Learn R Programming

integIRTy (version 1.0.8)

Integrating Multiple Modalities of High Throughput Assays Using Item Response Theory

Description

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) .

Copy Link

Version

Install

install.packages('integIRTy')

Monthly Downloads

177

Version

1.0.8

License

Apache License (== 2.0)

Maintainer

Kevin Coombes

Last Published

April 8th, 2025

Functions in integIRTy (1.0.8)

OV

Ovarian Cancer Datasets
fitOnSinglePlat

Fit IRT model on a single platform
dichotomize

A wrapper that is able to dichotomize expression, methylation and CN data
intIRTeasyRun

The easyrun function for integrating multiple modalities of high throughput assays using binary input matrix.
simulateBinaryResponseMat

Simulate binary response matrix according to 2-parameter Item Characteristic Function for given latent traits and item parameters.
intIRTeasyRunFromRaw

The easyrun function for integrating multiple modalities of high throughput assays using raw data.
dichotomizeExpr

Dichotomize the expression data given both tumor and normal samples.
computeAbility

Calculate latent traits for a given response matrix and item parameters using MLE
dichotomizeMethy

Dichotomize the methylation data given both tumor and normal controls.
dichotomizeCN

Dichotomizing copy number data based on segmented data (i.e. log2ratio).
calculatePermutedScoreByGeneSampling

Calculate the permuted latent trait by gene sampling