iasva
Iteratively Adjusted Surrogate Variable Analysis
Bioconductor version: 3.23 · Package version: 1.30.0
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
| Maintainer | Donghyung Lee <Donghyung.Lee@jax.org>, Anthony Cheng <Anthony.Cheng@jax.org> |
| Author | Donghyung Lee [aut, cre], Anthony Cheng [aut], Nathan Lawlor [aut], Duygu Ucar [aut] |
| License | GPL-2 |
| Downloads rank | 445 |
| Source branch | RELEASE_3_23 |
| biocViews | BatchEffect, FeatureExtraction, ImmunoOncology, Preprocessing, QualityControl, RNASeq, Software, StatisticalMethod |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | iasva_1.30.0.tar.gz |
| Windows binary (x86_64) | iasva_1.30.0.zip |
| macOS binary (arm64) | iasva_1.30.0.tgz |
| macOS binary (x86_64) | iasva_1.30.0.tgz |
Dependencies
Depends: R (>= 3.5)
Imports: irlba, stats, cluster, graphics, SummarizedExperiment, BiocParallel
Suggests: knitr, testthat, rmarkdown, sva, Rtsne, pheatmap, corrplot, DescTools, RColorBrewer