Package: QFeatures 1.23.1

Laurent Gatto

QFeatures: Quantitative features for mass spectrometry data

The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.

Authors:Laurent Gatto [aut, cre], Christophe Vanderaa [aut], Karolína Kryštofová [ctb], Léopold Guyot [ctb]

QFeatures_1.23.1.tar.gz
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QFeatures_1.23.1.tgz(r-4.6-any)QFeatures_1.23.1.tgz(r-4.5-any)
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QFeatures_1.23.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
QFeatures/json (API)

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

Bug tracker:https://github.com/rformassspectrometry/qfeatures/issues

Pkgdown/docs site:https://rformassspectrometry.github.io

Datasets:
  • feat1 - Feature example data
  • feat2 - Feature example data
  • feat3 - Example 'QFeatures' object after processing
  • feat4 - Example 'QFeatures'
  • ft_na - Feature example data
  • hlpsms - HyperLOPIT PSM-level expression data
  • se_na2 - Feature example data

On BioConductor:QFeatures-1.23.1(bioc 3.24)QFeatures-1.22.0(bioc 3.23)

infrastructuremassspectrometryproteomicsmetabolomicsbioconductormass-spectrometry

11.46 score 29 stars 57 packages 397 scripts 54 exports 91 dependencies

Last updated from:b4667576ef. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING230
linux-devel-x86_64NOTE806
source / vignettesOK362
linux-release-x86_64NOTE596
macos-release-arm64NOTE578
macos-oldrel-arm64NOTE760
windows-develNOTE548
windows-releaseNOTE524
windows-oldrelNOTE492
wasm-releaseOK211

Exports:addAssayaddAssayLinkaddAssayLinkOneToOneadjacencyMatrixadjacencyMatrix<-aggcountsaggregateFeaturesassayLinkAssayLinkassayLinksAssayLinkscoercecountUniqueFeaturescreatePrecursorIddimsdisplaydropEmptyAssaysexpandDataFramefilterFeaturesfilterNAgetQFeaturesTypeimputeinfIsNAisDuplicatedjoinAssayslogTransformlongFormlongFormatncolsnNAnormalizenrowsQFeaturesrbindRowDatareadQFeaturesreadQFeaturesFromDIANNreadSummarizedExperimentreduceDataFrameremoveAssayreplaceAssayreplaceColnamesrowData<-rowDataNamesscaleTransformselectRowDatasetQFeaturesTypeshowsubsetByFeaturesweepunfoldDataFrameupdateObjectvalidQFeaturesTypesVariableFilterzeroIsNA

Dependencies:abindAnnotationFilteraskpassbase64encBiobaseBiocBaseUtilsBiocGenericsbslibcachemcliclueclustercpp11crosstalkcurldata.tableDelayedArraydigestdplyrevaluatefarverfastmapfontawesomefsgenericsGenomicRangesggplot2gluegtablehighrhtmltoolshtmlwidgetshttrigraphIRangesisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeMsCoreUtilsMultiAssayExperimentopensslotelpillarpkgconfigplotlyplyrpromisesProtGenericspurrrR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownS4ArraysS4VectorsS7sassscalesSeqinfoSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunXVectoryaml

Imputing quantitative proteomics data
Introduction | Example data | Simple imputation | Passing paramters to the imputation function | The MARGIN argument | Mixed imputation | Different margins | Passing paramters to the imputation functions | Using the whole matrix to compute imputated values | Session information | License | References
Rendered fromImputation.Rmdusingknitr::rmarkdown

Last update: 2026-05-03
Started: 2026-05-03

Supported input formats for readQFeatures()
Methods | Datasets | Existing search outputs | New search outputs | Introduction | MaxQuant | Label-free | TMT | DIA-NN | plexDIA | sage | FragPipe | Session information | License
Rendered fromreadQFeatures2.Rmdusingknitr::rmarkdown

Last update: 2026-05-03
Started: 2026-04-26

Processing quantitative proteomics data with QFeatures
Reading data as QFeatures | Encoding the experimental design | Filtering out contaminants and reverse hits | Removing up unneeded feature variables | Managing missing values | Counting unique features | Imputation | Data transformation | Normalisation | Feature aggregation | See also | Session information | License | References
Rendered fromProcessing.Rmdusingknitr::rmarkdown

Last update: 2026-05-03
Started: 2019-12-14

Load mass spectrometry-based proteomics data using readQFeatures()
The QFeatures class | Converting tabular data | The single-set case | The multi-set case | Including sample annotations | Additional information | Sample names | Special case: empty samples | Reducing verbose | Under the hood | License | Reference
Rendered fromreadQFeatures.Rmdusingknitr::rmarkdown

