Package: scp 1.15.0

Christophe Vanderaa

scp: Mass Spectrometry-Based Single-Cell Proteomics Data Analysis

Utility functions for manipulating, processing, and analyzing mass spectrometry-based single-cell proteomics data. The package is an extension to the 'QFeatures' package and relies on 'SingleCellExpirement' to enable single-cell proteomics analyses. The package offers the user the functionality to process quantitative table (as generated by MaxQuant, Proteome Discoverer, and more) into data tables ready for downstream analysis and data visualization.

Authors:Christophe Vanderaa [aut, cre], Laurent Gatto [aut]

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scp.pdf |scp.html
scp/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/uclouvain-cbio/scp/issues

Datasets:

On BioConductor:scp-1.15.0(bioc 3.20)scp-1.14.0(bioc 3.19)

bioconductor-package

38 exports 1.31 score 107 dependencies 2 mentions

Last updated 2 months agofrom:b9838a085d

Exports:addReducedDimsaggregateFeaturesOverAssayscomputeSCRcumulativeSensitivityCurvedivideByReferencejaccardIndexmedianCVperCellnormalizeSCPpep2qvaluepredictSensitivityreadSCPreadSCPfromDIANNreadSingleCellExperimentreportMissingValuesscpAnnotateResultsscpComponentAggregatescpComponentAnalysisscpComponentBiplotscpComponentPlotscpDifferentialAggregatescpDifferentialAnalysisscpKeepEffectscpModelComponentMethodsscpModelEffectsscpModelFilterNPRatioscpModelFilterPlotscpModelFilterThresholdscpModelFilterThreshold<-scpModelFormulascpModelInputscpModelNamesscpModelResidualsscpModelWorkflowscpRemoveBatchEffectscpVarianceAggregatescpVarianceAnalysisscpVariancePlotscpVolcanoPlot

Dependencies:abindAnnotationFilteraskpassbase64encBiobaseBiocBaseUtilsBiocGenericsbslibcachemcliclueclustercolorspacecpp11crayoncrosstalkcurldata.tableDelayedArraydigestdplyrevaluatefansifarverfastmapfdrtoolfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttrigraphIHWIRangesisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelpsymphonymagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemetapodmgcvmimeMsCoreUtilsMultiAssayExperimentmunsellnipalsnlmeopensslpillarpkgconfigplotlyplyrpromisesProtGenericspurrrQFeaturesR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownS4ArraysS4VectorssassscalesSingleCellExperimentslamSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviridisLitewithrxfunXVectoryamlzlibbioc

Advanced usage of scp

Rendered fromadvanced.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-08
Started: 2021-07-27

Load Single-Cell Proteomics data using readSCP

Rendered fromread_scp.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-10
Started: 2021-06-21

QFeatures in a nutshell

Rendered fromQFeatures_nutshell.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-08
Started: 2021-07-16

Reporting missing values for Single Cell Proteomics

Rendered fromreporting_missing_values.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-08
Started: 2023-05-22

Single Cell Proteomics data modelling

Rendered fromscp_data_modelling.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-08
Started: 2024-04-02

Single Cell Proteomics data processing and analysis

Rendered fromscp.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-10
Started: 2020-08-18

Readme and manuals

Help Manual

Help pageTopics
Add scplainer Component Analysis ResultsaddReducedDims
Aggregate features over multiple assaysaggregateFeaturesOverAssays
Compute the sample over carrier ratio (SCR)computeSCR
Cumulative sensitivity curvecumulativeSensitivityCurve predictSensitivity
Divide assay columns by a reference columndivideByReference
Compute the pairwise Jaccard indexjaccardIndex
Minimally processed single-cell proteomics data setleduc_minimal
Compute the median coefficient of variation (CV) per cellmedianCVperCell
Example MaxQuant/SCoPE2 outputmqScpData
Normalize single-cell proteomics (SCP) datanormalizeSCP
Compute q-valuespep2qvalue
Read single-cell proteomics tabular datareadSCP readSCPfromDIANN readSingleCellExperiment
Four metrics to report missing valuesreportMissingValues
Single cell sample annotationsampleAnnotation
Single Cell QFeatures datascp1
Annotate single-cell proteomics analysis outputscpAnnotateResults
Class to store the results of single-cell proteomics modellingclass:ScpModel ScpModel ScpModel-class scpModelEffects scpModelFilterNPRatio scpModelFilterThreshold scpModelFilterThreshold<- scpModelFormula scpModelInput scpModelNames scpModelResiduals
Correct single-cell proteomics datascpKeepEffect ScpModel-DataCorrection scpRemoveBatchEffect
Differential abundance analysis for single-cell proteomicsscpDifferentialAggregate scpDifferentialAnalysis ScpModel-DifferentialAnalysis scpVolcanoPlot
Analysis of variance for single-cell proteomicsScpModel-VarianceAnalysis scpVarianceAggregate scpVarianceAnalysis scpVariancePlot
Modelling single-cell proteomics dataScpModel-Workflow scpModelFilterPlot scpModelWorkflow
Component analysis for single cell proteomicsscpComponentAggregate scpComponentAnalysis scpComponentBiplot scpComponentPlot ScpModel-ComponentAnalysis scpModelComponentMethods
Class to store the components of an estimated model for a featureclass:ScpModelFit ScpModelFit ScpModelFit-class