for univariate and bivariate spatial patterns in spatial omics data with single-molecule resolution. The tests implemented allow for analysis of nested designs and are automatically calibrated to different biological specimens. Tests for aggregation, colocalization, gradients and vicinity to cell edge or centroid are provided.	4	no	no
bioconductor-sosta	single_cell	A package for the analysis of anatomical tissue structures in spatial omics data; sosta (Spatial Omics STructure Analysis) is a package for analyzing spatial omics data to explore tissue organization at the anatomical structure level. It reconstructs anatomically relevant structures based on molecular features or cell types. It further calculates a range of metrics at the structure level to quantitatively describe tissue architecture. The package is designed to integrate with other packages for the analysis of spatial omics data.	4	no	no
bioconductor-spacetrooper	single_cell	SpaceTrooper performs Quality Control analysis of Image-Based spatial; SpaceTrooper performs Quality Control analysis using data driven GLM models of Image-Based spatial data, providing exploration plots, QC metrics computation, outlier detection. It implements a GLM strategy for the detection of low quality cells in imaging-based spatial data (Transcriptomics and Proteomics). It additionally implements several plots for the visualization of imaging based polygons through the ggplot2 package.	5	no	no
bioconductor-spaniel	single_cell	MCP wrapper for Bioconductor spaniel.	2	no	no
bioconductor-spari	single_cell	Spatially Aware Adjusted Rand Index for Evaluating Spatial Transcritpomics Clustering; The R package used in the manuscript "Spatially Aware Adjusted Rand Index for Evaluating Spatial Transcritpomics Clustering".	3	no	no
bioconductor-sparsematrixstats	transcriptomics	Summary Statistics for Rows and Columns of Sparse Matrices; High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col / rowMedians, col / rowVars etc. Currently, the optimizations are limited to data in the column sparse format. This package is inspired by the matrixStats package by Henrik Bengtsson.	1	no	no
bioconductor-spatialcpie	single_cell	MCP wrapper for Bioconductor spatialcpie.	1	no	no
bioconductor-spatialdatasets	single_cell	Collection of spatial omics datasets; This is a collection of publically available spatial omics datasets. Where possible we have curated these datasets as either SpatialExperiments, MoleculeExperiments or CytoImageLists and included annotations of the sample characteristics.	3	no	no
bioconductor-spatialdecon	single_cell	MCP wrapper for Bioconductor spatialdecon.	1	no	no
bioconductor-spatialdmelxsim	single_cell	Spatial allelic expression counts for fly cross embryo; Spatial allelic expression counts from Combs & Fraser (2018), compiled into a SummarizedExperiment object. This package contains data of allelic expression counts of spatial slices of a fly embryo, a Drosophila melanogaster x Drosophila simulans cross. See the CITATION file for the data source, and the associated script for how the object was constructed from publicly available data.	4	no	no
bioconductor-spatialexperiment	single_cell	MCP wrapper for Bioconductor spatialexperiment.	2	no	no
bioconductor-spatialexperimentio	transcriptomics	Read in Xenium, CosMx, MERSCOPE or STARmapPLUS data as SpatialExperiment object; Read in imaging-based spatial transcriptomics technology data. Current available modules are for Xenium by 10X Genomics, CosMx by Nanostring, MERSCOPE by Vizgen, or STARmapPLUS from Broad Institute. You can choose to read the data in as a SpatialExperiment or a SingleCellExperiment object.	5	no	no
bioconductor-spatialfda	single_cell	A Tool for Spatial Multi-sample Comparisons; spatialFDA is a package to calculate spatial statistics metrics. The package takes a SpatialExperiment object and calculates spatial statistics metrics using the package spatstat. Then it compares the resulting functions across samples/conditions using functional additive models as implemented in the package refund. Furthermore, it provides exploratory visualisations using functional principal component analysis, as well implemented in refund.	5	no	no
bioconductor-spatialfeatureexperiment	single_cell	Integrating SpatialExperiment with Simple Features in sf; A new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.	2	no	no
bioconductor-spatialheatmap	single_cell	MCP wrapper for Bioconductor spatialheatmap.	5	no	no
bioconductor-spatialomicsoverlay	single_cell	Spatial Overlay for Omic Data from Nanostring GeoMx Data; Tools for NanoString Technologies GeoMx Technology. Package to easily graph on top of an OME-TIFF image. Plotting annotations can range from tissue segment to gene expression.	1	no	no
bioconductor-speckle	single_cell	Statistical methods for analysing single cell RNA-seq data; The speckle package contains functions for the analysis of single cell RNA-seq data. The speckle package currently contains functions to analyse differences in cell type proportions. There are also functions to estimate the parameters of the Beta distribution based on a given counts matrix, and a function to normalise a counts matrix to the median library size. There are plotting functions to visualise cell type proportions and the mean-variance relationship in cell type proportions and counts. As our research into specialised analyses of single cell data continues we anticipate that the package will be updated with new functions.	6	no	no
bioconductor-spoon	single_cell	Address the Mean-variance Relationship in Spatial Transcriptomics Data; This package addresses the mean-variance relationship in spatially resolved transcriptomics data. Precision weights are generated for individual observations using Empirical Bayes techniques. These weights are used to rescale the data and covariates, which are then used as input in spatially variable gene detection tools.	1	no	no
bioconductor-spotclean	single_cell	SpotClean adjusts for spot swapping in spatial transcriptomics data; SpotClean is a computational method to adjust for spot swapping in spatial transcriptomics data. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind mRNA. Ideally, unique molecular identifiers at a spot measure spot-specific expression, but this is often not the case due to bleed from nearby spots, an artifact we refer to as spot swapping. SpotClean is able to estimate the contamination rate in observed data and decontaminate the spot swapping effect, thus increase the sensitivity and precision of downstream analyses.	2	no	no
bioconductor-spotsweeper	single_cell	Spatially-aware quality control for spatial transcriptomics; Spatially-aware quality control (QC) software for both spot-level and artifact-level QC in spot-based spatial transcripomics, such as 10x Visium. These methods calculate local (nearest-neighbors) mean and variance of standard QC metrics (library size, unique genes, and mitochondrial percentage) to identify outliers spot and large technical artifacts.	4	no	no
bioconductor-standr	single_cell	Spatial transcriptome analyses of Nanostring's DSP data in R; standR is an user-friendly R package providing functions to assist conducting good-practice analysis of Nanostring's GeoMX DSP data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. standR allows data inspection, quality control, normalization, batch correction and evaluation with informative visualizations.	1	no	no
bioconductor-statial	single_cell	A package to identify changes in cell state relative to spatial associations; Statial is a suite of functions for identifying changes in cell state. The functionality provided by Statial provides robust quantification of cell type localisation which are invariant to changes in tissue structure. In addition to this Statial uncovers changes in marker expression associated with varying levels of localisation. These features can be used to explore how the structure and function of different cell types may be altered by the agents they are surrounded with.	5	no	no
bioconductor-stjoincount	single_cell	stJoincount - Join count statistic for quantifying spatial correlation between clusters; stJoincount facilitates the application of join count analysis to spatial transcriptomic data generated from the 10x Genomics Visium platform. This tool first converts a labeled spatial tissue map into a raster object, in which each spatial feature is represented by a pixel coded by label assignment. This process includes automatic calculation of optimal raster resolution and extent for the sample. A neighbors list is then created from the rasterized sample, in which adjacent and diagonal neighbors for each pixel are identified. After adding binary spatial weights to the neighbors list, a multi-categorical join count analysis is performed to tabulate "joins" between all possible combinations of label pairs. The function returns the observed join counts, the expected count under conditions of spatial randomness, and the variance calculated under non-free sampling. The z-score is then calculated as the difference between observed and expected counts, divided by the square root of the variance.	4	no	no
bioconductor-summarizedexperiment	single_cell	A container (S4 class) for matrix-like assays; The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.	1	no	no
