iasva
This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see iasva.
Iteratively Adjusted Surrogate Variable Analysis
Bioconductor version: 3.9
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>
citation("iasva")
):
Installation
To install this package, start R (version "3.6") 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")
Detecting hidden heterogeneity in single cell RNA-Seq data | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | BatchEffect, FeatureExtraction, ImmunoOncology, Preprocessing, QualityControl, RNASeq, Software, StatisticalMethod |
Version | 1.2.0 |
In Bioconductor since | BioC 3.8 (R-3.5) (5.5 years) |
License | GPL-2 |
Depends | R (>= 3.5) |
Imports | irlba, stats, cluster, graphics, SummarizedExperiment, BiocParallel |
System Requirements | |
URL |
See More
Suggests | knitr, testthat, rmarkdown, sva, Rtsne, pheatmap, corrplot, DescTools, RColorBrewer |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | iasva_1.2.0.tar.gz |
Windows Binary | iasva_1.2.0.zip |
Mac OS X 10.11 (El Capitan) | iasva_1.2.0.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 |
Old Source Packages for BioC 3.9 | Source Archive |