Package: iasva
Type: Package
Title: Iteratively Adjusted Surrogate Variable Analysis
Version: 1.21.0
Date: 2018-11-29
Authors@R: c(person("Donghyung", "Lee", email = "Donghyung.Lee@jax.org",
    role = c("aut", "cre")), person("Anthony", "Cheng", 
    email = "Anthony.Cheng@jax.org", role = "aut"),
    person("Nathan", "Lawlor", email = "Nathan.Lawlor@jax.org",
    role = "aut"), person("Duygu", "Ucar",
    email = "Duygu.Ucar@jax.org", role = "aut"))
Maintainer: Donghyung Lee <Donghyung.Lee@jax.org>, Anthony Cheng <Anthony.Cheng@jax.org>
Description: 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.
Depends: 
    R (>= 3.5),
Imports:
    irlba,
    stats,
    cluster,
    graphics,
    SummarizedExperiment,
    BiocParallel
License: GPL-2
biocViews: Preprocessing, QualityControl, BatchEffect, RNASeq, Software,
    StatisticalMethod, FeatureExtraction, ImmunoOncology 
Suggests:
    knitr,
    testthat,
    rmarkdown,
    sva,
    Rtsne,
    pheatmap,
    corrplot,
    DescTools,
    RColorBrewer
VignetteBuilder: knitr
RoxygenNote: 6.0.1