Package: pvca 1.47.0

Jianying LI

pvca: Principal Variance Component Analysis (PVCA)

This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12.

Authors:Pierre Bushel <[email protected]>

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pvca.pdf |pvca.html✨
pvca/json (API)

# Install 'pvca' in R:
install.packages('pvca', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On BioConductor:pvca-1.47.0(bioc 3.21)pvca-1.46.0(bioc 3.20)

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

microarraybatcheffect

5.66 score 1 packages 108 scripts 456 downloads 7 mentions 1 exports 45 dependencies

Last updated 24 days agofrom:74c5ee9a41. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-winNOTENov 18 2024
R-4.5-linuxNOTENov 18 2024
R-4.4-winNOTENov 18 2024
R-4.4-macNOTENov 18 2024
R-4.3-winNOTENov 18 2024
R-4.3-macNOTENov 18 2024

Exports:pvcaBatchAssess

Dependencies:affyaffyioBiobaseBiocGenericsBiocManagerbootclicolorspacefansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclelimmalme4magrittrMASSMatrixmgcvminqamunsellnlmenloptrpillarpkgconfigpreprocessCoreR6RColorBrewerRcppRcppEigenrlangscalesstatmodtibbleutf8vctrsviridisLitevsnwithrzlibbioc

Batch effect estimation in Microarray data

Rendered frompvca.Rnwusingutils::Sweaveon Nov 18 2024.

Last update: 2018-08-30
Started: 2013-11-01