Last update: 2026-04-26
Started: 2026-04-26

Data visualization from a QFeatures object
Preparing the data | Exploring the QFeatures hierarchy | Basic data exploration | Using ggplot2 | Advanced data exploration | Interactive data exploration | License | References
Rendered fromVisualization.Rmdusingknitr::rmarkdown

Last update: 2025-05-21
Started: 2021-07-19

Quantitative features for mass spectrometry data
Introduction | Creating QFeatures object | Manipulating feature metadata | Subsetting | Filtering | Session information | License | References
Rendered fromQFeatures.Rmdusingknitr::rmarkdown

Last update: 2025-05-21
Started: 2020-07-14

Readme and manuals

Help Manual

Help pageTopics
Aggregate assays' quantitative featuresadjacencyMatrix,QFeatures-method adjacencyMatrix,SummarizedExperiment-method adjacencyMatrix<- aggcounts aggcounts,SummarizedExperiment-method aggregateFeatures aggregateFeatures,QFeatures-method aggregateFeatures,SummarizedExperiment-method
Placeholder for generics functions documentationAllGenerics
Links between AssaysaddAssayLink addAssayLinkOneToOne AssayLink assayLink AssayLink-class AssayLinks assayLinks AssayLinks-class class:AssayLink class:AssayLinks show,AssayLink-method updateObject,AssayLink-method updateObject,AssayLinks-method [,AssayLink,character,ANY,ANY-method [,AssayLink,character-method [,AssayLinks,character-method [,AssayLinks,list,ANY,ANY-method
Count Unique FeaturescountUniqueFeatures
Create precursor identfierscreatePrecursorId
Interactive MultiAssayExperiment Explorerdisplay
Feature example datafeat1 feat2 ft_na se_na2
Example 'QFeatures' object after processingfeat3
Example 'QFeatures'feat4
hyperLOPIT PSM-level expression datahlpsms
Quantitative proteomics data imputationimpute impute,QFeatures-method impute,SummarizedExperiment-method
Join assays in a QFeatures objectjoinAssays
Reshape into a long data formatlongForm longForm,QFeatures longForm,QFeatures-method longForm,SummarizedExperiment longForm,SummarizedExperiment-method longFormat
Managing missing datafilterNA filterNA,QFeatures-method filterNA,SummarizedExperiment-method infIsNA infIsNA,QFeatures,character-method infIsNA,QFeatures,integer-method infIsNA,QFeatures,missing-method infIsNA,QFeatures,numeric-method infIsNA,SummarizedExperiment,missing-method missing-data nNA nNA,QFeatures,character-method nNA,QFeatures,integer-method nNA,QFeatures,missing-method nNA,QFeatures,numeric-method nNA,SummarizedExperiment,missing-method zeroIsNA zeroIsNA,QFeatures,character-method zeroIsNA,QFeatures,integer-method zeroIsNA,QFeatures,missing-method zeroIsNA,QFeatures,numeric-method zeroIsNA,SummarizedExperiment,missing-method
Quantitative MS QFeaturesaddAssay c,QFeatures-method class:QFeatures coerce,MultiAssayExperiment,QFeatures-method coerce-QFeatures dims,QFeatures-method dropEmptyAssays names<-,QFeatures,character-method ncols,QFeatures-method nrows,QFeatures-method plot.QFeatures QFeatures QFeatures-class rbindRowData removeAssay replaceAssay replaceColnames rowData,QFeatures-method rowData<-,QFeatures,ANY-method rowData<-,QFeatures,DataFrameList-method rowDataNames selectRowData show,QFeatures-method updateObject,QFeatures-method [,QFeatures,ANY,ANY,ANY-method [,QFeatures,character,ANY,ANY-method [[<-,QFeatures,ANY,ANY-method
Filter features based on their rowDataCharacterVariableFilter CharacterVariableFilter-class filterFeatures filterFeatures,QFeatures,AnnotationFilter-method filterFeatures,QFeatures,formula-method isDuplicated NumericVariableFilter NumericVariableFilter-class QFeatures-filtering VariableFilter
QFeatures processinglogTransform logTransform,QFeatures-method logTransform,SummarizedExperiment-method normalize normalize,QFeatures-method normalize,SummarizedExperiment-method normalizeMethods QFeatures-processing scaleTransform scaleTransform,QFeatures-method scaleTransform,SummarizedExperiment-method sweep sweep,QFeatures-method sweep,SummarizedExperiment-method
QFeatures from tabular datareadQFeatures readQFeatures,data.frame,data.frame readQFeatures,data.frame,vector readQFeatures,missing,vector readSummarizedExperiment
Read DIA-NN output as a QFeatures objectsreadQFeaturesFromDIANN
Reduces and expands a 'DataFrame'expandDataFrame reduceDataFrame
Subset by feature namesubsetByFeature subsetByFeature,QFeatures,character-method
Unfold a data frameunfoldDataFrame