--- license: mit language: - en tags: - biology - genomics - yeast - transcription-factors - gene-expression - perturbation-screen - overexpression - knockout - microarray - functional-genomics pretty_name: "Hughes 2006 Yeast Transcription Factor Perturbation Dataset" size_categories: - 100K- unique identifier for a specific sample. The sample ID identifies a unique regulator_locus_tag and can be used to join the metadata to the other datasets in this repo - name: regulator_locus_tag dtype: string role: identifier description: Systematic gene name (ORF identifier) of the transcription factor - name: regulator_symbol dtype: string description: Standard gene symbol of the transcription factor - name: found_domain dtype: string description: Identified DNA-binding domain(s) or protein family classification - name: sgd_description dtype: string description: Functional description from Saccharomyces Genome Database (SGD) - name: essential dtype: bool description: Boolean indicating whether the gene is essential for viability - name: oe_passed_qc dtype: bool description: Boolean indicating whether overexpression experiments passed quality control - name: del_passed_qc dtype: bool description: Boolean indicating whether deletion experiments passed quality control - config_name: overexpression description: Overexpression perturbation normalized log2 fold changes dataset_type: annotated_features applies_to: - metadata data_files: - split: train path: overexpression.parquet dataset_info: features: - name: sample_id dtype: integer description: >- unique identifier for a specific sample. The sample ID identifies a unique regulator_locus_tag and can be used to join to the other datasets in this repo, including the metadata - name: regulator_locus_tag dtype: string role: identifier description: Systematic gene name (ORF identifier) of the perturbed transcription factor - name: regulator_symbol dtype: string description: Standard gene symbol of the perturbed transcription factor - name: target_locus_tag dtype: string role: identifier description: Systematic gene name (ORF identifier) of the target gene measured - name: target_symbol dtype: string description: Standard gene symbol of the target gene measured - name: dye_plus dtype: float64 role: quantitative_measure description: >- Normalized log2 fold change for positive (+) dye orientation. Positive values indicate upregulation in response to overexpression. - name: dye_minus dtype: float64 role: quantitative_measure description: >- Normalized log2 fold change for negative (-) dye orientation. Positive values indicate upregulation in response to overexpression. - name: mean_norm_log2fc dtype: float64 role: quantitative_measure description: >- Average log2 fold change across dye orientations, providing a dye-independent estimate of gene expression change upon transcription factor overexpression. - config_name: knockout description: Deletion/knockout perturbation normalized log2 fold changes dataset_type: annotated_features applies_to: - metadata data_files: - split: train path: knockout.parquet dataset_info: features: - name: sample_id dtype: integer description: >- unique identifier for a specific sample. The sample ID identifies a unique regulator_locus_tag and can be used to join to the other datasets in this repo, including the metadata - name: regulator_locus_tag dtype: string role: identifier description: Systematic gene name (ORF identifier) of the perturbed transcription factor - name: regulator_symbol dtype: string description: Standard gene symbol of the perturbed transcription factor - name: target_locus_tag dtype: string role: identifier description: Systematic gene name (ORF identifier) of the target gene measured - name: target_symbol dtype: string description: Standard gene symbol of the target gene measured - name: dye_plus dtype: float64 role: quantitative_measure description: >- Normalized log2 fold change for positive (+) dye orientation. Positive values indicate upregulation in response to deletion. - name: dye_minus dtype: float64 role: quantitative_measure description: >- Normalized log2 fold change for negative (-) dye orientation. Positive values indicate upregulation in response to deletion. - name: mean_norm_log2fc dtype: float64 role: quantitative_measure description: >- Average log2 fold change across dye orientations, providing a dye-independent estimate of gene expression change upon transcription factor deletion. --- # Hughes 2006 This data is parsed from data presented in [G. Chua, Q.D. Morris, R. Sopko, M.D. Robinson, O. Ryan, E.T. Chan, B.J. Frey, B.J. Andrews, C. Boone, & T.R. Hughes, Identifying transcription factor functions and targets by phenotypic activation, Proc. Natl. Acad. Sci. U.S.A. 103 (32) 12045-12050, https://doi.org/10.1073/pnas.0605140103 (2006).](https://doi.org/10.1073/pnas.0605140103) The data is made [available by the author](https://hugheslab.ccbr.utoronto.ca/supplementary-data/yeastTF/) and on NCBI with accession [GSE5499](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5499). I used the data provided by the author. Details on my parsing can be found in `scripts/`. The gene features are from BrentLab/yeast_genome_resources. This repo provides 3 datasets: - **knockout**: Deletion/knockout perturbation normalized log2 fold changes. - **metadata**: Transcription factor metadata including essentiality and QC status. - **overexpression**: Overexpression perturbation normalized log2 fold changes. ## 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](https://github.com/BrentLab/tfbpapi/?tab=readme-ov-file#installation), you can adapt this [tutorial](https://brentlab.github.io/tfbpapi/tutorials/hfqueryapi_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/hughes_2006" dataset from Hugging Face Hub. ```python from huggingface_hub import ModelCard from pprint import pprint card = ModelCard.load("BrentLab/hughes_2006", 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) ``` If you wish to pull the entire repo, due to its size you may need to use an [authentication token](https://huggingface.co/docs/hub/en/security-tokens). 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: ```python from huggingface_hub import snapshot_download import duckdb import os repo_id = "BrentLab/hughes_2006" 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"\nāœ“ Repository downloaded to: {repo_path}") # Construct path to the knockout parquet file parquet_path = os.path.join(repo_path, "knockout.parquet") print(f"āœ“ Parquet file at: {parquet_path}") ``` Use your favorite method of interacting with `parquet` files (eg duckDB, but you could use dplyr in R or pandas, too). ```python # Connect to DuckDB and query the parquet file conn = duckdb.connect() query = """ SELECT * FROM read_parquet(?) WHERE regulator_locus_tag = 'CST6' """ result = conn.execute(query, [parquet_path]).fetchall() print(f"Found {len(result)} rows for CST6") ```