SigCheck
Check a gene signature's prognostic performance against random signatures, known signatures, and permuted data/metadata
Bioconductor version: 3.23 · Package version: 2.44.0
While gene signatures are frequently used to predict phenotypes (e.g. predict prognosis of cancer patients), it it not always clear how optimal or meaningful they are (cf David Venet, Jacques E. Dumont, and Vincent Detours' paper "Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome"). Based on suggestions in that paper, SigCheck accepts a data set (as an ExpressionSet) and a gene signature, and compares its performance on survival and/or classification tasks against a) random gene signatures of the same length; b) known, related and unrelated gene signatures; and c) permuted data and/or metadata.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SigCheck") Details
| Maintainer | Rory Stark <bioconductor@starkhome.com> |
| Author | Rory Stark <bioconductor@starkhome.com> and Justin Norden |
| License | Artistic-2.0 |
| Downloads rank | 547 |
| Source branch | RELEASE_3_23 |
| biocViews | Classification, GeneExpression, GeneSetEnrichment, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | SigCheck_2.44.0.tar.gz |
| Windows binary (x86_64) | SigCheck_2.44.0.zip |
| macOS binary (arm64) | SigCheck_2.44.0.tgz |
| macOS binary (x86_64) | SigCheck_2.44.0.tgz |
Dependencies
Depends: R (>= 4.0.0), MLInterfaces, Biobase, e1071, BiocParallel, survival
Imports: graphics, stats, utils, methods
Suggests: BiocStyle, breastCancerNKI, qusage