bioconductor-svp	transcriptomics	Predicting cell states and their variability in single-cell or spatial omics data; SVP uses the distance between cells and cells, features and features, cells and features in the space of MCA to build nearest neighbor graph, then uses random walk with restart algorithm to calculate the activity score of gene sets (such as cell marker genes, kegg pathway, go ontology, gene modules, transcription factor or miRNA target sets, reactome pathway, ...), which is then further weighted using the hypergeometric test results from the original expression matrix. To detect the spatially or single cell variable gene sets or (other features) and the spatial colocalization between the features accurately, SVP provides some global and local spatial autocorrelation method to identify the spatial variable features. SVP is developed based on SingleCellExperiment class, which can be interoperable with the existing computing ecosystem.	2	no	no
bioconductor-tenxvisiumdata	single_cell	Visium spatial gene expression data by 10X Genomics; Collection of Visium spatial gene expression datasets by 10X Genomics, formatted into objects of class SpatialExperiment. Data cover various organisms and tissues, and include: single- and multi-section experiments, as well as single sections subjected to both whole transcriptome and targeted panel analysis. Datasets may be used for testing of and as examples in packages, for tutorials and workflow demonstrations, or similar purposes.	1	no	no
bioconductor-tenxxeniumdata	single_cell	Collection of Xenium spatial data by 10X genomics; Collection of Xenium spatial transcriptomics datasets provided by 10x Genomics, formatted into the Bioconductor classes, the SpatialExperiment or SpatialFeatureExperiment (SFE), to facilitate seamless integration into various applications, including examples, demonstrations, and tutorials. The constructed data objects include gene expression profiles, per-transcript location data, centroid, segmentation boundaries (e.g., cell or nucleus boundaries), and image.	1	no	no
bioconductor-tidyomics	single_cell	Easily install and load the tidyomics ecosystem; The tidyomics ecosystem is a set of packages for ’omic data analysis that work together in harmony; they share common data representations and API design, consistent with the tidyverse ecosystem. The tidyomics package is designed to make it easy to install and load core packages from the tidyomics ecosystem with a single command.	3	no	no
bioconductor-tidyspatialexperiment	single_cell	SpatialExperiment with tidy principles; tidySpatialExperiment provides a bridge between the SpatialExperiment package and the tidyverse ecosystem. It creates an invisible layer that allows you to interact with a SpatialExperiment object as if it were a tibble; enabling the use of functions from dplyr, tidyr, ggplot2 and plotly. But, underneath, your data remains a SpatialExperiment object.	2	no	no
bioconductor-treesummarizedexperiment	single_cell	TreeSummarizedExperiment: a S4 Class for Data with Tree Structures; TreeSummarizedExperiment has extended SingleCellExperiment to include hierarchical information on the rows or columns of the rectangular data.	1	no	no
bioconductor-tximport	transcriptomics	MCP wrapper for Bioconductor tximport.	3	no	yes
bioconductor-variantannotation	single_cell	MCP wrapper for Bioconductor variantannotation.	3	yes	no
bioconductor-vectrapolarisdata	single_cell	Vectra Polaris and Vectra 3 multiplex single-cell imaging data; Provides two multiplex imaging datasets collected on Vectra instruments at the University of Colorado Anschutz Medical Campus. Data are provided as a Spatial Experiment objects. Data is provided in tabular form and has been segmented and phenotyped using Inform software. Raw .tiff files are not included.	4	no	no
bioconductor-visiumio	single_cell	Import Visium data from the 10X Space Ranger pipeline; The package allows users to readily import spatial data obtained from either the 10X website or from the Space Ranger pipeline. Supported formats include tar.gz, h5, and mtx files. Multiple files can be imported at once with *List type of functions. The package represents data mainly as SpatialExperiment objects.	2	no	no
bioconductor-weberdivechalcdata	single_cell	Spatially-resolved transcriptomics and single-nucleus RNA-sequencing data from the locus coeruleus (LC) in postmortem human brain samples; Spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from the locus coeruleus (LC) in postmortem human brain samples. Data were generated with the 10x Genomics Visium SRT and 10x Genomics Chromium snRNA-seq platforms. Datasets are stored in SpatialExperiment and SingleCellExperiment formats.	2	no	no
bioconductor-xcms	single_cell	LC-MS and GC-MS Data Analysis; Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.	1	no	no
bioconductor-xenlite	single_cell	Simple classes and methods for managing Xenium datasets; Define a relatively light class for managing Xenium data using Bioconductor. Address use of parquet for coordinates, SpatialExperiment for assay and sample data. Address serialization and use of cloud storage.	5	no	no
bioconductor-xvector	single_cell	MCP wrapper for Bioconductor xvector.	8	no	no
bioconductor-zlibbioc	single_cell	MCP wrapper for Bioconductor zlibbioc.	1	no	no
biopython	single_cell	Freely available tools for computational molecular biology.	1	no	no
blast	transcriptomics	MCP wrapper for blast.	5	yes	yes
blast-legacy	single_cell	The Basic Local Alignment Search Tool (BLAST) finds regions of local similarity between sequences.	2	yes	no
bowtie	transcriptomics	MCP wrapper for bowtie.	2	no	no
bowtie2	transcriptomics	MCP wrapper for bowtie2.	1	no	yes
bpipe	single_cell	MCP wrapper for bpipe.	10	no	no
brooklyn_plot	genomics	MCP wrapper for brooklyn plot.	1	no	no
busco	single_cell	Assessment of assembly completeness using Universal Single Copy Orthologs; BUSCO provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs selected from OrthoDB.	4	no	yes
bwa	genomics	MCP wrapper for bwa.	11	no	yes
bx-python	single_cell	Tools for manipulating biological data, particularly multiple sequence alignments.	5	no	no
c-ares	single_cell	c-ares is a C library for asynchronous DNS requests (including name resolves).	2	no	no
cascade-reg	single_cell	Causal discovery of gene regulatory programs from single-cell genomics; CASCADE stands for Causality-Aware Single-Cell Adaptive.	7	no	no
cd-hit	single_cell	MCP wrapper for cd hit.	1	no	no
cdbtools	single_cell	CDB (Constant DataBase) indexing and retrieval tools for FASTA files.	3	no	no
cell2cell	pathway_enrichment	Inferring cell-cell interactions from transcriptomes with cell2cell.	2	no	no
cellitac	single_cell	Cell type identification using Transcription factor Analysis and Chromatin accessibility.	1	no	no
cellqc	single_cell	Cellqc standardizes the qualiy control of single-cell RNA-Seq (scRNA) data to render clean feature count matrices.	1	no	no
cellrank	general	MCP wrapper for cellrank.	1	no	no
cellsnake	single_cell	cellsnake, a user-friendly tool for single cell RNA sequencing analysis.	5	no	no
celltypist	single_cell	MCP wrapper for celltypist.	3	no	no
celltypist-so	single_cell	Fork of CellTypist without leidenalg in the package requirements.	2	no	no
checkatlas	single_cell	One liner tool to check the quality of your single-cell atlases.	2	no	no
checkm-genome	genomics	Assess the quality of microbial genomes recovered from isolates, single cells, and metagenomes.	16	no	no
circexplorer2	genomics	Circular RNA analysis toolkits.	4	no	no
circos	transcriptomics	MCP wrapper for circos.	6	no	no
clustalo	single_cell	MCP wrapper for clustalo.	1	no	no
clustalw	single_cell	MCP wrapper for clustalw.	2	no	no
cmappy	single_cell	Assorted tools for interacting with .gct, .gctx, .grp, and .gmt files as well as other Connectivity Map (Broad Institute) data/tools.	5	no	no
cnmf	single_cell	MCP wrapper for cnmf.	5	no	no
cnvkit	genomics	Copy number variant detection from high-throughput sequencing.	24	no	no
comebin	genomics	COMEBin allows effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning.	4	no	no
comet-ms	single_cell	Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool.	1	no	no
constellations	single_cell	MCP wrapper for constellations.	1	no	no
cooler	genomics	Sparse binary format for genomic interaction matrices.	15	no	no
cooltools	genomics	Analysis tools for genomic interaction data stored in .cool format.	9	no	no
coreutils	single_cell	The GNU Core Utilities are the basic file, shell and text manipulation utilities of the GNU operating system. These are the core utilities which are expected to exist on every operating system.	12	no	no
cosg	single_cell	Accurate and fast cell marker gene identification with COSG.	1	no	no
cospar	pathway_enrichment	A toolkit for dynamic inference of cell fate by integrating state and lineage information.	6	no	no
crispresso2	genomics	A software pipeline designed to enable rapid and intuitive interpretation of genome editing experiments.	6	no	no
crispritz	genomics	CRISPRitz, tool package for CRISPR experiments assessment and analysis.	4	no	no
crisprme	single_cell	CRISPRme, tool package for CRISPR experiments assessment and analysis.	1	no	no
cromwell	transcriptomics	MCP wrapper for cromwell.	4	no	no
csvtk	utility	MCP wrapper for csvtk.	40	no	yes
csvtk copy	utility	Auto-indexed MCP server for csvtk copy.	1	no	no
cutadapt	single_cell	Trim adapters from high-throughput sequencing reads.	3	no	no
cwltool	single_cell	Common Workflow Language reference implementation.	6	no	no
cytoscape	single_cell	MCP wrapper for cytoscape.	1	no	no
cytotrace2-python	single_cell	MCP wrapper for cytotrace2 python.	1	no	no
cyvcf2	single_cell	A cython wrapper around htslib built for fast parsing of Variant Call Format (VCF) files.	1	no	no
dca	single_cell	Count autoencoder for scRNA-seq denoising.	1	no	no
ddocent	genomics	dDocent is an interactive bash wrapper to QC, assemble, map, and call SNPs from all types of RAD data.	1	no	no
deblur	single_cell	Deblur is a greedy deconvolution algorithm based on known read error profiles.	2	no	no
