xseq: Assessing Functional Impact on Gene Expression of Mutations in Cancer

A hierarchical Bayesian approach to assess functional impact of mutations on gene expression in cancer. Given a patient-gene matrix encoding the presence/absence of a mutation, a patient-gene expression matrix encoding continuous value expression data, and a graph structure encoding whether two genes are known to be functionally related, xseq outputs: a) the probability that a recurrently mutated gene g influences gene expression across the population of patients; and b) the probability that an individual mutation in gene g in an individual patient m influences expression within that patient.

Version: 0.2.0
Depends: R (≥ 3.1.0)
Imports: e1071 (≥ 1.6-4), gptk (≥ 1.08), impute (≥ 1.42.0), preprocessCore (≥ 1.30.0), RColorBrewer (≥ 1.1-2), sfsmisc (≥ 1.0-27)
Suggests: knitr
Published: 2015-08-29
Author: Jiarui Ding, Sohrab Shah
Maintainer: Jiarui Ding <jiaruid at cs.ubc.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: xseq results


Reference manual: xseq.pdf
Vignettes: Vignette Title
Package source: xseq_0.2.0.tar.gz
Windows binaries: r-devel: xseq_0.2.0.zip, r-release: xseq_0.2.0.zip, r-oldrel: not available
OS X Snow Leopard binaries: r-release: not available, r-oldrel: not available
OS X Mavericks binaries: r-release: xseq_0.2.0.tgz