iasva: Iteratively Adjusted Surrogate Variable Analysis

Package: iasva 1.31.0

Donghyung Lee

iasva: Iteratively Adjusted Surrogate Variable Analysis

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.

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

iasva_1.31.0.tar.gz
iasva_1.31.0.zip(r-4.7)iasva_1.31.0.zip(r-4.6)iasva_1.31.0.zip(r-4.5)
iasva_1.31.0.tgz(r-4.6-any)iasva_1.31.0.tgz(r-4.5-any)
iasva_1.31.0.tar.gz(r-4.7-any)iasva_1.31.0.tar.gz(r-4.6-any)
iasva_1.31.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
iasva/json (API)

# Install 'iasva' in R:

install.packages('iasva', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

On BioConductor:iasva-1.31.0(bioc 3.24)iasva-1.30.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

preprocessing qualitycontrol batcheffect rnaseq software statisticalmethod featureextraction immunooncology

4.68 score 48 scripts 380 downloads 1 mentions 4 exports 28 dependencies

Last updated from:cf5a38d124. Checks:1 WARNING, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	214
linux-devel-x86_64	OK	410
source / vignettes	OK	314
linux-release-x86_64	OK	335
macos-release-arm64	OK	179
macos-oldrel-arm64	OK	144
windows-devel	OK	238
windows-release	OK	230
windows-oldrel	OK	222
wasm-release	OK	167

Exports:fast_iasva find_markers iasva study_R2

Dependencies:abind BH Biobase BiocGenerics BiocParallel cluster codetools cpp11 DelayedArray formatR futile.logger futile.options generics GenomicRanges IRanges irlba lambda.r lattice Matrix MatrixGenerics matrixStats S4Arrays S4Vectors Seqinfo snow SparseArray SummarizedExperiment XVector

Detecting hidden heterogeneity in single cell RNA-Seq data

Load packages | Load the islet single cell RNA-Seq data | Calculate geometric library size, i.e., library size of log-transfromed read counts. | Run IA-SVA | Find marker genes for the detected heterogeneity (SV1). | Run tSNE to detect the hidden heterogeneity. | Run tSNE post IA-SVA analyses, i.e., run tSNE on marker genes associated with SV1 as detected by IA-SVA. | Using a faster implementation of IA-SVA (fast_iasva) | Tuning parameters for IA-SVA | Session Info

Rendered fromdetecting_hidden_heterogeneity_iasvaV0.95.Rmdusingknitr::rmarkdown

Help page	Topics
A function for fast IA-SVA	fast_iasva
A function for finding markers for hidden factors	find_markers
A function for iteratively adjusted surrogate variable analysis (IA-SVA)	iasva
A function to study different values of R2	study_R2

Help page

Topics

A function for fast IA-SVA

fast_iasva

A function for finding markers for hidden factors

find_markers

A function for iteratively adjusted surrogate variable analysis (IA-SVA)

iasva

A function to study different values of R2

study_R2