decoupler	pathway_enrichment	MCP wrapper for decoupler.	7	no	no
deeptools	single_cell	A set of user-friendly tools for normalization and visualzation of deep-sequencing data.	1	no	no
deeptoolsintervals	single_cell	A python module creating/accessing GTF-based interval trees with associated meta-data.	1	no	no
delly	single_cell	MCP wrapper for delly.	3	no	no
dendropy	single_cell	MCP wrapper for dendropy.	5	no	no
diamond	single_cell	MCP wrapper for diamond.	17	no	yes
diamond copy	general	Auto-indexed MCP server for diamond copy.	1	no	no
disease-gene-qa	single_cell	MCP wrapper for disease gene qa.	3	yes	no
dnaio	single_cell	Read and write FASTA and FASTQ files efficiently.	5	no	no
doubletdetection	single_cell	Method to detect and enable removal of doublets from single-cell RNA-sequencing.	3	no	no
dropkick	single_cell	Automated scRNA-seq filtering.	2	no	no
dsh-bio	single_cell	MCP wrapper for dsh bio.	2	no	no
dxpy	utility	DNAnexus Platform API bindings for Python.".	12	no	no
easy_vitessce	single_cell	A package to easily use Vitessce to create interactive plots for single-cell data.	4	no	no
echidna	single_cell	Mapping genotype to phenotype through joint probabilistic modeling of single-cell gene expression and chromosomal copy number variation.	2	no	no
emboss	single_cell	The European Molecular Biology Open Software Suite.	13	no	no
ena-webin-cli	single_cell	MCP wrapper for ena webin cli.	2	no	no
ensembl-vep	utility	Ensembl Variant Effect Predictor; The VEP determines the effect of your variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions.	3	yes	no
entrez-direct	single_cell	Entrez Direct (EDirect) - Access to NCBI's Entrez databases; Entrez Direct (EDirect) provides access to Entrez, the NCBI's suite of interconnected databases (publication, sequence, structure, gene, variation, expression, etc.) from a Unix terminal window. Search terms are entered as command-line arguments. Individual operations are connected with Unix pipes to construct multi-step queries. Selected records can then be retrieved in a variety of formats.	10	no	no
epic	single_cell	Chip-Seq broad peak/domain finder.	3	no	no
episcanpy	single_cell	Epigenomics Single-Cell Analysis in Python.	1	no	no
eva-sub-cli	single_cell	EVA Submission Command Line Interface.	6	no	no
f5c	single_cell	MCP wrapper for f5c.	6	no	no
famsa	single_cell	MCP wrapper for famsa.	1	no	no
fast5	single_cell	A C++ header-only library for reading Oxford Nanopore Fast5 files.	2	no	no
fastani	single_cell	FastANI is developed for fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI).	1	no	no
fastdtw	single_cell	MCP wrapper for fastdtw.	2	no	no
fastp	single_cell	MCP wrapper for fastp.	1	no	no
fastqc	transcriptomics	Auto-indexed MCP server for fastqc.	1	no	yes
fasttree	single_cell	MCP wrapper for fasttree.	1	no	no
fermi2	transcriptomics	MCP wrapper for fermi2.	6	no	no
fgbio	single_cell	MCP wrapper for fgbio.	11	no	no
filechunkio	single_cell	FileChunkIO represents a chunk of an OS-level file containing bytes data.	1	no	no
flagx	single_cell	FLAG-X: FLow cytometry Automated Gating toolboX.	2	no	no
flye	single_cell	MCP wrapper for flye.	1	no	no
foldseek	single_cell	Auto-indexed MCP server for foldseek.	1	no	no
freebayes	genomics	MCP wrapper for freebayes.	1	no	yes
ftputil	single_cell	High-level FTP client library (virtual file system and more).	7	no	no
fwdpy11	single_cell	MCP wrapper for fwdpy11.	3	no	no
galaxy-lib	single_cell	Subset of Galaxy (http: core code base designed to be used a library.	5	no	no
gatk	genomics	MCP wrapper for gatk.	15	no	yes
gatk4	genomics	MCP wrapper for gatk4.	10	no	yes
gatk4-spark	single_cell	MCP wrapper for gatk4 spark.	5	no	no
gdk-pixbuf	single_cell	MCP wrapper for gdk pixbuf.	4	no	no
gecode	single_cell	Generic constraint development environment.	2	no	no
gemini	general	a lightweight db framework for disease and population genetics.	1	yes	no
gene-trajectory-python	single_cell	Compute gene trajectories; Gene Trajectory is a Python package that computes and analyzes gene trajectories in single-cell data.	1	no	no
genecircuitry	pathway_enrichment	GeneCircuitry: TRN analysis from single-cell data (Scanpy, CellOracle, Hotspot); A modular, checkpoint-enabled pipeline for TRN analysis from.	2	no	no
geneimpacts	genomics	prioritize effects of variant annotations from VEP, SnpEff, et al.	2	yes	no
genenotebook	general	Auto-indexed MCP server for genenotebook.	1	no	no
genoboo	genomics	A collaborative notebook for comparative genomics (active fork of GeneNoteBook).	3	no	no
genomad	general	Identification of mobile genetic elements.	1	no	no
genomepy	single_cell	Install and use genomes & gene annotations the easy way!	11	no	no
genometools-genometools	genomics	GenomeTools genome analysis system.	9	no	no
gffread	transcriptomics	MCP wrapper for gffread.	1	no	no
gffutils	genomics	Work with GFF and GTF files in a flexible database framework.	11	yes	yes
ghostscript	single_cell	An interpreter for the PostScript language and for PDF.	7	no	no
gimmemotifs	genomics	Motif prediction pipeline and various motif-related tools.	11	yes	no
glimmerhmm	single_cell	MCP wrapper for glimmerhmm.	1	no	no
gmap	genomics	MCP wrapper for gmap.	7	no	no
gneiss	single_cell	Compositional data analysis tools and visualizations.	6	no	no
gnuplot	single_cell	MCP wrapper for gnuplot.	1	no	no
gofasta	genomics	MCP wrapper for gofasta.	8	yes	no
goleft	single_cell	MCP wrapper for goleft.	6	no	no
gridss	single_cell	Auto-indexed MCP server for gridss.	1	no	no
gromacs	single_cell	GROMACS is a versatile package to perform molecular dynamics.	9	no	no
gseapy	pathway_enrichment	Gene Set Enrichment Analysis in Python.	5	yes	no
gsmap	single_cell	MCP wrapper for gsmap.	9	no	no
gtdbtk	single_cell	MCP wrapper for gtdbtk.	8	no	no
harpy	genomics	Process raw haplotagging data, from raw sequences to phased haplotypes; Harpy is a command-line tool to easily process platform-agnostic linked-read or WGS data. It uses.	17	no	no
hhsuite	transcriptomics	MCP wrapper for hhsuite.	2	no	no
hicexplorer	single_cell	Set of programs to process, analyze and visualize Hi-C and capture Hi-C data.	9	no	no
hifiasm	single_cell	MCP wrapper for hifiasm.	1	no	no
hisat2	transcriptomics	MCP wrapper for hisat2.	7	no	yes
hmmer	single_cell	Biosequence analysis using profile hidden Markov models.	11	no	no
htseq	transcriptomics	HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments.	1	no	yes
htslib	genomics	C library for high-throughput sequencing data formats.	4	no	no
humann	genomics	HUMAnN: The HMP Unified Metabolic Analysis Network, version 3.	1	no	no
humann2	genomics	HUMAnN2: The HMP Unified Metabolic Analysis Network 2.	10	no	no
hyphy	single_cell	Auto-indexed MCP server for hyphy.	1	no	no
igv	single_cell	MCP wrapper for igv.	5	no	no
igv-reports	genomics	Creates self-contained html pages for visual variant review with IGV (igv.js).	4	no	no
illumina-interop	single_cell	The Illumina InterOp libraries are a set of common routines used for reading and writing InterOp metric files. These metric files are binary files produced during a run providing detailed statistics about a run. In a few cases, the metric files are produced after a run during secondary analysis (index metrics) or for faster display of a subset of the original data (collapsed quality scores).	7	no	no
infernal	single_cell	Infernal is for searching DNA sequence databases for RNA structure and sequence similarities; Infernal ("INFERence of RNA ALignment") is for searching DNA sequence databases for RNA structure and sequence similarities.	11	no	no
insilicoseq	genomics	A sequencing simulator.	2	no	no
intarna	single_cell	Efficient RNA-RNA interaction prediction incorporating seeding and accessibility of interacting sites.	1	no	no
involucro	single_cell	MCP wrapper for involucro.	3	no	no
iow	single_cell	Implementation of Balanced Parentheses; An implementation of the balanced parentheses tree structure as described by.	2	no	no
ipyrad	genomics	Interactive assembly and analysis of RAD-seq data sets.	3	no	no
ipython-cluster-helper	transcriptomics	Tool to easily start up an IPython cluster on different schedulers.	7	no	no
iqtree	transcriptomics	MCP wrapper for iqtree.	1	no	no
itsxpress	single_cell	ITSxpress: Software to rapidly trim the Internally Transcribed Spacer (ITS) region from FASTQ files.	1	no	no
ivar	single_cell	MCP wrapper for ivar.	7	no	no
jalview	single_cell	MCP wrapper for jalview.	5	no	no
java-jdk	single_cell	MCP wrapper for java jdk.	3	no	no
jbrowse2	genomics	The JBrowse 2 Genome Browser.	12	no	no
jcvi	genomics	Python utility libraries on genome assembly, annotation, and comparative genomics; JCVI utility libraries.	30	no	no
jellyfish	single_cell	MCP wrapper for jellyfish.	11	no	no
jq	utility	MCP wrapper for jq.	1	no	no
k8	single_cell	MCP wrapper for k8.	3	no	no
kaiju	transcriptomics	MCP wrapper for kaiju.	11	no	no
kalign2	single_cell	Kalign is a fast and accurate multiple sequence alignment algorithm designed to align large numbers of protein sequences.	1	no	no
kallisto	transcriptomics	MCP wrapper for kallisto.	10	no	yes
kb-python	transcriptomics	A wrapper for the kallisto; bustools workflow for single-cell RNA-seq pre-processing.	6	no	no
khipu-metabolomics	single_cell	Python library for generalized, low-level annotation of MS metabolomics.	1	no	no
kma	single_cell	Auto-indexed MCP server for kma.	1	no	no
kmc	single_cell	MCP wrapper for kmc.	2	no	no
kmer-jellyfish	single_cell	Jellyfish is a tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence.	8	no	no
kraken2	metagenomics	MCP wrapper for kraken2.	3	no	yes
krona	single_cell	Krona Tools is a set of scripts to create Krona charts from several Bioinformatics tools as well as from text and XML files.	6	no	no
last	single_cell	MCP wrapper for last.	1	no	no
