metadata
license: mit
tags:
- transcription-factor
- binding
- chipexo
- genomics
- biology
language:
- en
pretty_name: Rossi ChIP-exo 2021
experimental_conditions:
temperature_celsius: 25
cultivation_method: unspecified
growth_phase_at_harvest:
phase: mid_log
od600: 0.8
media:
name: yeast_peptone_dextrose
carbon_source:
- compound: D-glucose
concentration_percent: unspecified
nitrogen_source:
- compound: yeast_extract
concentration_percent: unspecified
- compound: peptone
concentration_percent: unspecified
heat_shock:
induced: true
temperature_celsius: 37
duration_minutes: 6
pre_induction_temperature_celsius: 25
method: equal_volume_medium_transfer
configs:
- config_name: metadata
description: Metadata describing the tagged regulator in each experiment
dataset_type: metadata
data_files:
- split: train
path: rossi_2021_metadata.parquet
dataset_info:
features:
- name: regulator_locus_tag
dtype: string
description: Systematic gene name (ORF identifier) of the transcription factor
- name: regulator_symbol
dtype: string
description: Standard gene symbol of the transcription factor
- name: run_accession
dtype: string
description: GEO run accession identifier for the sample
- name: yeastepigenome_id
dtype: string
description: Sample identifier used by yeastepigenome.org
- config_name: genome_map
description: ChIP-exo 5' tag coverage data partitioned by sample accession
dataset_type: genome_map
data_files:
- split: train
path: genome_map/*/*.parquet
dataset_info:
features:
- name: chr
dtype: string
description: Chromosome name (e.g., chrI, chrII, etc.)
- name: pos
dtype: int32
description: Genomic position of the 5' tag
- name: pileup
dtype: int32
description: Depth of coverage (number of 5' tags) at this genomic position
- config_name: rossi_2021_metadata
description: >-
Replicate-level metadata for ChIP-exo experiments including experimental
conditions and sample information
dataset_type: metadata
applies_to:
- rossi_2021_af_replicates
data_files:
- split: train
path: rossi_2021_metadata.parquet
dataset_info:
features:
- name: regulator_locus_tag
dtype: string
description: Systematic gene identifier for the transcription factor
role: regulator_identifier
- name: regulator_symbol
dtype: string
description: Standard gene symbol for the transcription factor
role: regulator_identifier
- name: run_accession
dtype: string
description: SRA run accession identifier for this biological replicate
- name: yeastepigenome_id
dtype: string
description: Identifier from the Yeast Epigenome Project
- name: treatment
dtype: string
description: Experimental treatment condition
role: experimental_condition
- name: growth_media
dtype: string
description: Growth media composition
role: experimental_condition
- name: antibody
dtype: string
description: Antibody used for ChIP-exo immunoprecipitation
- name: sample_id
dtype: string
description: Unique identifier for the biological replicate
- config_name: rossi_2021_metadata_sample
description: >-
Sample-level metadata for combined ChIP-exo experiments including
experimental conditions
dataset_type: metadata
applies_to:
- rossi_2021_af_combined
data_files:
- split: train
path: rossi_2021_metadata_sample.parquet
dataset_info:
features:
- name: regulator_locus_tag
dtype: string
description: Systematic gene identifier for the transcription factor
role: regulator_identifier
- name: regulator_symbol
dtype: string
description: Standard gene symbol for the transcription factor
role: regulator_identifier
- name: treatment
dtype: string
description: Experimental treatment condition
role: experimental_condition
- name: growth_media
dtype: string
description: Growth media composition
role: experimental_condition
- name: antibody
dtype: string
description: Antibody used for ChIP-exo immunoprecipitation
- name: sample_id
dtype: string
description: Unique identifier combining regulator and replicates
- config_name: rossi_2021_af_replicates
description: >-
ChIP-exo annotated features at biological replicate level with binding
peaks and statistical significance metrics
dataset_type: annotated_features
data_files:
- split: train
path: rossi_2021_af_replicates.parquet
dataset_info:
features:
- name: sample_id
dtype: string
description: Unique identifier for the biological replicate
role: sample_id
- name: run_accession
dtype: string
description: SRA run accession identifier for this biological replicate
- name: regulator_locus_tag
dtype: string
description: Systematic gene identifier for the transcription factor
role: regulator_identifier
- name: regulator_symbol
dtype: string
description: Standard gene symbol for the transcription factor
role: regulator_identifier
- name: target_locus_tag
dtype: string
description: Systematic gene identifier for the target gene
role: target_identifier
- name: target_symbol
dtype: string
description: Standard gene symbol for the target gene
role: target_identifier
- name: seqnames
dtype: string
description: Chromosome identifier (e.g., chrI, chrII, chrXVI)
- name: start
dtype: int64
description: Promoter region start position (1-based coordinate)
- name: end
dtype: int64
description: Promoter region end position (1-based, inclusive)
- name: background_counts
dtype: int64
description: Read counts in the background/control sample for this peak region
role: quantitative_measure
- name: experiment_counts
dtype: int64
description: Read counts in the ChIP-exo experiment sample for this peak region
role: quantitative_measure
- name: total_background_counts
dtype: int64
description: Total read counts across the entire genome in the background sample
role: quantitative_measure
- name: total_experiment_counts
dtype: int64
description: Total read counts across the entire genome in the experiment sample
role: quantitative_measure
- name: enrichment
dtype: float64
description: Enrichment score for the binding peak
role: quantitative_measure
- name: poisson_pval
dtype: float64
description: P-value from Poisson distribution test for peak significance
