Package: pcaExplorer 2.31.0

Federico Marini

pcaExplorer: Interactive Visualization of RNA-seq Data Using a Principal Components Approach

This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.

Authors:Federico Marini [aut, cre]

pcaExplorer_2.31.0.tar.gz
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pcaExplorer.pdf |pcaExplorer.html✨
pcaExplorer/json (API)
NEWS

# Install 'pcaExplorer' in R:

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

Bug tracker:https://github.com/federicomarini/pcaexplorer/issues

On BioConductor:pcaExplorer-2.31.0(bioc 3.20)pcaExplorer-2.30.0(bioc 3.19)

bioconductor-package

17 exports 1.38 score 177 dependencies 1 dependents 26 mentions

Last updated 2 months agofrom:883a3461c2

Exports:correlatePCs distro_expr geneprofiler genespca get_annotation get_annotation_orgdb hi_loadings limmaquickpca2go makeExampleDESeqDataSet_multifac pair_corr pca2go pcaExplorer pcaplot pcaplot3d pcascree plotPCcorrs topGOtable

Dependencies:abind annotate AnnotationDbi AnnotationForge askpass assertthat base64enc BH Biobase BiocFileCache BiocGenerics BiocManager BiocParallel biomaRt Biostrings bit bit64 bitops blob bslib ca cachem callr Category cli cluster codetools colorspace commonmark cpp11 crayon crosstalk curl data.table DBI dbplyr DelayedArray dendextend DESeq2 digest doParallel dplyr DT egg evaluate fansi farver fastmap filelock fontawesome foreach formatR fs futile.logger futile.options gclus genefilter generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 ggrepel glue GO.db GOstats graph gridBase gridExtra GSEABase gtable heatmaply highr hms htmltools htmlwidgets httpuv httr httr2 igraph IRanges isoband iterators jquerylib jsonlite KEGGREST knitr labeling lambda.r later lattice lazyeval lifecycle limma locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime munsell nlme NMF openssl permute pheatmap pillar pkgconfig plogr plotly plyr png prettyunits processx progress promises ps purrr qap R6 rappdirs RBGL RColorBrewer Rcpp RcppArmadillo RCurl registry reshape2 Rgraphviz rlang rmarkdown rngtools RSQLite S4Arrays S4Vectors sass scales seriation shiny shinyAce shinyBS shinydashboard snow sourcetools SparseArray SparseM statmod stringi stringr SummarizedExperiment survival sys threejs tibble tidyr tidyselect tinytex topGO TSP UCSC.utils utf8 vctrs vegan viridis viridisLite webshot withr xfun XML xml2 xtable XVector yaml zlibbioc

pcaExplorer User Guide

Federico Marini, Harald Binder

Rendered frompcaExplorer.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2023-04-12
Started: 2016-02-22

Up and running with r Biocpkg("pcaExplorer")

Federico Marini, Harald Binder

Rendered fromupandrunning.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2023-04-12
Started: 2019-02-12

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Principal components (cor)relation with experimental covariates	correlatePCs
Plot distribution of expression values	distro_expr
Extract and plot the expression profile of genes	geneprofiler
Principal components analysis on the genes	genespca
Get an annotation data frame from biomaRt	get_annotation
Get an annotation data frame from org db packages	get_annotation_orgdb
Extract genes with highest loadings	hi_loadings
Functional interpretation of the principal components, based on simple overrepresentation analysis	limmaquickpca2go
Make a simulated DESeqDataSet for two or more experimental factors	makeExampleDESeqDataSet_multifac
Pairwise scatter and correlation plot of counts	pair_corr
Functional interpretation of the principal components	pca2go
Explore a dataset from a PCA perspective	pcaExplorer
pcaExplorer: analyzing time-lapse microscopy imaging, from detection to tracking	pcaExplorer-package pcaExplorer-pkg
Sample PCA plot for transformed data	pcaplot
Sample PCA plot for transformed data	pcaplot3d
Scree plot of the PCA on the samples	pcascree
Plot significance of (cor)relations of covariates VS principal components	plotPCcorrs
Extract functional terms enriched in the DE genes, based on topGO	topGOtable