lastz	transcriptomics	MCP wrapper for lastz.	2	no	no
liana	transcriptomics	LIANA+: a one-stop-shop framework for cell-cell communication.	1	no	no
libcifpp	single_cell	Library containing code to manipulate mmCIF and PDB files; This library, libcifpp, is a generic CIF library with some specific additions to work with mmCIF files.	5	no	no
libdb	general	The Berkeley DB embedded database system.	1	no	no
libdeflate	single_cell	libdeflate is a library for fast, whole-buffer DEFLATE-based compression and decompression.	4	no	no
libsequence	single_cell	A C++ class library for evolutionary genetics.	1	yes	no
local-bio-cache	genomics	Offline local bio cache MCP server for registering FASTA collections, optionally building local BLAST databases, running local BLAST-like sequence search with Python fallback, running pairwise sequence alignment, and querying cached TF binding tables from GTRD, ENCODE, or ChIP-Atlas; Use this server when remote BLAST, UniProt sequence search, or TF binding APIs are unstable. It provides local sequence grounding, local UniProt-like search over predownloaded FASTA files, and offline TF binding lookup over curated flat files.	11	no	no
locarna	single_cell	MCP wrapper for locarna.	6	no	no
macs2	single_cell	Model Based Analysis for ChIP-Seq data.	12	no	no
mafft	single_cell	MCP wrapper for mafft.	3	no	yes
mageck	pathway_enrichment	MCP wrapper for mageck.	6	no	no
mameshiba	single_cell	mameshiba installs only the dependencies needed to run MameShiba; mameshiba is a minimal conda meta-package that installs all dependencies required.	3	no	no
mappy	single_cell	MCP wrapper for mappy.	2	no	no
markerrepo	single_cell	A tool for marker list management and annotation in the single cell context.	4	no	no
mash	single_cell	MCP wrapper for mash.	8	no	no
maxquant	single_cell	MCP wrapper for maxquant.	3	no	no
mcl	single_cell	Auto-indexed MCP server for mcl.	1	no	no
medaka	genomics	A tool to create consensus sequences and variant calls from nanopore sequencing data using neural networks.	7	no	no
megahit	single_cell	MCP wrapper for megahit.	2	no	no
meme	single_cell	Motif-based sequence analysis tools.	2	no	no
mentalist	single_cell	The MLST pipeline developed by the PathOGiST research group.	4	no	no
metagenome-atlas	transcriptomics	ATLAS - Three commands to start analysing your metagenome data; Atlas is a easy to use metagenomic pipeline.	2	no	no
metaphlan	metagenomics	Metagenomic Phylogenetic Analysis; MetaPhlAn is a computational tool for profiling the composition of microbial.	2	no	yes
metaphlan2	metagenomics	Metagenomic Phylogenetic Analysis; MetaPhlAn is a computational tool for profiling the composition of microbial.	4	no	yes
mikado	genomics	A Python3 annotation program to select the best gene model in each locus.	8	no	no
minced	single_cell	MCP wrapper for minced.	1	no	no
miniasm	single_cell	MCP wrapper for miniasm.	2	no	no
minimap2	single_cell	MCP wrapper for minimap2.	3	no	yes
minvar	genomics	A tool to detect minority variants in HIV-1 and HCV populations.	1	no	no
mitos	single_cell	MITOS is a tool for the annotation of metazoan mitochondrial genomes.	4	no	no
mlst	transcriptomics	Auto-indexed MCP server for mlst.	1	no	no
mmtf-python	single_cell	A decoding libary for the PDB mmtf format.	2	no	no
mobivision-m	transcriptomics	MobiVision-M is a linux based software design specifically for single-microbe RNA sequencing analysis.	3	no	no
moments	single_cell	Evolutionary inference using SFS and LD statistics.	6	no	no
mosdepth	single_cell	MCP wrapper for mosdepth.	1	no	no
mothur	single_cell	MCP wrapper for mothur.	5	no	no
msisensor-pro	genomics	MCP wrapper for msisensor pro.	2	no	no
msproteomicstools	single_cell	msproteomicstools is a Python library that can be used in LC-MS/MS based proteomics. It features a core library called.	1	no	no
msstitch	single_cell	MS proteomics post processing utilities.	22	no	no
multiqc	transcriptomics	Aggregate results from bioinformatics analyses across many samples into a single report.	9	no	yes
multiqc-bcbio	single_cell	MultiQC plugin for bcbio report visualization.	4	no	no
multiqc-xenium-extra	single_cell	MultiQC plugin for extra Xenium spatial transcriptomics analysis.	1	no	no
multivelo	utility	MCP wrapper for multivelo.	1	no	no
mummer	single_cell	MCP wrapper for mummer.	1	no	no
munkres	single_cell	MCP wrapper for munkres.	1	no	no
muscle	single_cell	MCP wrapper for muscle.	2	no	no
mysql-connector-c	single_cell	MySQL Connector/C, the C interface for communicating with MySQL servers.	1	no	no
mztosqlite	single_cell	MCP wrapper for mztosqlite.	1	no	no
nanocomp	single_cell	Comparing runs of Oxford Nanopore sequencing data and alignments.	2	no	no
nanoget	single_cell	Functions to extract information from Oxford Nanopore sequencing data and alignments.	4	no	no
nanomath	single_cell	A few simple math function for other Oxford Nanopore processing scripts.	3	no	no
nanoplot	single_cell	Plotting suite for long read sequencing data and alignments.	1	no	no
nanopolish	genomics	Signal-level algorithms for MinION data.	6	no	no
ncbi-amrfinderplus	general	AMRFinderPlus finds antimicrobial resistance and other genes in protein or nucleotide sequences; This software and the accompanying database are designed to.	1	yes	no
ncbi-datasets-pylib	genomics	Easily gather data from across NCBI databases.	12	yes	no
ncbi-genome-download	single_cell	Download genome files from the NCBI FTP server.	2	no	no
ncbi-ngs-sdk	single_cell	NGS is a new, domain-specific API for accessing reads, alignments and pileups produced from Next Generation Sequencing.	1	no	no
ncbi-vdb	single_cell	SRA tools database engine; "VDB is the database engine that all SRA tools use. It is a columnar database.	1	no	no
ncls	single_cell	A fast interval tree-like implementation in C, wrapped for the Python ecosystem. Basically a static interval-tree that is silly fast for both construction and lookups.	4	no	no
nextalign	single_cell	MCP wrapper for nextalign.	3	no	no
nextclade	single_cell	MCP wrapper for nextclade.	7	no	no
nextflow	single_cell	MCP wrapper for nextflow.	9	no	no
nf-core	single_cell	Python package with helper tools for the nf-core community.	15	no	no
nglview	single_cell	An IPython widget to interactively view molecular structures and trajectories. Utilizes the embeddable NGL Viewer for rendering.	6	no	no
ngmlr	genomics	MCP wrapper for ngmlr.	1	no	no
ngs-smap	genomics	SMAP is a software package that analyzes next-generation DNA sequencing read mapping distributions and performs haplotype calling to create multi-allelic molecular markers.	1	no	no
ngs-tools	single_cell	Reusable tools for working with next-generation sequencing (NGS) data.	1	no	no
novae	single_cell	Graph-based foundation model for spatial transcriptomics data.	4	no	no
novoalign	single_cell	MCP wrapper for novoalign.	2	no	no
ont-fast5-api	single_cell	Oxford Nanopore Technologies fast5 API software.	5	no	no
openms-thirdparty	single_cell	A helper package to install OpenMS TOPP tools with all their compatible and conda-available versions of adapted thirdparty tools.	1	no	no
opticlust	single_cell	Single cell clustering and recommendations at a glance.	5	no	no
orthofinder	single_cell	MCP wrapper for orthofinder.	1	no	yes
ourotools	single_cell	A comprehensive toolkit for quality control and analysis of single-cell long-read RNA-seq data; Ouro-Tools is a novel, comprehensive computational pipeline for long-read scRNA-seq with the following key features. Ouro-Tools (1) normalizes mRNA size distributions and (2) detects mRNA 7-methylguanosine caps to integrate multiple single-cell long-read RNA-sequencing experiments across modalities and characterize full-length transcripts, respectively.	1	no	no
pairix	transcriptomics	MCP wrapper for pairix.	5	no	no
palantir	single_cell	Palantir for modeling continuous cell state and cell fate choices in single cell data.	11	no	no
paml	single_cell	A package of programs for phylogenetic analyses of DNA or protein sequences using maximum likelihood.	5	no	no
pandaseq	general	Auto-indexed MCP server for pandaseq.	1	no	no
pango-designation	single_cell	MCP wrapper for pango designation.	1	no	no
pangolearn	single_cell	Store of the trained model for pangolin to access.	2	no	no
pangolin	single_cell	Phylogenetic Assignment of Named Global Outbreak LINeages.	1	no	no
parasail-python	single_cell	Python bindings for the parasail C library containing implementations of pairwise sequence alignment algorithms.	1	no	no
pasta	single_cell	MCP wrapper for pasta.	1	no	no
paste-bio	single_cell	A computational method to align and integrate spatial transcriptomics experiments.	2	no	no
pcdl	single_cell	physicell data loader (pcdl) provides a platform independent, python3 based, pip installable interface to transform output, generated with the PhysiCell agent based modeling framework, into standard formats.	18	no	no
peakqc	single_cell	Quality control of single cell ATAC-seq data based on fragment length distributions.	1	no	no
peptide-shaker	general	MCP wrapper for peptide shaker.	4	no	no
perl-aceperl	transcriptomics	MCP wrapper for perl aceperl.	1	no	no
perl-algorithm-diff	transcriptomics	MCP wrapper for perl algorithm diff.	4	no	no
perl-algorithm-munkres	transcriptomics	Auto-indexed MCP server for perl-algorithm-munkres.	1	no	no
perl-alien-build	general	Build external dependencies for use in CPAN.	1	no	no
perl-alien-libxml2	single_cell	Installs the C libxml2 library on your system.	1	no	no
perl-app-cpanminus	transcriptomics	MCP wrapper for perl app cpanminus.	1	no	no
perl-appconfig	transcriptomics	MCP wrapper for perl appconfig.	1	no	no
perl-archive-tar	transcriptomics	MCP wrapper for perl archive tar.	3	no	no
perl-autoloader	transcriptomics	MCP wrapper for perl autoloader.	2	no	no
