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
QFeatures_1.23.1.zip(r-4.7)QFeatures_1.23.1.zip(r-4.6)QFeatures_1.23.1.zip(r-4.5)
QFeatures_1.23.1.tgz(r-4.6-any)QFeatures_1.23.1.tgz(r-4.5-any)
QFeatures_1.23.1.tar.gz(r-4.7-any)QFeatures_1.23.1.tar.gz(r-4.6-any)
QFeatures_1.23.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
QFeatures/json (API)
NEWS

# Install 'QFeatures' in R:
install.packages('QFeatures', repos = c('https://rformassspectrometry.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

11.60 score 29 stars 55 packages 398 scripts 54 exports 91 dependencies

Last updated from:b4667576ef. Checks:7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE484
source / vignettesOK485
linux-release-x86_64NOTE469
macos-release-arm64NOTE391
macos-oldrel-arm64NOTE590
windows-develNOTE508
windows-releaseNOTE477
windows-oldrelNOTE510
wasm-releaseOK179

Exports:addAssayaddAssayLinkaddAssayLinkOneToOneadjacencyMatrixadjacencyMatrix<-aggcountsaggregateFeaturesassayLinkAssayLinkassayLinksAssayLinkscoercecountUniqueFeaturescreatePrecursorIddimsdisplaydropEmptyAssaysexpandDataFramefilterFeaturesfilterNAgetQFeaturesTypeimputeinfIsNAisDuplicatedjoinAssayslogTransformlongFormlongFormatncolsnNAnormalizenrowsQFeaturesrbindRowDatareadQFeaturesreadQFeaturesFromDIANNreadSummarizedExperimentreduceDataFrameremoveAssayreplaceAssayreplaceColnamesrowData<-rowDataNamesscaleTransformselectRowDatasetQFeaturesTypeshowsubsetByFeaturesweepunfoldDataFrameupdateObjectvalidQFeaturesTypesVariableFilterzeroIsNA

Dependencies:abindAnnotationFilteraskpassbase64encBiobaseBiocBaseUtilsBiocGenericsbslibcachemcliclueclustercpp11crosstalkcurldata.tableDelayedArraydigestdplyrevaluatefarverfastmapfontawesomefsgenericsGenomicRangesggplot2gluegtablehighrhtmltoolshtmlwidgetshttrigraphIRangesisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeMsCoreUtilsMultiAssayExperimentopensslotelpillarpkgconfigplotlyplyrpromisesProtGenericspurrrR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownS4ArraysS4VectorsS7sassscalesSeqinfoSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunXVectoryaml

Data visualization from a QFeatures object

Laurent Gatto

Rendered fromVisualization.Rmdusingknitr::rmarkdownon May 11 2026.

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

Imputing quantitative proteomics data

Laurent Gatto

Rendered fromImputation.Rmdusingknitr::rmarkdownon May 11 2026.

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

Load mass spectrometry-based proteomics data using readQFeatures()

Laurent Gatto, Christophe Vanderaa

Rendered fromreadQFeatures.Rmdusingknitr::rmarkdownon May 11 2026.

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

Processing quantitative proteomics data with QFeatures

Laurent Gatto

Rendered fromProcessing.Rmdusingknitr::rmarkdownon May 11 2026.

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

Quantitative features for mass spectrometry data

Laurent Gatto

Rendered fromQFeatures.Rmdusingknitr::rmarkdownon May 11 2026.

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

Supported input formats for readQFeatures()

Karolína Kryštofová, Laurent Gatto

Rendered fromreadQFeatures2.Rmdusingknitr::rmarkdownon May 11 2026.

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

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