Launch a Shiny application to process QFeatures objects

processQFeatures() launches an interactive Shiny application that allows users to visually configure and apply pre-processing workflows to a QFeatures object.

The input qfeatures can be provided as an in-memory QFeatures object, as a path to an .rds file containing one, or omitted. If omitted, the application prompts the user to upload a QFeatures object from an .rds file.

Usage

processQFeatures(
  qfeatures = NULL,
  initialSets = NULL,
  prefilledSteps = c("sampleFiltering", "featureFiltering", "missingValuesFeatures",
    "missingValuesSamples", "normalisation", "aggregation", "join", "aggregation"),
  maxSize = 100
)

Arguments

qfeatures: Optional QFeatures object to be processed, or a character string specifying the path to a .rds file containing a QFeatures object. If omitted, the app starts without processing steps and displays a startup modal.
initialSets: An integer, logical, or character vector specifying which assays (feature sets) should be used as the starting point for processing. If NULL and qfeatures is provided, all assays in qfeatures are used. If qfeatures is omitted, the user chooses the initial sets after uploading the .rds file.
prefilledSteps: A character vector specifying the initial workflow steps to display when the application launches. Steps must be provided using their internal identifiers (e.g. "sampleFiltering", "featureFiltering", "normalisation").
maxSize: An integer that changes the shiny.maxRequestSize value, in MB. This controls the maximum upload size for the startup .rds file upload modal.

Value

The processQFeatures Shiny application.

Details

The application provides a drag-and-drop workflow builder that allows users to select, order, and configure processing steps such as filtering, normalization, and transformation. The configured workflow can then be applied to the selected assays.

Examples


# the example should be launched with `ask = FALSE`

library(QFeatures)
#> Loading required package: MultiAssayExperiment
#> Loading required package: SummarizedExperiment
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#> 
#> Attaching package: ‘MatrixGenerics’
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#>     colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#>     colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#>     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#>     colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#>     colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#>     colWeightedMeans, colWeightedMedians, colWeightedSds,
#>     colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#>     rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#>     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#>     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#>     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#>     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#>     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#>     rowWeightedSds, rowWeightedVars
#> Loading required package: GenomicRanges
#> Loading required package: stats4
#> Loading required package: BiocGenerics
#> Loading required package: generics
#> 
#> Attaching package: ‘generics’
#> The following objects are masked from ‘package:base’:
#> 
#>     as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
#>     setequal, union
#> 
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
#>     mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
#>     rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
#>     unsplit, which.max, which.min
#> Loading required package: S4Vectors
#> 
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:utils’:
#> 
#>     findMatches
#> The following objects are masked from ‘package:base’:
#> 
#>     I, expand.grid, unname
#> Loading required package: IRanges
#> Loading required package: Seqinfo
#> Loading required package: Biobase
#> Welcome to Bioconductor
#> 
#>     Vignettes contain introductory material; view with
#>     'browseVignettes()'. To cite Bioconductor, see
#>     'citation("Biobase")', and for packages 'citation("pkgname")'.
#> 
#> Attaching package: ‘Biobase’
#> The following object is masked from ‘package:MatrixGenerics’:
#> 
#>     rowMedians
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     anyMissing, rowMedians
#> 
#> Attaching package: ‘QFeatures’
#> The following object is masked from ‘package:base’:
#> 
#>     sweep
library(QFeaturesGUI)

data("sampleTable")
data("inputTable")

qfeatures <- readQFeatures(
    inputTable,
    colData = sampleTable,
    runCol = "Raw.file"
)
#> Checking arguments.
#> Loading data as a 'SummarizedExperiment' object.
#> Splitting data in runs.
#> 
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#> Formatting sample annotations (colData).
#> Formatting data as a 'QFeatures' object.

app <- processQFeatures(
    qfeatures,
    initialSets = seq_along(qfeatures),
    maxSize = 100
)

if (interactive()) {
    shiny::runApp(app)
}