--- license: mit language: - en tags: - transcription-factor - binding - chec-seq - genomics - biology pretty_name: Barkai ChEC-seq Compendium size_categories: - 100M_metadata.parquet` files store metadata. You may use the field `accession` to extract the corresponding data. See `scripts/` for more parsing details. ## Data Structure ### genome_map/ This is a parquet dataset which is partitioned by Series and Accession | Field | Description | |------------|----------------------------------------------------------------| | `seqnames` | Chromosome or sequence name (e.g., chrI, chrII, etc.) | | `start` | Start position of the genomic interval (1-based coordinates) | | `end` | End position of the genomic interval (1-based coordinates) | | `pileup` | Number of reads or signal intensity at this genomic position | ### [GSE178430](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE179430) Metadata | Field | Description | |------------------------------|--------------------------------------------------------------------------------| | `accession` | Sample accession identifier | | `regulator_locus_tag` | Systematic gene name (ORF identifier) of the tagged transcription factor | | `regulator_symbol` | Standard gene symbol of the tagged transcription factor | | `strainid` | Strain identifier used in the experiment | | `instrument` | Sequencing instrument used for data generation | | `genotype` | Full genotype description of the experimental strain | | `dbd_donor_symbol` | Gene symbol of the DNA-binding domain donor (for chimeric constructs) | | `ortholog_donor` | Ortholog donor information for cross-species constructs | | `paralog_deletion_symbol` | Gene symbol of deleted paralog in the strain background | | `paralog_resistance_cassette`| Antibiotic resistance cassette used for paralog deletion | ### [GSE209631](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE209631) Metadata | Field | Description | |-----------------------|--------------------------------------------------------------------------------| | `accession` | Sample accession identifier | | `regulator_locus_tag` | Systematic gene name (ORF identifier) of the tagged transcription factor | | `regulator_symbol` | Standard gene symbol of the tagged transcription factor | | `variant_type` | Type of transcription factor variant tested in the experiment | ### [GSE222268](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE222268) Metadata | Field | Description | |-----------------------|--------------------------------------------------------------------------------| | `title` | Experiment title or sample description | | `accession` | GEO sample accession identifier | | `extract_protocol_ch1`| Protocol used for sample extraction and preparation | | `description` | Detailed description of the experimental sample or condition | | `instrument_model` | Model of sequencing instrument used for data generation | ## Usage The entire repository is large. It may be preferrable to only retrieve specific files or partitions. You can use the metadata files to choose which files to pull. ```python from huggingface_hub import snapshot_download import duckdb import os # Download only the partitioned dataset directory repo_path = snapshot_download( repo_id="BrentLab/barkai_compendium", repo_type="dataset", allow_patterns="_metadata.parquet" ) dataset_path = os.path.join(repo_path, "GSE178430_metadata.parquet") con = duckdb.connect() meta_res = conn.execute("SELECT * FROM read_parquet(?) LIMIT 10", [dataset_path]).df() print(meta_res) ``` We might choose to take a look at the file with accession `GSM5417602` ```python # Download only the partitioned dataset directory repo_path = snapshot_download( repo_id="BrentLab/barkai_compendium", repo_type="dataset", allow_patterns="genome_map/series=GSE179430/accession=GSM5417602/*parquet" # Only the parquet data ) # The rest works the same dataset_path = os.path.join(repo_path, "genome_map") result = conn.execute("SELECT * FROM read_parquet(?) LIMIT 10", [f"{dataset_path}/**/*.parquet"]).df() print(result) ``` **Dataset Author and Contact**: Chase Mateusiak [@cmatKhan](https://github.com/cmatkhan/)