Virtual Cell Perturbation Transcriptomics Dataset ELEM-1200RS

Dataset Summary

The ELEM Biotech Virtual Cell Perturbation Transcriptomics Dataset "ELEM-1200RS" [V1.0], comprises approximately 1,200 bulk RNA-seq samples derived from 63 wild-type cell lines, with knockdown experiments targeting 914 unique genes. Gene expression data are provided as TPM-normalized expression matrices in .h5ad format, making the dataset directly suitable for downstream bioinformatics analyses and machine learning workflows (e.g., cell perturbation prediction and gene regulatory network inference), while maintaining the data structure adopted by the Virtual Cell Challenge.

• Note on Priority Access:

Teams wishing to apply for priority data access and usage should email yongbo_cheng@elem-bio.cn to obtain the "AIVC Data Priority Access and Usage Agreement" and complete the signing of the agreement between September 24, 2026, and September 30, 2026.

Data Structure

• Note on Annotation Metadata:

The publicly released dataset does not include the mapping between sample IDs and the corresponding target-gene names or cell line names. To obtain the complete annotation metadata, please submit your request to ELEM via email: yongbo_cheng@elem-bio.cn. The corresponding annotation information will be provided upon confirmation.

File1: 'ELEM_1200RS_P1.h5ad'

adata.X TPM-normalized expression matrix (Samples × Genes) 'adata.X' contains the TPM-normalized gene expression matrix corresponding to the same type of RNA-seq samples. The TPM values are derived from the raw RNA-seq expression measurements using transcript/gene abundance normalization.

adata.obs 'sample_id': Unique identifier for each RNA-seq sample.

adata.var 'gene_symbol': HGNC gene symbol (e.g., 'SCYL3'). 'gene_id': Ensembl Gene Identifier (e.g., 'ENSG00000000457.15'). 'gene_type': Gene feature type (e.g., 'protein_coding', 'lncRNA').

File2: batch0908_0911.result.tar.gz

The dataset is organized hierarchically into sample directories following the pattern //. Each directory contains expression quantification tables and quality control (QC) metrics:

1. Main Expression Results .gene.TPM.xls Gene-level TPM expression table for this sample. Columns: Gene (Ensembl ID), Symbol (Gene Symbol), Chr (Chromosome), GeneType (Biotype), TPM. .gene.reads.xls Gene-level raw read count table for this sample. Columns: Gene, Symbol, Chr, Start-End, Strand, GeneLength, ExonLength, Depth, Coverage, Reads. _expression_profile.txt Raw gene expression profile. 17 columns, including TPM, SenseReads, AntisenseReads, IntronReads, Depth, Coverage, and other metrics.

2. Quality Control (QC) Reports QC.clean.tsv: Read cleaning QC. QC.mapping.tsv: Alignment QC. QC.expr.tsv: Expression QC. _randCheck_gene.{txt,pdf,png}: Uniformity of gene 5'→3' read distribution. _randCheck_mRNA.{txt,pdf,png}: Uniformity of mRNA 5'→3' read distribution. _randCheck_region.{txt,pdf,png}: Uniformity of read distribution across 5'UTR/CDS/3'UTR. _fastp.html: Interactive fastp QC report (read cleaning). _hisat2_stat.txt: HISAT2 alignment summary.

Data Processing Pipeline

1. Experimental Setup: Human cells were subjected to targeted perturbations alongside non-targeting controls.
2. Sequencing: RNA was extracted and sequenced on GeneMind platforms (150 bp paired-end).
3. Bioinformatics & Quantification: Reads were aligned to the human reference genome (GRCh38 v49) using 'HISAT2'. Matrices were assembled into an 'AnnData' object with standardized 'obs' and 'var' annotations.

Quick Start & Usage

You can load the '.h5ad' file directly using 'anndata' or 'scanpy' in Python.

License and Data Use Terms

Allowed Scope of Use

Permission is granted to use this dataset for the training, fine-tuning, and academic research of AI models.

Attribution Requirement

Users who publish research, academic papers, or commercial products based on this dataset must explicitly acknowledge the dataset's name and source link in a prominent location.

Derivative Works Limitation

Any derivative datasets generated based on this dataset must be released and open-sourced under the same license agreement.

Contact

For questions regarding the dataset, please open an issue in this Hugging Face repository or contact us by email at yongbo_cheng@elem-bio.cn.

Disclaimer

This dataset is provided for research purposes. The dataset authors make no guarantees regarding the completeness, accuracy, or suitability of the data for any particular application.

Users are responsible for verifying the provenance, preprocessing status, and licensing conditions of the data before using it in downstream research.