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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("survcomp")
In most cases, you don't need to download the package archive at all.
survcomp
Performance Assessment and Comparison for Survival Analysis
Bioconductor version: 3.0
R package providing functions to assess and to compare the performance of risk prediction (survival) models.
Author: Benjamin Haibe-Kains, Markus Schroeder, Catharina Olsen, Christos Sotiriou, Gianluca Bontempi, John Quackenbush
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains at utoronto.ca>, Markus Schroeder <markus.schroeder at ucdconnect.ie>, Catharina Olsen <colsen at ulb.ac.be>
Citation (from within R,
enter citation("survcomp")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("survcomp")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("survcomp")
| R Script | SurvComp: a package for performance assessment and comparison for survival analysis | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, GeneExpression, Software, Visualization |
| Version | 1.16.0 |
| In Bioconductor since | BioC 2.8 (R-2.13) |
| License | Artistic-2.0 |
| Depends | survival, prodlim, R (>= 2.10) |
| Imports | ipred, SuppDists, KernSmooth, survivalROC, bootstrap, grid, rmeta |
| LinkingTo | |
| Suggests | Hmisc, CPE, clinfun, Biobase |
| SystemRequirements | |
| Enhances | |
| URL | http://www.pmgenomics.ca/bhklab/ |
| Depends On Me | genefu |
| Imports Me | |
| Suggests Me | breastCancerMAINZ, breastCancerNKI, breastCancerTRANSBIG, breastCancerUNT, breastCancerUPP, breastCancerVDX, metaseqR |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | survcomp_1.16.0.tar.gz |
| Windows Binary | survcomp_1.16.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | survcomp_1.16.0.tgz |
| Mac OS X 10.9 (Mavericks) | survcomp_1.16.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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