Identify Differential Selection

Tests for context-dependent selection on cancer driver genes using somatic mutation data. The package implements the DiffDriver statistical framework to assess whether the strength of positive selection on mutations in a driver gene is associated with tumor- or individual-level context variables, such as clinical traits, genomic features, or immune microenvironment subtypes. DiffDriver estimates individual- and position-specific background mutation rates, models selection as a deviation from the background rate using functional annotations, and tests context effects through a latent-variable logistic model. It provides utilities for preparing mutation and annotation data, fitting differential-selection models, running gene-level association tests, summarizing candidate genes, and visualizing mutation patterns. The method is described in Zhou et al. (2026) "Detecting context-dependent selection on cancer driver genes with DiffDriver" .


diffDriver

To install

First, install the package remotes.

install.packages("remotes")

Then install diffdriver.

remotes::install_github("szhaolab/diffdriver", ref ="main") 

The package also relies on annotation files. There are two types of annotation files.

  • 9-annotation files.
  • 96-annotation files.

Both sets of files can be downloaded at DOI

How to use

Please checkout the tutorial on the package website.

Reference manual

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install.packages("diffdriver")

0.1.7 by Siming Zhao, 3 months ago


https://szhaolab.github.io/diffdriver/, https://github.com/szhaolab/diffdriver


Browse source code at https://github.com/cran/diffdriver


Authors: Siming Zhao [aut, cre] , Jie Zhou [aut] , Qirui Zhang [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Matrix, stats, data.table, brglm, fastTopics, SQUAREM

Suggests knitr, rmarkdown, logging, testthat


See at CRAN