iasva

DOI: 10.18129/B9.bioc.iasva  

Iteratively Adjusted Surrogate Variable Analysis

Bioconductor version: Release (3.16)

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.

Author: Donghyung Lee [aut, cre], Anthony Cheng [aut], Nathan Lawlor [aut], Duygu Ucar [aut]

Maintainer: Donghyung Lee <Donghyung.Lee at jax.org>, Anthony Cheng <Anthony.Cheng at jax.org>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("iasva")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("iasva")

 

HTML	R Script	Detecting hidden heterogeneity in single cell RNA-Seq data
PDF		Reference Manual
Text		NEWS

Details

biocViews	BatchEffect, FeatureExtraction, ImmunoOncology, Preprocessing, QualityControl, RNASeq, Software, StatisticalMethod
Version	1.16.0
In Bioconductor since	BioC 3.8 (R-3.5) (4.5 years)
License	GPL-2
Depends	R (>= 3.5)
Imports	irlba, stats, cluster, graphics, SummarizedExperiment, BiocParallel
LinkingTo
Suggests	knitr, testthat, rmarkdown, sva, Rtsne, pheatmap, corrplot, DescTools, RColorBrewer
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	iasva_1.16.0.tar.gz
Windows Binary	iasva_1.16.0.zip
macOS Binary (x86_64)	iasva_1.16.0.tgz
macOS Binary (arm64)	iasva_1.16.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/iasva
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/iasva
Bioc Package Browser	https://code.bioconductor.org/browse/iasva/
Package Short Url	https://bioconductor.org/packages/iasva/
Package Downloads Report	Download Stats