Package: integIRTy 1.0.7

Kevin R. Coombes

integIRTy: Integrating Multiple Modalities of High Throughput Assays Using Item Response Theory

Provides a systematic framework for integrating multiple modalities of assays profiled on the same set of samples. The goal is to identify genes that are altered in cancer either marginally or consistently across different assays. The heterogeneity among different platforms and different samples are automatically adjusted so that the overall alteration magnitude can be accurately inferred. See Tong and Coombes (2012) <doi:10.1093/bioinformatics/bts561>.

Authors:Pan Tong, Kevin R Coombes

integIRTy_1.0.7.tar.gz
integIRTy_1.0.7.tar.gz(r-4.5-noble)integIRTy_1.0.7.tar.gz(r-4.4-noble)
integIRTy_1.0.7.tgz(r-4.4-emscripten)integIRTy_1.0.7.tgz(r-4.3-emscripten)
integIRTy.pdf |integIRTy.html✨
integIRTy/json (API)

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

Peer review:

Bug tracker:https://r-forge.r-project.org/projects/oompa

Datasets:
  • CN_N - Ovarian Cancer Datasets
  • CN_T - Ovarian Cancer Datasets
  • Expr_N - Ovarian Cancer Datasets
  • Expr_T - Ovarian Cancer Datasets
  • Methy_N - Ovarian Cancer Datasets
  • Methy_T - Ovarian Cancer Datasets

10 exports 0.00 score 16 dependencies 139 downloads

Last updated 2 years agofrom:c5dd3296e5

Exports:calculatePermutedScoreByGeneSamplingcomputeAbilitydichotomizedichotomizeCNdichotomizeExprdichotomizeMethyfitOnSinglePlatintIRTeasyRunintIRTeasyRunFromRawsimulateBinaryResponseMat

Dependencies:abindadmisccodetoolsdoParallelexpmforeachiteratorslatticeltmMASSMatrixmclustmsmmvtnormpolycorsurvival

integIRTy Vignette

Rendered fromintegIRTy.Rnwusingutils::Sweaveon Jul 02 2024.

Last update: 2017-07-11
Started: 2017-07-11