perl-base	transcriptomics	MCP wrapper for perl base.	1	no	no
perl-bio-asn1-entrezgene	transcriptomics	MCP wrapper for perl bio asn1 entrezgene.	1	no	no
perl-bio-coordinate	single_cell	Methods for dealing with genomic coordinates.	3	no	no
perl-bio-featureio	transcriptomics	MCP wrapper for perl bio featureio.	1	no	no
perl-bio-phylo	transcriptomics	Auto-indexed MCP server for perl-bio-phylo.	1	no	no
perl-bio-samtools	transcriptomics	MCP wrapper for perl bio samtools.	1	no	no
perl-bio-searchio-hmmer	single_cell	A parser for HMMER2 and HMMER3 output (hmmscan, hmmsearch, hmmpfam).	2	no	no
perl-bio-tools-phylo-paml	single_cell	Parses output from the PAML programs codeml, baseml, basemlg, codemlsites and yn00.	5	no	no
perl-bio-tools-run-alignment-clustalw	single_cell	Object for the calculation of a multiple sequence alignment from a set of unaligned sequences or alignments using the Clustalw program.	1	no	no
perl-bioperl	transcriptomics	Auto-indexed MCP server for perl-bioperl.	1	no	no
perl-bioperl-core	transcriptomics	MCP wrapper for perl bioperl core.	3	no	no
perl-bioperl-run	transcriptomics	Auto-indexed MCP server for perl-bioperl-run.	1	no	no
perl-business-isbn	transcriptomics	MCP wrapper for perl business isbn.	6	no	no
perl-business-isbn-data	single_cell	data pack for Business::ISBN.	7	no	no
perl-capture-tiny	transcriptomics	MCP wrapper for perl capture tiny.	1	no	no
perl-carp	transcriptomics	Auto-indexed MCP server for perl-carp.	1	no	no
perl-cgi	transcriptomics	MCP wrapper for perl cgi.	1	no	no
perl-class-inspector	transcriptomics	MCP wrapper for perl class inspector.	1	no	no
perl-class-load	transcriptomics	Auto-indexed MCP server for perl-class-load.	1	no	no
perl-class-load-xs	transcriptomics	Auto-indexed MCP server for perl-class-load-xs.	1	no	no
perl-common-sense	transcriptomics	MCP wrapper for perl common sense.	1	no	no
perl-compress-raw-zlib	transcriptomics	MCP wrapper for perl compress raw zlib.	4	no	no
perl-config-general	transcriptomics	MCP wrapper for perl config general.	2	no	no
perl-constant	transcriptomics	MCP wrapper for perl constant.	1	no	no
perl-convert-binary-c	transcriptomics	MCP wrapper for perl convert binary c.	1	no	no
perl-convert-binhex	transcriptomics	MCP wrapper for perl convert binhex.	1	no	no
perl-cpan-meta	transcriptomics	Auto-indexed MCP server for perl-cpan-meta.	1	no	no
perl-cpan-meta-requirements	single_cell	A set of version requirements for a CPAN dist.	4	no	no
perl-crypt-rc4	transcriptomics	MCP wrapper for perl crypt rc4.	4	no	no
perl-data-dumper	transcriptomics	MCP wrapper for perl data dumper.	1	no	no
perl-data-optlist	transcriptomics	MCP wrapper for perl data optlist.	1	no	no
perl-date-format	transcriptomics	MCP wrapper for perl date format.	1	no	no
perl-dbi	transcriptomics	MCP wrapper for perl dbi.	3	no	no
perl-devel-globaldestruction	transcriptomics	Auto-indexed MCP server for perl-devel-globaldestruction.	1	no	no
perl-devel-overloadinfo	single_cell	introspect overloaded operators.	1	no	no
perl-devel-stacktrace	transcriptomics	MCP wrapper for perl devel stacktrace.	4	no	no
perl-digest-md5	transcriptomics	MCP wrapper for perl digest md5.	1	no	no
perl-digest-perl-md5	transcriptomics	MCP wrapper for perl digest perl md5.	2	no	no
perl-digest-sha1	single_cell	Perl interface to the SHA-1 algorithm.	3	no	no
perl-dist-checkconflicts	transcriptomics	Auto-indexed MCP server for perl-dist-checkconflicts.	1	no	no
perl-dynaloader	transcriptomics	Auto-indexed MCP server for perl-dynaloader.	1	no	no
perl-encode	transcriptomics	MCP wrapper for perl encode.	1	no	no
perl-encode-locale	transcriptomics	MCP wrapper for perl encode locale.	1	no	no
perl-error	transcriptomics	MCP wrapper for perl error.	2	no	no
perl-eval-closure	transcriptomics	Auto-indexed MCP server for perl-eval-closure.	1	no	no
perl-exception-class	transcriptomics	MCP wrapper for perl exception class.	1	no	no
perl-exporter	transcriptomics	MCP wrapper for perl exporter.	4	no	no
perl-extutils-cbuilder	transcriptomics	MCP wrapper for perl extutils cbuilder.	5	no	no
perl-extutils-makemaker	transcriptomics	MCP wrapper for perl extutils makemaker.	4	no	no
perl-ffi-checklib	single_cell	Check that a library is available for FFI.	10	no	no
perl-file-sort	transcriptomics	MCP wrapper for perl file sort.	2	no	no
perl-file-spec	transcriptomics	MCP wrapper for perl file spec.	2	no	no
perl-file-which	transcriptomics	MCP wrapper for perl file which.	2	no	no
perl-font-afm	transcriptomics	MCP wrapper for perl font afm.	1	no	no
perl-getopt-long	transcriptomics	MCP wrapper for perl getopt long.	6	no	no
perl-graph	transcriptomics	MCP wrapper for perl graph.	2	no	no
perl-graphviz	transcriptomics	MCP wrapper for perl graphviz.	1	no	no
perl-html-element-extended	transcriptomics	MCP wrapper for perl html element extended.	1	no	no
perl-html-formatter	transcriptomics	MCP wrapper for perl html formatter.	1	no	no
perl-html-parser	transcriptomics	MCP wrapper for perl html parser.	2	no	no
perl-html-tableextract	transcriptomics	MCP wrapper for perl html tableextract.	3	no	no
perl-html-tagset	transcriptomics	MCP wrapper for perl html tagset.	2	no	no
perl-html-tidy	transcriptomics	MCP wrapper for perl html tidy.	1	no	no
perl-html-tree	transcriptomics	MCP wrapper for perl html tree.	1	no	no
perl-html-treebuilder-xpath	transcriptomics	MCP wrapper for perl html treebuilder xpath.	1	no	no
perl-http-cookies	transcriptomics	MCP wrapper for perl http cookies.	9	no	no
perl-http-daemon	transcriptomics	MCP wrapper for perl http daemon.	1	no	no
perl-http-date	transcriptomics	MCP wrapper for perl http date.	5	no	no
perl-http-negotiate	transcriptomics	MCP wrapper for perl http negotiate.	2	no	no
perl-image-info	transcriptomics	MCP wrapper for perl image info.	2	no	no
perl-image-size	transcriptomics	MCP wrapper for perl image size.	1	no	no
perl-importer	transcriptomics	MCP wrapper for perl importer.	5	no	no
perl-io-compress	transcriptomics	MCP wrapper for perl io compress.	2	no	no
perl-io-html	transcriptomics	MCP wrapper for perl io html.	4	no	no
perl-io-sessiondata	transcriptomics	MCP wrapper for perl io sessiondata.	4	no	no
perl-io-string	transcriptomics	MCP wrapper for perl io string.	4	no	no
perl-io-stringy	transcriptomics	MCP wrapper for perl io stringy.	4	no	no
perl-io-tty	transcriptomics	MCP wrapper for perl io tty.	1	no	no
perl-io-zlib	transcriptomics	MCP wrapper for perl io zlib.	2	no	no
perl-ipc-cmd	transcriptomics	MCP wrapper for perl ipc cmd.	1	no	no
perl-ipc-run	transcriptomics	Auto-indexed MCP server for perl-ipc-run.	1	no	no
perl-ipc-sharelite	single_cell	Lightweight interface to shared memory.	1	no	no
perl-jcode	transcriptomics	MCP wrapper for perl jcode.	1	no	no
perl-json	transcriptomics	MCP wrapper for perl json.	5	no	no
perl-json-pp	single_cell	JSON::XS compatible pure-Perl module.	2	no	no
perl-json-xs	transcriptomics	MCP wrapper for perl json xs.	4	no	no
perl-lib	genomics	MCP wrapper for perl lib.	8	no	no
perl-libwww-perl	transcriptomics	MCP wrapper for perl libwww perl.	9	no	no
perl-libxml-perl	transcriptomics	MCP wrapper for perl libxml perl.	1	no	no
perl-list-moreutils	transcriptomics	MCP wrapper for perl list moreutils.	10	no	no
perl-list-moreutils-xs	transcriptomics	MCP wrapper for perl list moreutils xs.	1	no	no
perl-locale-maketext-simple	transcriptomics	MCP wrapper for perl locale maketext simple.	1	no	no
perl-lwp-mediatypes	transcriptomics	MCP wrapper for perl lwp mediatypes.	5	no	no
perl-lwp-simple	transcriptomics	Auto-indexed MCP server for perl-lwp-simple.	1	no	no
perl-mailtools	transcriptomics	MCP wrapper for perl mailtools.	1	no	no
perl-math-bezier	transcriptomics	MCP wrapper for perl math bezier.	1	no	no
perl-math-derivative	transcriptomics	MCP wrapper for perl math derivative.	3	no	no
perl-math-random	transcriptomics	MCP wrapper for perl math random.	6	no	no
perl-math-round	transcriptomics	MCP wrapper for perl math round.	1	no	no
perl-math-spline	transcriptomics	MCP wrapper for perl math spline.	1	no	no
perl-metabolomics-fragment-annotation	transcriptomics	MCP wrapper for perl metabolomics fragment annotation.	1	no	no
perl-mime-base64	transcriptomics	Auto-indexed MCP server for perl-mime-base64.	1	no	no
perl-mime-lite	transcriptomics	MCP wrapper for perl mime lite.	5	no	no
perl-mime-types	transcriptomics	MCP wrapper for perl mime types.	1	no	no
perl-module-build	transcriptomics	MCP wrapper for perl module build.	4	no	no
perl-module-corelist	transcriptomics	MCP wrapper for perl module corelist.	8	no	no
perl-module-load-conditional	transcriptomics	MCP wrapper for perl module load conditional.	3	no	no
perl-module-metadata	transcriptomics	MCP wrapper for perl module metadata.	11	no	no
perl-module-runtime	transcriptomics	MCP wrapper for perl module runtime.	1	no	no
perl-module-runtime-conflicts	single_cell	Provide information on conflicts for Module::Runtime.	1	no	no
perl-moo	transcriptomics	MCP wrapper for perl moo.	1	no	no
perl-moose	transcriptomics	MCP wrapper for perl moose.	1	no	no
perl-mozilla-ca	transcriptomics	Auto-indexed MCP server for perl-mozilla-ca.	1	no	no
perl-net-http	transcriptomics	MCP wrapper for perl net http.	5	no	no
perl-net-ssleay	transcriptomics	MCP wrapper for perl net ssleay.	2	no	no
perl-number-format	transcriptomics	MCP wrapper for perl number format.	7	no	no
perl-ole-storage_lite	transcriptomics	MCP wrapper for perl ole storage lite.	1	no	no
perl-package-deprecationmanager	single_cell	Manage deprecation warnings for your distribution.	1	no	no
perl-package-stash	transcriptomics	MCP wrapper for perl package stash.	3	no	no
perl-params-check	transcriptomics	MCP wrapper for perl params check.	1	no	no
perl-params-util	transcriptomics	MCP wrapper for perl params util.	1	no	no
perl-params-validate	transcriptomics	MCP wrapper for perl params validate.	1	no	no
