Launch a Shiny App for interactive exploration of a dataset from the perspective of Principal Components Analysis

pcaExplorer(dds = NULL, dst = NULL, countmatrix = NULL,
  coldata = NULL, pca2go = NULL, annotation = NULL,
  runLocal = TRUE)

Arguments

dds

A DESeqDataSet object. If not provided, then a countmatrix and a coldata need to be provided. If none of the above is provided, it is possible to upload the data during the execution of the Shiny App

dst

A DESeqTransform object. Can be computed from the dds object if left NULL. If none is provided, then a countmatrix and a coldata need to be provided. If none of the above is provided, it is possible to upload the data during the execution of the Shiny App

countmatrix

A count matrix, with genes as rows and samples as columns. If not provided, it is possible to upload the data during the execution of the Shiny App

coldata

A data.frame containing the info on the covariates of each sample. If not provided, it is possible to upload the data during the execution of the Shiny App

pca2go

An object generated by the pca2go function, which contains the information on enriched functional categories in the genes that show the top or bottom loadings in each principal component of interest. If not provided, it is possible to compute live during the execution of the Shiny App

annotation

A data.frame object, with row.names as gene identifiers (e.g. ENSEMBL ids) and a column, gene_name, containing e.g. HGNC-based gene symbols

runLocal

A logical indicating whether the app is to be run locally or remotely on a server, which determines how documentation will be accessed.

Value

A Shiny App is launched for interactive data exploration

Examples

library(airway) data(airway) airway
#> class: RangedSummarizedExperiment #> dim: 64102 8 #> metadata(1): '' #> assays(1): counts #> rownames(64102): ENSG00000000003 ENSG00000000005 ... LRG_98 LRG_99 #> rowData names(0): #> colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521 #> colData names(9): SampleName cell ... Sample BioSample
dds_airway <- DESeq2::DESeqDataSetFromMatrix(assay(airway), colData = colData(airway), design=~dex+cell) if (FALSE) { rld_airway <- DESeq2::rlogTransformation(dds_airway) pcaExplorer(dds_airway,rld_airway) pcaExplorer(countmatrix = counts(dds_airway), coldata = colData(dds_airway)) pcaExplorer() # and then upload count matrix, covariate matrix (and eventual annotation) }