README.md

---
license: mit
tags:
  - transcription-factor
  - binding
  - chipexo
  - genomics
  - biology
language:
  - en
pretty_name: Rossi ChIP-exo 2021
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_annotated_features
    description: ChIP-exo regulator-target binding features with peak statistics
    dataset_type: annotated_features
    default: true
    metadata_fields:
      - regulator_locus_tag
      - regulator_symbol
      - target_locus_tag
      - target_symbol
    data_files:
      - split: train
        path: yeastepigenome_annotatedfeatures.parquet
    dataset_info:
      features:
        - name: sample_id
          dtype: int32
          description: Unique identifier for each ChIP-exo experimental sample.
        - name: pss_id
          dtype: float64
          description: >-
            Current brentlab promotersetsig table id. This will eventually be
            removed.
        - name: binding_id
          dtype: float64
          description: Current brentlab binding table id. This will eventually be removed.
        - name: yeastepigenome_id
          dtype: float64
          description: Unique identifier in the yeastepigenome database.
        - name: regulator_locus_tag
          dtype: string
          description: Systematic ORF name of the regulator.
          role: regulator_identifier
        - name: regulator_symbol
          dtype: string
          description: Common gene name of the regulator.
          role: regulator_identifier
        - name: target_locus_tag
          dtype: string
          description: >-
            The systematic ID of the feature to which the effect/pvalue is
            assigned. See hf/BrentLab/yeast_genome_resources
          role: target_identifier
        - name: target_symbol
          dtype: string
          description: >-
            The common name of the feature to which the effect/pvalue is
            assigned. If there is no common name, the `target_locus_tag` is
            used.
          role: target_identifier
        - name: n_sig_peaks
          dtype: float64
          description: Number of peaks in the promoter region of the the target gene
          role: quantitative_measure
        - name: max_fc
          dtype: float64
          description: >-
            If there are multiple peaks in the promoter region, then the maximum
            is reported. Otherwise, it is the fold change of the single peak in
            the promoter.
          role: quantitative_measure
        - name: min_pval
          dtype: float64
          description: 'The most significant p-value among peaks for this interaction. '
          role: quantitative_measure
  - config_name: reprocess_annotatedfeatures
    description: >-
      Annotated features reprocessed with updated peak
      calling methodology
    dataset_type: annotated_features
    data_files:
      - split: train
        path: creprocess_annotatedfeatures.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: target_locus_tag
          dtype: string
          description: Systematic gene name (ORF identifier) of the target gene
        - name: target_symbol
          dtype: string
          description: Standard gene symbol of the target gene
        - name: baseMean
          dtype: float64
          description: Average of normalized count values, dividing by size factors, taken over all samples
        - name: log2FoldChange
          dtype: float64
          description: Log2 fold change between comparison and control groups
        - name: lfcSE
          dtype: float64
          description: Standard error estimate for the log2 fold change estimate
        - name: stat
          dtype: float64
          description: Value of the test statistic for the gene
        - name: pvalue
          dtype: float64
          description: P-value of the test for the gene
        - name: padj
          dtype: float64
          description: Adjusted p-value for multiple testing for the gene
---

# Rossi 2021

This data is gathered from [yeastepigenome.org](https://yeastepigenome.org/). This work was published in

[Rossi MJ, Kuntala PK, Lai WKM, Yamada N, Badjatia N, Mittal C, Kuzu G, Bocklund K, Farrell NP, Blanda TR, Mairose JD, Basting AV, Mistretta KS, Rocco DJ, Perkinson ES, Kellogg GD, Mahony S, Pugh BF. A high-resolution protein architecture of the budding yeast genome. Nature. 2021 Apr;592(7853):309-314. doi: 10.1038/s41586-021-03314-8. Epub 2021 Mar 10. PMID: 33692541; PMCID: PMC8035251.](https://doi.org/10.1038/s41586-021-03314-8)

## Dataset details

`genome_map` is fully reprocessed data from the sequence files. I used the nf-core/chipseq pipeline, details for which can be found in `scripts/`. With
those bams, I filtered the reads using `samtools` and the same settings specified in Rossi et al 2021, and then counted 5' ends using bedtools. See
`scripts/count_tags.sh`.

## Data Structure

### Metadata

| Field                 | Description                                                       |
|-----------------------|-------------------------------------------------------------------|
| `regulator_locus_tag` | Systematic gene name (ORF identifier) of the transcription factor |
| `regulator_symbol`    | Standard gene symbol of the transcription factor                  |
| `run_accession`       | GEO run accession identifier for the sample                       |
| `yeastepigenome_id`   | Sample identifier used by yeastepigenome.org                      |

### Genome Map

| Field    | Description                                                    |
|----------|----------------------------------------------------------------|
| `chr`    | Chromosome name, ucsc (e.g., chrI, chrII, etc.)                |
| `pos`    | Genomic position of the 5' tag                                 |
| `pileup` | Depth of coverage (number of 5' tags) at this genomic position |

## Usage

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.

```python
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:

```python
# 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)
```