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: 0.2.1
Depends: R (≥ 3.1.0)
Imports: e1071 (≥ 1.6-4), gptk (≥ 1.08), impute (≥ 1.38.1), preprocessCore (≥ 1.26.1), RColorBrewer (≥ 1.1-2), sfsmisc (≥ 1.0-27)
Suggests: knitr
Published: 2015-09-11
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

Downloads:

Reference manual: xseq.pdf
Vignettes: xseq – Assessing Functional Impact on Gene Expression of Mutations in Cancer
Package source: xseq_0.2.1.tar.gz
Windows binaries: r-devel: xseq_0.2.1.zip, r-release: xseq_0.2.1.zip, r-oldrel: xseq_0.2.1.zip
OS X Mavericks binaries: r-release: xseq_0.2.1.tgz, r-oldrel: xseq_0.2.1.tgz
Old sources: xseq archive

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