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seqnames
stringclasses
17 values
start
float64
0
1.53M
end
int32
1
1.53M
pileup
int32
1
490k
chrI
43
44
1
chrI
202
203
1
chrI
254
255
1
chrI
281
282
1
chrI
288
289
1
chrI
322
323
1
chrI
455
456
1
chrI
471
472
1
chrI
479
480
1
chrI
484
485
1
chrI
489
490
1
chrI
505
506
1
chrI
518
519
1
chrI
522
523
1
chrI
559
560
1
chrI
589
590
1
chrI
592
593
1
chrI
701
702
1
chrI
703
704
1
chrI
725
726
1
chrI
828
829
1
chrI
934
935
1
chrI
947
948
1
chrI
949
950
1
chrI
973
974
1
chrI
1,090
1,091
1
chrI
1,103
1,104
1
chrI
1,124
1,125
1
chrI
1,157
1,158
2
chrI
1,253
1,254
1
chrI
1,255
1,256
1
chrI
1,260
1,261
1
chrI
1,261
1,262
1
chrI
1,291
1,292
2
chrI
1,334
1,335
2
chrI
1,380
1,381
1
chrI
1,417
1,418
1
chrI
1,429
1,430
1
chrI
1,442
1,443
1
chrI
1,446
1,447
2
chrI
1,447
1,448
3
chrI
1,448
1,449
2
chrI
1,449
1,450
1
chrI
1,458
1,459
2
chrI
1,501
1,502
4
chrI
1,505
1,506
1
chrI
1,558
1,559
1
chrI
1,563
1,564
1
chrI
1,566
1,567
1
chrI
1,669
1,670
1
chrI
1,671
1,672
1
chrI
1,698
1,699
1
chrI
1,761
1,762
1
chrI
1,793
1,794
1
chrI
1,813
1,814
1
chrI
1,833
1,834
1
chrI
1,848
1,849
1
chrI
1,890
1,891
1
chrI
1,891
1,892
1
chrI
1,902
1,903
1
chrI
1,908
1,909
1
chrI
1,932
1,933
1
chrI
1,956
1,957
1
chrI
1,964
1,965
1
chrI
1,976
1,977
1
chrI
2,050
2,051
1
chrI
2,055
2,056
1
chrI
2,060
2,061
1
chrI
2,117
2,118
1
chrI
2,139
2,140
1
chrI
2,242
2,243
1
chrI
2,277
2,278
1
chrI
2,303
2,304
1
chrI
2,317
2,318
1
chrI
2,318
2,319
1
chrI
2,393
2,394
1
chrI
2,404
2,405
1
chrI
2,427
2,428
1
chrI
2,441
2,442
1
chrI
2,458
2,459
1
chrI
2,462
2,463
1
chrI
2,463
2,464
1
chrI
2,511
2,512
1
chrI
2,555
2,556
1
chrI
2,586
2,587
1
chrI
2,594
2,595
1
chrI
2,603
2,604
1
chrI
2,747
2,748
1
chrI
2,752
2,753
1
chrI
2,897
2,898
1
chrI
2,969
2,970
1
chrI
2,979
2,980
1
chrI
3,043
3,044
1
chrI
3,081
3,082
1
chrI
3,082
3,083
1
chrI
3,089
3,090
1
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3,144
1
chrI
3,149
3,150
1
chrI
3,151
3,152
1
chrI
3,164
3,165
1
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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.

Dataset Details

genome_map stores the pileup of 5' end tags. See the Series and associated cited paper for details, but it is a standard processing pipeline to count 5' ends.

The <series_accession>_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

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

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

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.

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

# 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

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