metadata

language:
  - en
license:
  - mit
task_categories:
  - table-to-text
task_ids:
  - entity-linking-retrieval
pretty_name: TCGA Cancer Variant and Clinical Data
tags:
  - cancer-genomics
  - variant-calling
  - transcriptomics
  - clinical-data
dataset_info:
  features:
    - name: aliquot_id
      dtype: string
    - name: transcript_id
      dtype: string
    - name: mutated_protein
      dtype: string
    - name: wildtype_protein
      dtype: string
    - name: wgs_aliquot_id
      dtype: string
    - name: Cancer Type
      dtype: string
    - name: Cancer Stage
      dtype: string
    - name: Donor Survival Time
      dtype: float
    - name: Donor Vital Status
      dtype: string
    - name: Donor Age at Diagnosis
      dtype: float
    - name: Tumour Grade
      dtype: string
    - name: Donor Sex
      dtype: string
    - name: Histology Abbreviation
      dtype: string
  config_name: default
  splits:
    - name: train
      num_bytes: null
      num_examples: null
dataset_files:
  - name: protein_sequences_metadata.tsv
    description: >-
      This file contains metadata on protein sequences, including transcript
      IDs, mutated protein sequences, wildtype sequences, and clinical
      information related to cancer studies from TCGA.
    format: tsv
    url: ./protein_sequences_metadata.tsv
size_categories:
  - 10K<n<100K

TCGA Cancer Variant and Clinical Data

Dataset Description

This dataset combines genetic variant information at the protein level with clinical data from The Cancer Genome Atlas (TCGA) project, curated by the International Cancer Genome Consortium (ICGC). It provides a comprehensive view of protein-altering mutations and clinical characteristics across various cancer types.

Dataset Summary

The dataset includes:

Protein sequence data for both mutated and wildtype proteins
Clinical data for each patient, including cancer type, stage, survival time, and demographic information
Unique identifiers linking genomic data to clinical information

Supported Tasks and Leaderboards

This dataset can support various tasks in cancer genomics and precision medicine, including:

Analysis of protein-altering mutations and their impact on cancer progression
Correlation studies between specific protein mutations and clinical outcomes
Cancer subtype classification based on genetic and clinical features
Survival analysis incorporating genetic and clinical data
Identification of potential biomarkers for cancer prognosis or treatment response

Languages

The dataset is in English, but primarily consists of protein sequences, numerical data, and standardized clinical terms.

Dataset Structure

Data Instances

Each row in the dataset represents a unique combination of a patient sample and a transcript. Here's an example entry:

{
  'aliquot_id': '8fb9496e-ddb8-11e4-ad8f-5ed8e2d07381',
  'transcript_id': 'ENST00000512632',
  'mutated_protein': 'MACPALGLEALQPLQPEPPPE...', # (truncated for brevity)
  'wildtype_protein': 'MACPALGLEALQPLQPEPPPE...', # (truncated for brevity)
  'wgs_aliquot_id': '80ab6c08-c622-11e3-bf01-24c6515278c0',
  'Cancer Type': 'Liver Cancer - RIKEN, JP',
  'Cancer Stage': '2',
  'Donor Survival Time': 1440.0,
  'Donor Vital Status': 'deceased',
  'Donor Age at Diagnosis': 67.0,
  'Tumour Grade': 'I',
  'Donor Sex': 'male',
  'Histology Abbreviation': 'Liver-HCC'
}

Data Fields

aliquot_id: Unique identifier for the RNA sequencing sample
transcript_id: Ensembl transcript ID
mutated_protein: Amino acid sequence of the mutated protein
wildtype_protein: Amino acid sequence of the wildtype (non-mutated) protein
wgs_aliquot_id: Identifier for the whole genome sequencing data
Cancer Type: Type and origin of the cancer
Cancer Stage: Stage of the cancer at diagnosis
Donor Survival Time: Survival time of the patient in days
Donor Vital Status: Whether the patient is alive or deceased
Donor Age at Diagnosis: Age of the patient at diagnosis
Tumour Grade: Grade of the tumor
Donor Sex: Sex of the patient
Histology Abbreviation: Abbreviation for the cancer histology

Data Splits

This dataset does not have explicit splits. All data is contained in a single table.

Dataset Creation

Source Data

The dataset was derived from the following ICGC/TCGA sources:

Normalized transcript expression data:

s3://icgc25k-open/PCAWG/transcriptome/transcript_expression/pcawg.rnaseq.transcript.expr.tpm.tsv.gz

Metadata linked to aliquot_id:

s3://icgc25k-open/PCAWG/transcriptome/metadata/rnaseq.extended.metadata.aliquot_id.V4.tsv.gz

SNV and Indel data:

s3://icgc25k-open/PCAWG/consensus_snv_indel/final_consensus_snv_indel_passonly_icgc.public.tgz

Data Processing

The data processing involved several steps:

Downloading and extracting the source files
Parsing VCF files to extract variant information
Translating DNA variants to protein sequences
Combining the protein sequence data with clinical data

The script set_tcga_data.py was used to perform these processing steps.

Additional Information

Dataset Curators

This dataset was curated by [Your Name/Organization] based on data from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project.

Licensing Information

This dataset is released under the MIT License. Please note that usage of the source TCGA data may be subject to additional terms and conditions.

Citation Information

If you use this dataset, please cite:

[Your citation information]

And also cite the original PCAWG project:

The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82–93 (2020). https://doi.org/10.1038/s41586-020-1969-6

Contributions

Thanks to the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium for making the original data available.