iasva
This is the released version of iasva; for the devel version, see iasva.
Iteratively Adjusted Surrogate Variable Analysis
Bioconductor version: Release (3.20)
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 "4.4") 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 | 1.24.0 |
| In Bioconductor since | BioC 3.8 (R-3.5) (6 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_1.24.0.tar.gz |
| Windows Binary (x86_64) | iasva_1.24.0.zip |
| macOS Binary (x86_64) | iasva_1.24.0.tgz |
| macOS Binary (arm64) | iasva_1.24.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/iasva |
| Source Repository (Developer Access) | git clone [email protected]:packages/iasva |
| Bioc Package Browser | https://code.bioconductor.org/browse/iasva/ |
| Package Short Url | https://bioconductor.org/packages/iasva/ |
| Package Downloads Report | Download Stats |