intIRTeasyRun: The easyrun function for integrating multiple modalities of...

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

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

Description

It fits IRT models on each of the specified platform and calculate integrated latent trait. If required, permuted latent trait by gene sampling will also be calculated. An option for parallel computing is implemented to speed up the computation.

Usage

intIRTeasyRun(platforms, model = 3, guessing = FALSE,
    addPermutedScore = FALSE, fold = 1, echo = TRUE, parallel = FALSE)

Arguments

platforms	A list of response matrices representing different platforms. It assumes that the number of rows (genes ) must be equal whiel the number of columns (samples) can be different.
model	The model type as described in fitOnSinglePlat.
guessing	A logical variable indicating whether to include guessing parameter in the model.
addPermutedScore	A logical variable indicating whether to also calculate permuted latent trait by gene sampling.
fold	The fold of sampling to calculate permuted score as used in calculatePermutedScoreByGeneSampling(). Only relevant when addPermutedScore=TRUE is used.
echo	A logical variable indicating whether to print out the progress information.
parallel	Logical indicating whether to use parallel computing with foreach package as backend.

Details

Parallel computing uses foreach and related packages for backend. The parallelism assumes computation on each platform individually takes similar time; the latent trait computation of the integrated data is assumed to be comparable to computation on individual platform. By default, all parallel options are set to be FALSE. Parallelism happens on the individual assay and combined data level; No parallelism happens on genes since it would only slow donw the computation due to data transfering!

Value

A list with following elements:

fits	Model fits for each platform as returned by fitOnSinglePlat function
estimatedScoreMat	A matrix of estimated latent traits. The first several columns correspond to the individual assays; the last column represents the integrated latent trait with all data.
permutedScoreMat	A matrix of latent trait estimates after permuting the binary matrix within columns. This is only available if addPermutedScore is set to TRUE. The first several columns correspond to the individual assays; the last column represents the integrated data.
dscrmnList	A list of discrimination parameters. Each element contains all of the discrimination parameters as a vector for each assay. The last element contains the discrimination parameters for the integrated data which is formed by combining discrimination parameters from each assay sequentially.
dffcltList	Same format as dscrmnList except it contains difficulty parameter.
gussngList	Same format as dscrmnList except it contains guessing parameter. Be default, this is just all 0's.

Author(s)

Pan Tong ([e-mail]), Kevin R Coombes ([e-mail])

References

Tong P, Coombes KR. integIRTy: a method to identify altered genes in cancer accounting for multiple mechanisms of regulation using item response theory. Bioinformatics, 2012 Nov 15; 28(22):2861–9.

See Also

intIRTeasyRunFromRaw, fitOnSinglePlat, calculatePermutedScoreByGeneSampling

integIRTy documentation built on May 3, 2022, 9:08 a.m.