PCAWG Passenger Mutation Analysis




PCAWG Data Context

List of genomic element definitions and data context applied to annotate PCAWG mutations

PCAWG-specific Annotations

  1. Genomic elements:

  2. Gene List Categories:




Derived Datasets

Access to all files tagged as "controlled" is login-secured. These controlled dataset used in this publication are accessible to the research community as described under private data download guidleine

TF motif gain or loss enrichment files

  1. P-value associated with gain-of-motif events in PCAWG (uniform background):

  2. P-value associated with loss-of-motif events in PCAWG (uniform background):

  3. P-value associated with gain-of-motif events in PCAWG (signature-corrected background):

  4. P-value associated with loss-of-motif events in PCAWG (signature-corrected background):

Weak Drivers in PCAWG

  1. List of weak driver elements in PCAWG:

Randomized PCAWG mutations

  1. Simulated mutations (moatsim randomization):

  2. Simulated mutations (broad randomization):




Tools and Source Code

This section lists tools and scripts used to characterize putative passengers in the PCAWG project

PCAWG analyses tools

  1. FunSeq2 Source Code: Github link to FunSeq2

  2. ALoFT Source Code: Github link to ALoFT

  3. Additive Variance Analysis Source Code: Github link to additive variance analysis code

  4. VAF and GERP Correlation Analysis:

  5. Survival Analysis:

  6. Subclonal Heterogeneity Analysis:

  7. Signature Correlation Analysis:




Primary Datasets

Access to all files tagged as "controlled" is login-secured. These controlled dataset used in this publication are accessible to the research community as described under private data download guidleine




*All datasets are aligned to the reference genome grch37 and gencode v19, unless mentioned otherwise.

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Citation

Pan-cancer analysis of whole genomes; Campbell et al, BioRxiv 2018

Passenger mutations in 2500 cancer genomes: Overall molecular functional impact and consequences; Kumar et al, BioRxiv 2018

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