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Insights for Precision Oncology from the 100,000 Genomes Cancer Programme

​ This page describes the resource methods that accompany the paper "Insights for precision oncology from the 100,000 Genomes Cancer Programme" Sosinsky et al. 2023.

A selection of supplementary materials are available online (see below Online Supplementary Materials). However, most of the data is located within the Research Environment, Genomics England's secure workspace.

To access genomic and clinical data within this workspace, you must apply to become a member of either the Genomics England Research Network or the Discovery Forum (industry partners).

The process for joining the Research Network consists of the following steps:

  • Your institution will need to sign a participation agreement and email the signed version to gecip-help@genomicsengland.co.uk
  • Choose a GECIP of interest and apply to join through the online form
  • Track your application on the Research Portal
  • The domain lead will review your application within ten working days
  • Your institution will validate your affiliation
  • You will complete our online Information Governance training and will be granted access to the Research Environment within two hours of passing the online training

Online code

Code to recreate the paper figures is available on gitlab and zenodo. You can copy and paste this code into Rstudio in the Research Environment to recreate the figures in the publication.

Research Environment Supplementary Materials

A master table containing the data required to recreate figures in the paper is located within the Research Environment at /published_data_archive/paper_data/paper_data_RR335/

There are two subfolders in that location: /published_data_archive/paper_data/paper_data_RR335/data/ and /published_data_archive/paper_data/paper_data_RR335/code/.

Data directory

Within data/ subfolder there are the following files:

  • pan_cancer_master_table_2023-08-30.tsv (master table)
  • pan_cancer_master_table_data_dictionary.xlsx (data dictionary for master table) ​

Code directory:

Within the /published_data_archive/paper_data/paper_data_RR335/code/ subfolder there are the following files:

  • README.md (description of code) ​
  • figure_1/
    • pan_cancer_figure_1e_stage_vs_disease_type.R
    • pan_cancer_figure_1e_treatment_status_vs_disease_type.R
    • pan_cancer_figure_1e_tumour_purity_vs_disease_type.R ​
  • figure_2/
    • pan_cancer_figure_2_small_variants_somatic.R
    • pan_cancer_figure_2_copy_number_aberrations.R
    • pan_cancer_figure_2_structural_variants.R
    • pan_cancer_figure_2_hrd.R
    • pan_cancer_figure_2_tmb.R
    • pan_cancer_figure_2_mmr_signatures.R
    • pan_cancer_figure_2_small_variants_germline.R
    • pan_cancer_figure_2_pharmacogenomic_variants.R ​
  • figure_3/
    • pan_cancer_figure_3a_tmb_cosmic_signatures_and_hr_status.R
    • pan_cancer_figure_3b_survival_curves_hr_and_mmr_status.R
    • pan_cancer_figure_3c_survival_curves_skcm_and_luad.R ​
  • figure_4/
    • pan_cancer_figure_4a_small_variants_and_copy_number_aberrations.R
    • pan_cancer_figure_4b_survival_curves_gene_alterations.R ​
  • utilities/
    • get_actionability_plot.R
    • get_actionable_targets.R
    • get_filepaths.R
    • get_master_table.R
    • get_pan_cancer_code_order.R
    • get_public_sample_ids.R
    • get_study_code_order.R
    • get_treatments.R
    • get_vardata_counts_splits.R ​
  • data/
    • CANCER_CENSUS_GENES.tsv
    • Inherited-Cancer-NGTD-MR-October-2021-22.xlsx
    • Somatic-Cancer-NGTD-MR-October-2021-22.xlsx
    • clinical_indication_to_pan_cancer_code_mapping.xlsx
    • pan_cancer_code_definitions.tsv

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