perl-parent	transcriptomics	MCP wrapper for perl parent.	7	no	no
perl-parse-recdescent	transcriptomics	MCP wrapper for perl parse recdescent.	4	no	no
perl-pod-escapes	transcriptomics	MCP wrapper for perl pod escapes.	1	no	no
perl-pod-usage	transcriptomics	MCP wrapper for perl pod usage.	2	no	no
perl-postscript	transcriptomics	MCP wrapper for perl postscript.	4	no	no
perl-regexp-common	transcriptomics	MCP wrapper for perl regexp common.	5	no	no
perl-role-tiny	transcriptomics	MCP wrapper for perl role tiny.	4	no	no
perl-sereal	transcriptomics	MCP wrapper for perl sereal.	1	no	no
perl-sereal-decoder	transcriptomics	MCP wrapper for perl sereal decoder.	3	no	no
perl-set-intervaltree	transcriptomics	MCP wrapper for perl set intervaltree.	8	no	no
perl-set-intspan	transcriptomics	Auto-indexed MCP server for perl-set-intspan.	1	no	no
perl-set-scalar	transcriptomics	Auto-indexed MCP server for perl-set-scalar.	1	no	no
perl-soap-lite	transcriptomics	MCP wrapper for perl soap lite.	4	no	no
perl-sort-naturally	transcriptomics	MCP wrapper for perl sort naturally.	2	no	no
perl-spreadsheet-parseexcel	utility	MCP wrapper for perl spreadsheet parseexcel.	4	no	no
perl-spreadsheet-writeexcel	transcriptomics	MCP wrapper for perl spreadsheet writeexcel.	2	no	no
perl-sub-exporter	transcriptomics	MCP wrapper for perl sub exporter.	5	no	no
perl-sub-exporter-progressive	transcriptomics	MCP wrapper for perl sub exporter progressive.	5	no	no
perl-sub-identify	transcriptomics	MCP wrapper for perl sub identify.	1	no	no
perl-sub-name	single_cell	MCP wrapper for perl sub name.	1	no	no
perl-sub-quote	single_cell	Efficient generation of subroutines via string eval.	8	no	no
perl-sub-uplevel	transcriptomics	MCP wrapper for perl sub uplevel.	2	no	no
perl-svg	transcriptomics	Auto-indexed MCP server for perl-svg.	1	no	no
perl-task-weaken	transcriptomics	MCP wrapper for perl task weaken.	6	no	no
perl-template-toolkit	transcriptomics	MCP wrapper for perl template toolkit.	3	no	no
perl-test	transcriptomics	MCP wrapper for perl test.	2	no	no
perl-test-deep	transcriptomics	MCP wrapper for perl test deep.	3	no	no
perl-test-differences	transcriptomics	MCP wrapper for perl test differences.	4	no	no
perl-test-exception	transcriptomics	MCP wrapper for perl test exception.	4	no	no
perl-test-fatal	transcriptomics	MCP wrapper for perl test fatal.	1	no	no
perl-test-harness	transcriptomics	MCP wrapper for perl test harness.	1	no	no
perl-test-most	transcriptomics	Auto-indexed MCP server for perl-test-most.	1	no	no
perl-test-warn	transcriptomics	MCP wrapper for perl test warn.	3	no	no
perl-text-diff	transcriptomics	Auto-indexed MCP server for perl-text-diff.	1	no	no
perl-text-parsewords	transcriptomics	Auto-indexed MCP server for perl-text-parsewords.	1	no	no
perl-tie-ixhash	transcriptomics	MCP wrapper for perl tie ixhash.	5	no	no
perl-time-hires	transcriptomics	MCP wrapper for perl time hires.	15	no	no
perl-timedate	transcriptomics	Auto-indexed MCP server for perl-timedate.	1	no	no
perl-tree-dag_node	transcriptomics	MCP wrapper for perl tree dag node.	6	no	no
perl-try-tiny	transcriptomics	MCP wrapper for perl try tiny.	6	no	no
perl-types-serialiser	transcriptomics	Auto-indexed MCP server for perl-types-serialiser.	1	no	no
perl-unicode-map	transcriptomics	MCP wrapper for perl unicode map.	1	no	no
perl-uri	transcriptomics	MCP wrapper for perl uri.	9	no	no
perl-url-encode	single_cell	Encoding and decoding of application/x-www-form-urlencoded encoding.	6	no	no
perl-version	single_cell	Structured version objects.	7	no	no
perl-www-robotrules	transcriptomics	MCP wrapper for perl www robotrules.	4	no	no
perl-xml-dom-xpath	transcriptomics	Auto-indexed MCP server for perl-xml-dom-xpath.	1	no	no
perl-xml-filter-buffertext	transcriptomics	MCP wrapper for perl xml filter buffertext.	1	no	no
perl-xml-libxml	transcriptomics	MCP wrapper for perl xml libxml.	5	no	no
perl-xml-libxslt	transcriptomics	MCP wrapper for perl xml libxslt.	1	no	no
perl-xml-namespacesupport	single_cell	MCP wrapper for perl xml namespacesupport.	1	no	no
perl-xml-parser	transcriptomics	MCP wrapper for perl xml parser.	1	no	no
perl-xml-regexp	transcriptomics	MCP wrapper for perl xml regexp.	4	no	no
perl-xml-sax	transcriptomics	MCP wrapper for perl xml sax.	6	no	no
perl-xml-sax-base	transcriptomics	MCP wrapper for perl xml sax base.	3	no	no
perl-xml-sax-expat	transcriptomics	MCP wrapper for perl xml sax expat.	1	no	no
perl-xml-twig	transcriptomics	MCP wrapper for perl xml twig.	5	no	no
perl-xml-xpath	transcriptomics	MCP wrapper for perl xml xpath.	5	no	no
perl-xml-xpathengine	transcriptomics	MCP wrapper for perl xml xpathengine.	1	no	no
perl-xsloader	transcriptomics	MCP wrapper for perl xsloader.	4	no	no
perl-yaml	transcriptomics	MCP wrapper for perl yaml.	9	no	no
phyml	single_cell	MCP wrapper for phyml.	1	no	no
piaso	single_cell	PIASO: Precise Integrative Analysis of Single-cell Omics; PIASO is a Python toolkit for precise integrative analysis of single-cell omics data.	2	no	no
picard	single_cell	MCP wrapper for picard.	10	no	no
picard copy	general	Auto-indexed MCP server for picard copy.	1	no	no
picard-slim	general	Auto-indexed MCP server for picard-slim.	1	no	no
pilon	general	Auto-indexed MCP server for pilon.	1	no	no
pixelator	single_cell	A command-line tool and library to process and analyze sequencing data from Molecular Pixelation (MPX) assays.	10	no	no
planemo	general	Command-line utilities to assist in building tools for the Galaxy project (https://galaxyproject.org).	1	no	no
plink	single_cell	Auto-indexed MCP server for plink.	1	no	no
poa	general	Auto-indexed MCP server for poa.	1	no	no
portcullis	single_cell	Splice junction analysis and filtering from BAM files.	9	no	no
pplacer	single_cell	Auto-indexed MCP server for pplacer.	1	no	no
prank	single_cell	MCP wrapper for prank.	4	no	no
primer3	single_cell	Design PCR primers from DNA sequence. From mispriming libraries to sequence quality data to the generation of internal oligos, primer3 does it.	5	no	no
primer3-py	general	Python bindings for Primer3.	1	yes	no
prodigal	transcriptomics	MCP wrapper for prodigal.	2	no	no
prokka	transcriptomics	MCP wrapper for prokka.	7	no	yes
prophyle	single_cell	ProPhyle is an accurate, resource-frugal and deterministic phylogeny-based metagenomic classifier.	8	no	no
proteinortho	transcriptomics	MCP wrapper for proteinortho.	5	no	no
proteomiqon-peptidedb	single_cell	MCP wrapper for proteomiqon peptidedb.	1	no	no
proteomiqon-peptidespectrummatching	single_cell	MCP wrapper for proteomiqon peptidespectrummatching.	1	no	no
pubchempy	single_cell	MCP wrapper for pubchempy.	6	no	no
py2bit	single_cell	MCP wrapper for py2bit.	5	no	no
pybedtools	genomics	Wraps BEDTools for use in Python and adds many additional features.	20	yes	yes
pybigwig	single_cell	A python extension written in C for quick access to bigWig files.	7	no	no
pybiolib	general	BioLib Python Client.	1	no	no
pycistopic	single_cell	MCP wrapper for pycistopic.	6	no	no
pyfaidx	general	pyfaidx: efficient pythonic random access to fasta subsequences.	1	yes	no
pyfastx	single_cell	MCP wrapper for pyfastx.	7	no	no
pyhmmer	single_cell	Cython bindings and Python interface to HMMER3.	6	no	no
pyranges	transcriptomics	Performant Pythonic GenomicRanges.	7	no	no
pyrle	general	Genomic Rle-objects for Python.	1	no	no
pyrodigal	transcriptomics	MCP wrapper for pyrodigal.	1	no	no
pyroe	general	MCP wrapper for pyroe.	5	no	no
pyrovelocity	single_cell	Probabilistic RNA velocity for cell fate uncertainty estimation.	1	no	no
pysam	genomics	Pysam is a Python module for reading and manipulating SAM files. It's a lightweight wrapper of the htslib C-API, the same one that powers samtools, bcftools, and tabix.	11	no	no
pysftp	single_cell	A friendly face on SFTP.	6	no	no
pyspoa	single_cell	Python binding to spoa library.	1	no	no
pytabix	single_cell	Fast random access to sorted files compressed with bgzip and indexed by tabix.	3	no	no
pyteomics	single_cell	A framework for proteomics data analysis.	8	no	no
python-edlib	single_cell	Lightweight, super fast C/C++ (& Python) library for sequence alignment using edit (Levenshtein) distance.	1	no	no
pyvcf	genomics	A Variant Call Format reader for Python.	1	no	no
pyvcf3	genomics	A Variant Call Format reader for Python.	4	yes	no
qcatch	single_cell	QCatch: Quality Control downstream of alevin-fry / simpleaf.	2	no	no
qiime	general	Quantitative Insights Into Microbial Ecology.	1	no	no
qualimap	transcriptomics	MCP wrapper for qualimap.	6	no	no
quast	genomics	Quality Assessment Tool for Genome Assemblies.	1	no	no
r-abdiv	single_cell	Alpha and Beta Diversity Measures; 'A collection of measures for measuring ecological diversity.	10	no	no
r-acidbase	single_cell	Low-level base functions imported by Acid Genomics packages.	11	no	no
r-archr	transcriptomics	This package is designed to streamline scATAC analyses in R.	8	no	no
r-azimuth	single_cell	Azimuth is a Shiny app demonstrating a query-reference mapping algorithm for single-cell data.	1	no	no
r-basejump	single_cell	Base functions for bioinformatics and R package development.	1	no	no
r-beyondcell	single_cell	Tool for the Analysis of tumour therapeutic heterogeneity in single-cell RNA-seq; Beyondcell is a methodology for the identification of drug vulnerabilities in single-cell RNA-seq (scRNA-seq) data. To this end, Beyondcell focuses on the analysis of drug-related commonalities between cells by classifying them into distinct Therapeutic Clusters (TCs).	7	no	no
r-cdseq	single_cell	Estimate cell-type-specific gene expression profiles and sample-specific cell-type proportions simultaneously using bulk sequencing data. Kang et al. (2019) doi:10.1371/journal.pcbi.1007510.	3	no	no
