metadata
license: mit
language:
- en
tags:
- transcription-factor
- binding
- chec-seq
- genomics
- biology
pretty_name: Barkai ChEC-seq Compendium
size_categories:
- 100M<n<1B
experimental_conditions:
temperature_celsius: 30
cultivation_method: liquid_culture
growth_phase_at_harvest:
od600: 4
stage: overnight_stationary_phase
media:
name: synthetic_complete_dextrose
carbon_source:
- compound: D-dextrose
concentration_percent: unspecified
nitrogen_source: unspecified
citation: https://www.weizmann.ac.il/molgen/barkai/
configs:
- config_name: genomic_coverage
description: Genomic coverage data with pileup counts at specific positions
dataset_type: genome_map
default: true
data_files:
- split: train
path: genome_map/*/*/part-0.parquet
partitioning:
enabled: true
partition_by:
- series
- accession
path_template: genome_map/series={series}/accession={accession}/*.parquet
dataset_info:
features:
- name: seqnames
dtype: string
description: Chromosome or sequence name (e.g., chrI, chrII, etc.)
- name: start
dtype: int32
description: Start position of the genomic interval (1-based coordinates)
- name: end
dtype: int32
description: End position of the genomic interval (1-based coordinates)
- name: pileup
dtype: int32
description: Number of tags (5' of read) at this genomic position
partition_info:
- name: Series
dtype: string
description: GEO series of the dataset
- name: Accession
dtype: string
description: GEO accession of the specific sample
- config_name: GSE178430_metadata
description: Metadata for GSE178430
dataset_type: metadata
data_files:
- split: train
path: GSE178430_metadata.parquet
dataset_info:
features:
- name: sample_id
dtype: integer
description: Unique sample identifier. Uniquely identifies an accession
- name: series
dtype: string
description: the GEO series to which this collection belongs
- name: accession
dtype: string
description: Sample accession identifier
- name: regulator_locus_tag
dtype: string
description: >-
Systematic gene name (ORF identifier) of the tagged transcription
factor
- name: regulator_symbol
dtype: string
description: Standard gene symbol of the tagged transcription factor
- name: strainid
dtype: string
description: Strain identifier used in the experiment
- name: instrument
dtype: string
description: Sequencing instrument used for data generation
- name: genotype
dtype: string
description: Full genotype description of the experimental strain
- name: dbd_donor_symbol
dtype: string
description: >-
Gene symbol of the DNA-binding domain donor (for chimeric
constructs)
- name: ortholog_donor
dtype: string
description: Ortholog donor information for cross-species constructs
- name: paralog_deletion_symbol
dtype: string
description: Gene symbol of deleted paralog in the strain background
- name: paralog_resistance_cassette
dtype: string
description: Antibiotic resistance cassette used for paralog deletion
- config_name: GSE209631_metadata
description: ChEC-seq experiment metadata for transcription factor variant studies
dataset_type: metadata
data_files:
- split: train
path: GSE209631_metadata.parquet
dataset_info:
features:
- name: sample_id
dtype: integer
description: Unique sample identifier. Uniquely identifies an accession
- name: series
dtype: string
description: the GEO series to which this collection belongs
- name: accession
dtype: string
description: Sample accession identifier
- name: regulator_locus_tag
dtype: string
description: >-
Systematic gene name (ORF identifier) of the tagged transcription
factor
role: regulator_identifier
- name: regulator_symbol
dtype: string
description: Standard gene symbol of the tagged transcription factor
role: regulator_identifier
- name: variant_type
dtype: string
description: Type of transcription factor variant tested in the experiment
- config_name: GSE222268_metadata
description: General experiment metadata for genomic studies
dataset_type: metadata
data_files:
- split: train
path: GSE222268_metadata.parquet
dataset_info:
features:
- name: sample_id
dtype: string
description: Unique identifier for the experimental sample
- name: series
dtype: string
description: Series or batch identifier grouping related samples
- name: accession
dtype: string
description: Accession number from public database (e.g., SRA, GEO)
- name: regulator_locus_tag
dtype: string
description: Systematic gene identifier for the transcription factor regulator
role: regulator_identifier
- name: regulator_symbol
dtype: string
description: Standard gene symbol for the transcription factor regulator
role: regulator_identifier
- name: experiment_details
dtype: string
description: >-
Detailed description of experimental methods, parameters, or
conditions
role: experimental_condition
- name: description
dtype:
class_label:
names:
- MNase
- ChEC-seq
description: Experiment type, either MNase or ChEC-seq
Barkai Compendium
This collects the ChEC-seq data from the following GEO series:
The metadata for each is parsed out from the SraRunTable, or in the case of GSE222268, the NCBI series matrix file (the genotype isn't in the SraRunTable)
The Barkai lab refers to this set as their binding compendium.
The genotypes for GSE222268 are not clear enough to me currently to parse well.
Accessing Data
The examples below require the
HuggingFace Hub client
(pip install huggingface_hub).
Direct parquet access
The repository is large and contains both single parquet files (metadata) and partitioned datasets (genome_map coverage data). Download the metadata files first to identify which partitions are relevant before fetching coverage data.
Single parquet file example (metadata):
from huggingface_hub import snapshot_download
import duckdb
repo_path = snapshot_download(
repo_id="BrentLab/barkai_compendium",
repo_type="dataset",
allow_patterns="*metadata.parquet",
)
conn = duckdb.connect()
# returns a pandas DataFrame with the first 5 rows
conn.execute(
"SELECT * FROM read_parquet(?) LIMIT 5",
[f"{repo_path}/GSE178430_metadata.parquet"],
).df()
Partitioned dataset example (genome_map coverage):
repo_path = snapshot_download(
repo_id="BrentLab/barkai_compendium",
repo_type="dataset",
allow_patterns="genome_map/series=GSE179430/accession=GSM5417602/*.parquet",
)
conn.execute(
"SELECT * FROM read_parquet(?) LIMIT 5",
[f"{repo_path}/genome_map/**/*.parquet"],
).df()
Accessing using R
Clone the repository and read parquet files directly with arrow:
# install.packages("arrow")
arrow::read_parquet("GSE178430_metadata.parquet")