iasva
This is the released version of iasva; for the devel version, see iasva.
Iteratively Adjusted Surrogate Variable Analysis
Bioconductor version: Release (3.23)
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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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 | 1.30.0 |
| In Bioconductor since | BioC 3.8 (R-3.5) (8 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_1.30.0.tar.gz |
| Windows Binary (x86_64) | iasva_1.30.0.zip |
| macOS Binary (big-sur-x86_64) | iasva_1.30.0.tgz |
| macOS Binary (sonoma-arm64) | iasva_1.30.0.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 |