r-dwls	single_cell	Deconvolution of bulk mRNA data using single-cell RNAseq to provide cell type specific signatures.	6	no	no
r-epitrace	single_cell	Inference of cell age and phylogeny from single cell ATAC data.	6	no	no
r-flanders	transcriptomics	Fast colocalization using AnnData objects in R; flanders is an R package designed to seamlessly convert finemapping output files from the nf-flanders pipeline.	3	no	no
r-goalie	single_cell	Assertive check functions for defensive R programming.	11	no	no
r-mams	single_cell	R package for Matrix and Analysis Metadata Standards.	1	no	no
r-redeemr	single_cell	R package for Regulatory multi-omics with Deep Mitochondrial mutation profiling; Introduce a new approach for single-cell Regulatory multi-omics (transcriptomics and chromatin accessibility) with Deep Mitochondrial mutation profiling (~10-fold increase in detection rate), or ReDeeM. redeemR is the R package that facilitates mutation refining, lineage tracing, as well multiomics integration analysis.	1	no	no
r-restfulr	single_cell	Models a RESTful service as if it were a nested R list.	5	no	no
r-saige	single_cell	SAIGE is an R package with Scalable and Accurate Implementation of Generalized mixed model (Chen, H. et al. 2016); SAIGE is an R package with Scalable and Accurate Implementation of Generalized.	1	no	no
r-sceasy	single_cell	A package providing functions to convert between different single-cell data formats.	1	no	no
r-scopfunctions	single_cell	An R package of functions for single cell -omics analysis.	8	no	no
r-scpred	single_cell	MCP wrapper for r scpred.	3	no	no
r-seurat	single_cell	MCP wrapper for r seurat.	9	no	no
r-seurat-data	single_cell	Single cell RNA sequencing datasets can be large, consisting of matrices that contain expression data for several thousand features across several thousand cells. This package is designed to easily install, manage, and learn about various single-cell datasets, provided Seurat objects and distributed as independent packages.	5	no	no
r-seurat-disk	single_cell	The h5Seurat file format is specifically designed for the storage and analysis of multi-modal single-cell and spatially-resolved expression experiments, for example, from CITE-seq or 10X Visium technologies. It holds all molecular information and associated metadata, including (for example) nearest-neighbor graphs, dimensional reduction information, spatial coordinates and image data, and cluster labels. We also support rapid and on-disk conversion between h5Seurat and AnnData objects, with the goal of enhancing interoperability between Seurat and Scanpy.	4	no	no
r-seurat-scripts	single_cell	MCP wrapper for r seurat scripts.	1	no	no
r-signac	single_cell	MCP wrapper for r signac.	3	no	no
racon	genomics	Auto-indexed MCP server for racon.	1	no	no
raxml	single_cell	Phylogenetics - Randomized Axelerated Maximum Likelihood.	5	no	no
recognizer	general	A tool for domain based annotation with the COG database; reCOGnizer performs domain based annotation with RPS-BLAST, using.	1	no	no
repeatmasker	single_cell	RepeatMasker is a program that screens DNA sequences for interspersed repeats and low complexity DNA sequences.	2	no	no
rgi	genomics	This tool provides a preliminary annotation of your DNA sequence(s) based upon the data available in The Comprehensive Antibiotic Resistance Database (CARD). Hits to genes tagged with Antibiotic Resistance ontology terms will be highlighted. As CARD expands to include more pathogens, genomes, plasmids, and ontology terms this tool will grow increasingly powerful in providing first-pass detection of antibiotic resistance associated genes. See license at CARD website.	9	no	no
rnastructure	single_cell	RNAstructure is a complete package for RNA and DNA secondary structure prediction and analysis. It includes algorithms for secondary structure prediction, including facility to predict base pairing probabilities. It also can be used to predict bimolecular structures and can predict the equilibrium binding affinity of an oligonucleotide to a structured RNA target. This is useful for siRNA design. It can also predict secondary structures common to two, unaligned sequences, which is much more accurate than single sequence secondary structure prediction. Finally, RNAstructure can take a number of different types of experiment mapping data to constrain or restrain structure prediction. These include chemical mapping, enzymatic mapping, NMR, and SHAPE data.	10	no	no
rnftools	genomics	RNF framework for NGS: simulation of reads, evaluation of mappers, conversion of RNF-compliant data.	1	no	no
rpsbproc	single_cell	Auto-indexed MCP server for rpsbproc.	1	no	no
rsa	single_cell	Pure-Python RSA implementation.	6	no	no
rscape	transcriptomics	MCP wrapper for rscape.	1	no	no
rsem	transcriptomics	MCP wrapper for rsem.	3	no	no
rseqc	single_cell	QC package for RNA-seq data.	18	no	no
rtg-tools	general	Auto-indexed MCP server for rtg-tools.	1	no	no
rust-bio-tools	transcriptomics	A growing collection of fast and secure command line utilities for dealing with NGS data.	10	no	no
sage-proteomics	proteomics	Proteomics searching so fast it feels like magic.	1	no	no
salmon	transcriptomics	Auto-indexed MCP server for salmon.	1	no	yes
samap	single_cell	The SAMap algorithm.	3	no	no
sambamba	single_cell	MCP wrapper for sambamba.	11	no	no
samblaster	genomics	MCP wrapper for samblaster.	1	no	no
samsift	single_cell	Advanced filtering and tagging of SAM/BAM alignments using Python expressions.	1	no	no
samtools	single_cell	MCP wrapper for samtools.	29	yes	yes
sc-musketeers	single_cell	A tri-partite modular autoencoder for addressing imbalanced cell type annotation and batch effect reduction.	1	no	no
scaden	single_cell	Cell type deconvolution using single cell data.	6	no	no
scanpy	single_cell	MCP wrapper for scanpy.	1	no	no
scanpy-cli	single_cell	CLI for Scanpy.	13	no	no
scanpy-scripts	single_cell	Scripts for using scanpy from the command line.	16	no	no
scar	single_cell	MCP wrapper for scar.	1	no	no
scarches	single_cell	MCP wrapper for scarches.	6	no	no
sccaf	single_cell	MCP wrapper for sccaf.	1	no	no
sccellfie	pathway_enrichment	A tool for inferring metabolic activities from single-cell and spatial transcriptomics.	4	no	no
scelvis	transcriptomics	MCP wrapper for scelvis.	9	no	no
scepia	single_cell	Single Cell Epigenome-based Inference of Activity.	2	no	no
scglue	single_cell	Graph-linked unified embedding for unpaired single-cell multi-omics data integration; GLUE is a flexible framework that utilizes prior knowledge about feature.	11	no	no
scib	single_cell	Evaluating single-cell data integration methods.	1	no	no
scirpy	single_cell	A Scanpy extension for analyzing single-cell T-cell and B-cell receptor (TCR/BCR) sequencing data.	5	no	no
scmeta	single_cell	MCP wrapper for scmeta.	8	no	no
scmidas	single_cell	A torch-based integration method for single-cell multi-omic data.	3	no	no
scpred-cli	single_cell	MCP wrapper for scpred cli.	2	no	no
scrnasim-toolz	single_cell	Tools used by scRNAsim workflow.	7	no	no
scspectra	single_cell	Supervised discovery of interpretable gene programs from single-cell data.	6	no	no
scstem	single_cell	A method for mapping single-cell and spatial transcriptomics data with transfer learning.	1	no	no
sctriangulate	pathway_enrichment	A Python package to mix-and-match conflicting clustering results in single cell analysis, and generate reconciled clustering solutions.	1	no	no
scvelo	single_cell	MCP wrapper for scvelo.	1	no	no
scvi	single_cell	Single-cell Variational Inference.	7	no	no
scvi-tools	single_cell	Deep probabilistic analysis of single-cell omics data.	1	no	no
scvis	single_cell	scvis is a python package for dimension reduction of high-dimensional biological data, especially single-cell RNA-sequencing (scRNA-seq) data.	2	no	no
scvis_galaxy	single_cell	scvis is a python package for dimension reduction of high-dimensional biological data, especially single-cell RNA-sequencing (scRNA-seq) data.	3	no	no
scxmatch	single_cell	Python implementation for single-cell cross match test, an efficient implementation of Rosenbaum's test.	1	no	no
sdeper	single_cell	Spatial Deconvolution method with Platform Effect Removal; SDePER (Spatial Deconvolution method with Platform Effect Removal) is a hybrid machine learning and regression method to deconvolve Spatial barcoding-based transcriptomic data using reference single-cell RNA sequencing data, considering platform effects removal, sparsity of cell types per capture spot and across-spots spatial correlation in cell type compositions. SDePER is also able to impute cell type compositions and gene expression at unmeasured locations in a tissue map with enhanced resolution.	2	no	no
seacells	single_cell	SEACells algorithm for Inference of transcriptional and epigenomic cellular states from single-cell genomics data.	5	no	no
searchgui	single_cell	MCP wrapper for searchgui.	4	no	no
segemehl	single_cell	Short read mapping with gaps.	2	no	no
sentieon	single_cell	Accelerated performance bioinformatics tools for mapping and variant calling.	1	no	no
sepp	single_cell	SATe-enabled phylogenetic placement.	3	no	no
seq2science	genomics	Automated preprocessing of Next-Generation-Sequencing data.	3	no	no
seqcluster	single_cell	small RNA analysis from NGS data.	1	no	no
seqfu	transcriptomics	MCP wrapper for seqfu.	19	no	no
seqkit	single_cell	MCP wrapper for seqkit.	27	no	no
seqtk	single_cell	MCP wrapper for seqtk.	15	no	no
sequence-operations	single_cell	MCP wrapper for sequence operations.	7	no	no
seurat-scripts	single_cell	MCP wrapper for seurat scripts.	11	no	no
sevenbridges-python	single_cell	SBG API python client bindings; sevenbridges-python is a Python library that provides an interface for the Seven Bridges Platform the Cancer Genomics Cloud and Cavatica public APIs. It works with Python versions 2.6+ and supports Python 3.	4	no	no
