Package: iDOS 1.0.1

iDOS: Integrated Discovery of Oncogenic Signatures

A method to integrate molecular profiles of cancer patients (gene copy number and mRNA abundance) to identify candidate gain of function alterations. These candidate alterations can be subsequently further tested to discover cancer driver alterations. Briefly, this method tests of genomic correlates of mRNA dysregulation and prioritise those where DNA gains/amplifications are associated with elevated mRNA expression of the same gene. For details see, Haider S et al. (2016) "Genomic alterations underlie a pan-cancer metabolic shift associated with tumour hypoxia", Genome Biology, <https://pubmed.ncbi.nlm.nih.gov/27358048/>.

Authors:Syed Haider [aut, cre], Francesca Buffa [aut]

iDOS_1.0.1.tar.gz
iDOS_1.0.1.zip(r-4.7-any)iDOS_1.0.1.zip(r-4.6-any)iDOS_1.0.1.zip(r-4.5-any)
iDOS_1.0.1.tgz(r-4.6-any)iDOS_1.0.1.tgz(r-4.5-any)
iDOS_1.0.1.tar.gz(r-4.7-any)iDOS_1.0.1.tar.gz(r-4.6-any)
iDOS_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
iDOS/json (API)

# Install 'iDOS' in R:
install.packages('iDOS', repos = c('https://syedhaider5.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 10 scripts 282 downloads 9 exports 5 dependencies

Last updated from:40b5f76f63. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK106
source / vignettesOK473
linux-releaseOK109
macos-releaseOK156
macos-oldrelOK166
windows-develOK63
windows-releaseOK52
windows-oldrelOK53
wasm-releaseOK101

Exports:create.counts.tablecreate.training.validation.splitestimate.expression.cna.correlationestimate.null.distribution.correlationfind.DE.featuresget.program.defaultsget.test.dataget.top.featuresload.datasets

Dependencies:formatRfutile.loggerfutile.optionslambda.rVennDiagram

Readme and manuals

Help Manual

Help pageTopics
create.counts.tablecreate.counts.table
create.training.validation.splitcreate.training.validation.split
estimate.expression.cna.correlationestimate.expression.cna.correlation
estimate.null.distribution.correlationestimate.null.distribution.correlation
find.DE.featuresfind.DE.features
get.program.defaultsget.program.defaults
get.test.dataget.test.data
get.top.featuresget.top.features
load.datasetsload.datasets