Package: weitrix
Title: Weighted matrix manipulation, finding components of variation
        with weighted or sparse data
Version: 1.0.0
Authors@R: person("Paul", "Harrison", email = "paul.harrison@monash.edu", role = c("aut", "cre"), comment=c(ORCID="0000-0002-3980-268X"))
Description: Data type and tools for working with matrices having precision weights and missing data. This package provides a common representation and tools that can be used with many types of high-throughput data. The meaning of the weights is compatible with usage in the base R function "lm" and the package "limma". Calibrate weights by scaling weights row-wise to account for known predictors of precision. Find PCA-like components of variation even with many missing values, rotated so that individual components may be meaningfully interpreted. DelayedArray matrices and BiocParallel are supported.
License: LGPL-2.1 | file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0), SummarizedExperiment
Imports: methods, utils, stats, assertthat, S4Vectors, DelayedArray,
        DelayedMatrixStats, BiocParallel, BiocGenerics, limma, dplyr,
        purrr, ggplot2, scales, reshape2, RhpcBLASctl
Suggests: knitr, rmarkdown, tidyverse, airway, edgeR, topconfects,
        EnsDb.Hsapiens.v86, org.Sc.sgd.db, AnnotationDbi, testthat (>=
        2.1.0)
RoxygenNote: 7.1.0
VignetteBuilder: knitr
biocViews: Software, DataRepresentation, DimensionReduction,
        GeneExpression, Transcriptomics, RNASeq, SingleCell, Regression
git_url: https://git.bioconductor.org/packages/weitrix
git_branch: RELEASE_3_11
git_last_commit: 626a8e4
git_last_commit_date: 2020-04-27
Date/Publication: 2020-04-27
NeedsCompilation: no
Packaged: 2020-04-28 07:47:22 UTC; biocbuild
Author: Paul Harrison [aut, cre] (<https://orcid.org/0000-0002-3980-268X>)
Maintainer: Paul Harrison <paul.harrison@monash.edu>
Built: R 4.0.0; ; 2020-04-28 18:22:34 UTC; windows