role: quantitative_measure
- name: log_poisson_pval
dtype: float64
description: Log-transformed Poisson p-value
role: quantitative_measure
- name: hypergeometric_pval
dtype: float64
description: P-value from hypergeometric distribution test for peak significance
role: quantitative_measure
- name: log_hypergeometric_pval
dtype: float64
description: Log-transformed hypergeometric p-value
role: quantitative_measure
- name: poisson_qval
dtype: float64
description: FDR-adjusted q-value from Poisson test (multiple testing correction)
role: quantitative_measure
- name: hypergeometric_qval
dtype: float64
description: >-
FDR-adjusted q-value from hypergeometric test (multiple testing
correction)
role: quantitative_measure
- config_name: rossi_2021_af_combined
description: >-
Combined ChIP-exo annotated features with binding peaks and statistical
significance metrics aggregated across biological replicates
dataset_type: annotated_features
data_files:
- split: train
path: rossi_2021_af_combined.parquet
dataset_info:
features:
- name: sample_id
dtype: string
description: Unique identifier combining regulator and replicates
role: sample_id
- name: regulator_locus_tag
dtype: string
description: Systematic gene identifier for the transcription factor
role: regulator_identifier
- name: regulator_symbol
dtype: string
description: Standard gene symbol for the transcription factor
role: regulator_identifier
- name: target_locus_tag
dtype: string
description: Systematic gene identifier for the target gene
role: target_identifier
- name: target_symbol
dtype: string
description: Standard gene symbol for the target gene
role: target_identifier
- name: seqnames
dtype: string
description: Chromosome identifier (e.g., chrI, chrII, chrXVI)
- name: start
dtype: int64
description: Promoter region start position (1-based coordinate)
- name: end
dtype: int64
description: Promoter region end position (1-based, inclusive)
- name: background_counts
dtype: int64
description: >-
Combined read counts in the background/control sample for this peak
region
role: quantitative_measure
- name: experiment_counts
dtype: int64
description: >-
Combined read counts in the ChIP-exo experiment sample for this peak
region
role: quantitative_measure
- name: total_background_counts
dtype: int64
description: >-
Total read counts across the entire genome in the combined
background sample
role: quantitative_measure
- name: total_experiment_counts
dtype: int64
description: >-
Total read counts across the entire genome in the combined
experiment sample
role: quantitative_measure
- name: enrichment
dtype: float64
description: >-
Enrichment score for the binding peak calculated from combined
replicates
role: quantitative_measure
- name: poisson_pval
dtype: float64
description: P-value from Poisson distribution test for peak significance
role: quantitative_measure
- name: log_poisson_pval
dtype: float64
description: Log-transformed Poisson p-value
role: quantitative_measure
- name: hypergeometric_pval
dtype: float64
description: P-value from hypergeometric distribution test for peak significance
role: quantitative_measure
- name: log_hypergeometric_pval
dtype: float64
description: Log-transformed hypergeometric p-value
role: quantitative_measure
- name: poisson_qval
dtype: float64
description: FDR-adjusted q-value from Poisson test (multiple testing correction)
role: quantitative_measure
- name: hypergeometric_qval
dtype: float64
description: >-
FDR-adjusted q-value from hypergeometric test (multiple testing
correction)
role: quantitative_measure
Rossi 2021
This data is gathered from yeastepigenome.org. This work was published in
Usage
The python package tfbpapi provides an interface to this data which eases
examining the datasets, field definitions and other operations. You may also
download the parquet datasets directly from hugging face by clicking on
"Files and Versions", or by using the huggingface_cli and duckdb directly.
In both cases, this provides a method of retrieving dataset and field definitions.
tfbpapi
After installing tfbpapi, you can adapt this tutorial in order to explore the contents of this repository.
huggingface_cli/duckdb
You can retrieves and displays the file paths for each configuration of the "BrentLab/rossi_2021" dataset from Hugging Face Hub.
from huggingface_hub import ModelCard
from pprint import pprint
card = ModelCard.load("BrentLab/rossi_2021", repo_type="dataset")
# cast to dict
card_dict = card.data.to_dict()
# Get partition information
dataset_paths_dict = {d.get("config_name"): d.get("data_files")[0].get("path") for d in card_dict.get("configs")}
pprint(dataset_paths_dict)
The entire repository is large. It may be preferable 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 metadata first
repo_path = snapshot_download(
repo_id="BrentLab/rossi_2021",
repo_type="dataset",
allow_patterns="rossi_2021_metadata.parquet"
)
dataset_path = os.path.join(repo_path, "rossi_2021_metadata.parquet")
conn = 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 SRR11466106:
# Download only a specific sample's genome coverage data
repo_path = snapshot_download(
repo_id="BrentLab/rossi_2021",
repo_type="dataset",
allow_patterns="genome_map/accession=SRR11466106/*.parquet"
)
# Query the specific partition
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)
If you wish to pull the entire repo, due to its size you may need to use an authentication token. If you do not have one, try omitting the token related code below and see if it works. Else, create a token and provide it like so:
repo_id = "BrentLab/rossi_2021"
hf_token = os.getenv("HF_TOKEN")
# Download entire repo to local directory
repo_path = snapshot_download(
repo_id=repo_id,
repo_type="dataset",
token=hf_token
)
print(f"\n✓ Repository downloaded to: {repo_path}")
# Construct path to the rossi_annotated_features parquet file
parquet_path = os.path.join(repo_path, "yeastepigenome_annotatedfeatures.parquet")
print(f"✓ Parquet file at: {parquet_path}")