shiba	transcriptomics	A versatile method for systematic identification of differential RNA splicing across platforms; A versatile computational method for systematic identification of differential RNA splicing.	2	no	no
simo-omics	single_cell	Spatial integration of multi-omics single-cell datasets through probabilistic alignment.	1	no	no
simplejson	single_cell	Simple, fast, extensible JSON encoder/decoder for Python.	2	no	no
sina	single_cell	MCP wrapper for sina.	3	no	no
sincei	single_cell	A user-friendly toolkit for QC, counting, clustering and plotting of single-cell (epi)genomics data.	6	no	no
slow5tools	single_cell	MCP wrapper for slow5tools.	11	no	no
snakemake	single_cell	A popular workflow management system aiming at full in-silico reproducibility; Snakemake is a workflow management system that aims to reduce the complexity of creating.	6	no	no
snakemake-interface-common	general	Common functions and classes for Snakemake and its plugins.	1	no	no
snakemake-interface-executor-plugins	single_cell	This package provides a stable interface for interactions between Snakemake and its executor plugins.	1	no	no
snakemake-interface-logger-plugins	general	This package provides a stable interface for interactions between Snakemake and its logger plugins.	1	no	no
snakemake-interface-report-plugins	single_cell	This package provides a stable interface for interactions between Snakemake and its report plugins.	5	no	no
snakemake-interface-storage-plugins	single_cell	This package provides a stable interface for interactions between Snakemake and its storage plugins.	5	no	no
snakemake-minimal	single_cell	A popular workflow management system aiming at full in-silico reproducibility; Snakemake is a workflow management system that aims to reduce the complexity.	8	no	no
snakemake-wrapper-utils	genomics	A collection of utility functions and classes for Snakemake wrappers.	5	no	no
snakesv	genomics	snakeSV: Flexible framework for large-scale SV discovery.	4	no	no
snap-aligner	genomics	Auto-indexed MCP server for snap-aligner.	1	no	no
snippy	genomics	MCP wrapper for snippy.	5	no	no
snp2cell	single_cell	MCP wrapper for snp2cell.	8	no	no
snpeff	genomics	MCP wrapper for snpeff.	6	yes	no
snpsift	transcriptomics	MCP wrapper for snpsift.	1	no	no
sopa	single_cell	Spatial-omics pipeline and analysis.	8	no	no
sorted_nearest	general	Find nearest interval.	1	no	no
sortmerna	transcriptomics	MCP wrapper for sortmerna.	3	no	no
sourmash	single_cell	Quickly search, compare, and analyze genomic and metagenomic data sets.	8	no	no
spades	single_cell	SPAdes (St. Petersburg genome assembler) is intended for both standard isolates and single-cell MDA bacteria assemblies; SPAdes (St. Petersburg genome assembler) is a genome assembly algorithm which was designed for.	10	no	no
spagrn	single_cell	A comprehensive tool to infer TF-centered, spatial gene regulatory networks for the spatially resolved transcriptomics (SRT) data.	1	no	no
spapros	single_cell	Probe set selection for targeted spatial transcriptomics.	5	no	no
spatialleiden	single_cell	Implementation of multiplex Leiden for analysis of spatial omics data.	1	no	no
sra-tools	transcriptomics	MCP wrapper for sra tools.	6	no	no
stacks	single_cell	MCP wrapper for stacks.	15	no	no
star	transcriptomics	An RNA-seq read aligner.	4	no	yes
star-fusion	transcriptomics	MCP wrapper for star fusion.	4	no	no
stream	single_cell	STREAM-Single-cell Trajectories Reconstruction, Exploration And Mapping.	8	no	no
stringtie	genomics	MCP wrapper for stringtie.	2	no	no
subread	transcriptomics	High-performance read alignment, quantification, and mutation discovery.	8	no	yes
switchtfi	single_cell	Implementation of the SwitchTFI method as presented in: https:.	1	no	no
t-coffee	transcriptomics	MCP wrapper for t coffee.	5	no	no
t_coffee	single_cell	A collection of tools for Computing, Evaluating and Manipulating Multiple Alignments of DNA, RNA, Protein Sequences and Structures.	5	no	no
tabix	genomics	MCP wrapper for tabix.	1	yes	no
tabixpp	genomics	A C++ wrapper around the tabix project, a generic indexer for TAB-delimited genome position files.	1	yes	no
talon	genomics	TALON is a Python package for identifying and quantifying known and novel.	8	no	no
taxonkit	single_cell	MCP wrapper for taxonkit.	12	no	no
tb-profiler	genomics	Profiling tool for Mycobacterium tuberculosis to detect drug resistance and lineage from sequencing data.	5	no	no
thapbi-pict	general	THAPBI Phytophthora ITS1 Classifier Tool (PICT); THAPBI Phytophthora ITS1 Classifier Tool (PICT) an ITS1-based.	1	no	no
tidyp	single_cell	MCP wrapper for tidyp.	2	no	no
tirank	pathway_enrichment	A comprehensive analysis tool for transferring phenotype of bulk transcriptomic data to single-cell or spatial transcriptomic data; TiRank integrates deep learning and statistical analysis to infer phenotype.	2	no	no
tmalign	single_cell	TM-align sequence-order independent protein structure alignment.	5	no	no
tobias	single_cell	Transcription factor Occupancy prediction By Investigation of ATAC-seq Signal; TOBIAS (Transcription factor Occupancy prediction By Investigation of ATAC-seq Signal) is a collection.	1	no	no
toil	single_cell	A scalable, efficient, cross-platform and easy-to-use workflow engine in pure Python.	1	no	no
transdecoder	single_cell	Auto-indexed MCP server for transdecoder.	1	no	no
treetime	single_cell	Maximum-Likelihood dating and ancestral inference for phylogenetic trees.	5	no	no
trf	single_cell	Auto-indexed MCP server for trf.	1	no	no
trim-galore	single_cell	Trim Galore! is a wrapper script to automate quality and adapter trimming as well as quality control.	3	no	no
trimadap	single_cell	Fast but inaccurate adapter trimmer for Illumina reads.	1	no	no
trimal	general	Auto-indexed MCP server for trimal.	1	no	no
trimmomatic	single_cell	MCP wrapper for trimmomatic.	2	no	no
trinity	transcriptomics	MCP wrapper for trinity.	4	no	no
trnascan-se	single_cell	tRNA detection in large-scale genomic sequences.	4	no	no
ucsc-bedgraphtobigwig	single_cell	Convert a bedGraph file to bigWig format.	1	no	no
ucsc-bedtobigbed	single_cell	Convert bed file to bigBed. (BigBed version: 4).	1	no	no
ucsc-cell-browser	single_cell	A browser for single-cell data, main site at http://cells.ucsc.edu. UCSC Cellbrowser, an interactive browser for single cell data. Includes importers and basic pipelines for text files, Seurat, Scanpy and Cellranger. All Javascript - does not require a server backend.	10	no	no
ucsc-fatotwobit	single_cell	Convert DNA from fasta to 2bit format.	1	yes	no
ucsc-gtftogenepred	single_cell	Convert a GTF file to a genePred.	1	no	no
ucsc-liftover	single_cell	Move annotations from one assembly to another.	2	yes	no
ucsc-nibfrag	single_cell	Extract part of a nib file as .fa (all bases/gaps lower case by default).	1	no	no
ucsc-twobitinfo	single_cell	Get information about sequences in a .2bit file.	1	no	no
ucsc-twobittofa	single_cell	Convert all or part of .2bit file to fasta.	1	yes	no
ucsc-wigtobigwig	single_cell	Convert ascii format wig file (in fixedStep, variableStep).	1	no	no
umi_tools	single_cell	Tools for dealing with Unique Molecular Identifiers (UMIs) / Random Molecular Tags (RMTs).	1	no	no
umis	transcriptomics	Tools for processing UMI RNA-tag data.	5	no	no
unicycler	single_cell	MCP wrapper for unicycler.	3	no	no
unifrac	single_cell	Fast phylogenetic diversity calculations; UniFrac is a commonly phylogenetic diversity distance metric used in.	2	no	no
unifrac-binaries	single_cell	Fast phylogenetic diversity calculations; UniFrac is a commonly phylogenetic diversity distance metric used in.	1	no	no
upimapi	general	UniProt Id Mapping through API; UPIMAPI takes as input either a list of UniProt IDs or a blast file from.	1	no	no
urllib3	single_cell	HTTP library with thread-safe connection pooling, file post, and more.	4	no	no
usher	single_cell	Ultrafast Sample Placement on Existing Trees (UShER).	4	no	no
vardict	transcriptomics	Auto-indexed MCP server for vardict.	1	no	no
vardict-java	genomics	MCP wrapper for vardict java.	5	no	no
varlociraptor	single_cell	Auto-indexed MCP server for varlociraptor.	1	no	no
varscan	single_cell	Auto-indexed MCP server for varscan.	1	no	no
vcflib	transcriptomics	Auto-indexed MCP server for vcflib.	1	no	no
vcfpy	single_cell	Python 3 VCF library with good support for both reading and writing.	6	no	no
vcftools	genomics	MCP wrapper for vcftools.	6	yes	no
vcontact2	single_cell	Viral Contig Automatic Clustering and Taxonomy.	4	no	no
viennarna	single_cell	ViennaRNA package -- RNA secondary structure prediction and comparison.	23	no	no
vitessce-python	single_cell	Jupyter widget facilitating interactive visualization of spatial single-cell data with Vitessce.	1	no	no
vpt	single_cell	Command line tool for highly parallelized processing of Vizgen data.	11	no	no
vsearch	general	Auto-indexed MCP server for vsearch.	1	no	no
vt	single_cell	A tool set for short variant discovery in genetic sequence data.	11	no	no
wasp2	genomics	Allele-specific analysis of next-generation sequencing data with Rust acceleration; WASP2 is a high-performance tool for allele-specific analysis of NGS data.	6	no	no
whatshap	genomics	Phase genomic variants using DNA sequencing reads (haplotype assembly).	8	no	no
womtool	single_cell	MCP wrapper for womtool.	6	no	no
xclone	single_cell	Inference of clonal Copy Number Alterations in single cells.	5	no	no
xopen	general	Open compressed files transparently in Python.	1	no	no
yacrd	single_cell	MCP wrapper for yacrd.	5	no	no
zdb	transcriptomics	MCP wrapper for zdb.	6	no	no
zol	genomics	zol (& fai): large-scale targeted detection and evolutionary investigation of gene clusters.	11	no	no