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iasva

Iteratively Adjusted Surrogate Variable Analysis

Bioconductor version: 3.24 · Package version: 1.31.0

Iteratively Adjusted Surrogate Variable Analysis (IA-SVA) is a statistical framework to uncover hidden sources of variation even when these sources are correlated. IA-SVA provides a flexible methodology to i) identify a hidden factor for unwanted heterogeneity while adjusting for all known factors; ii) test the significance of the putative hidden factor for explaining the unmodeled variation in the data; and iii), if significant, use the estimated factor as an additional known factor in the next iteration to uncover further hidden factors.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("iasva")

Details

MaintainerDonghyung Lee <Donghyung.Lee@jax.org>, Anthony Cheng <Anthony.Cheng@jax.org>
AuthorDonghyung Lee [aut, cre], Anthony Cheng [aut], Nathan Lawlor [aut], Duygu Ucar [aut]
LicenseGPL-2
Downloads rank445
Source branchdevel
biocViewsBatchEffect, FeatureExtraction, ImmunoOncology, Preprocessing, QualityControl, RNASeq, Software, StatisticalMethod

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageiasva_1.31.0.tar.gz
Windows binary (x86_64)iasva_1.31.0.zip
macOS binary (arm64)iasva_1.31.0.tgz
macOS binary (x86_64)iasva_1.31.0.tgz
Dependencies

Depends: R (>= 3.5)

Imports: irlba, stats, cluster, graphics, SummarizedExperiment, BiocParallel

Suggests: knitr, testthat, rmarkdown, sva, Rtsne, pheatmap, corrplot, DescTools, RColorBrewer