Package: scp 1.17.0
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:
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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')) |
Bug tracker:https://github.com/uclouvain-cbio/scp/issues
- leduc_minimal - Minimally processed single-cell proteomics data set
- mqScpData - Example MaxQuant/SCoPE2 output
- sampleAnnotation - Single cell sample annotation
- scp1 - Single Cell QFeatures data
On BioConductor:scp-1.17.0(bioc 3.21)scp-1.16.0(bioc 3.20)
geneexpressionproteomicssinglecellmassspectrometrypreprocessingcellbasedassaysbioconductormass-spectrometrysingle-cellsoftware
Last updated 23 days agofrom:aa22264da7. Checks:OK: 1 ERROR: 4 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | NOTE | Oct 31 2024 |
| R-4.5-linux | ERROR | Oct 31 2024 |
| R-4.4-win | NOTE | Oct 31 2024 |
| R-4.4-mac | ERROR | Oct 31 2024 |
| R-4.3-win | ERROR | Oct 31 2024 |
| R-4.3-mac | ERROR | Oct 31 2024 |
Exports:addReducedDimsaggregateFeaturesOverAssayscomputeSCRcumulativeSensitivityCurvedivideByReferencejaccardIndexmedianCVperCellnormalizeSCPpep2qvaluepredictSensitivityreadSCPreadSCPfromDIANNreadSingleCellExperimentreportMissingValuesscpAnnotateResultsscpComponentAggregatescpComponentAnalysisscpComponentBiplotscpComponentPlotscpDifferentialAggregatescpDifferentialAnalysisscpKeepEffectscpModelComponentMethodsscpModelEffectsscpModelFilterNPRatioscpModelFilterPlotscpModelFilterThresholdscpModelFilterThreshold<-scpModelFormulascpModelInputscpModelNamesscpModelResidualsscpModelWorkflowscpRemoveBatchEffectscpVarianceAggregatescpVarianceAnalysisscpVariancePlotscpVolcanoPlot
Dependencies:abindAnnotationFilteraskpassbase64encBiobaseBiocBaseUtilsBiocGenericsbslibcachemcliclueclustercolorspacecpp11crayoncrosstalkcurldata.tableDelayedArraydigestdplyrevaluatefansifarverfastmapfdrtoolfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttrigraphIHWIRangesisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelpsymphonymagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemetapodmgcvmimeMsCoreUtilsMultiAssayExperimentmunsellnipalsnlmeopensslpillarpkgconfigplotlyplyrpromisesProtGenericspurrrQFeaturesR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownS4ArraysS4VectorssassscalesSingleCellExperimentslamSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviridisLitewithrxfunXVectoryamlzlibbioc
Advanced usage of scp
Rendered fromadvanced.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-04-08
Started: 2021-07-27
Load Single-Cell Proteomics data using readSCP
Rendered fromread_scp.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-04-10
Started: 2021-06-21
QFeatures in a nutshell
Rendered fromQFeatures_nutshell.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-04-08
Started: 2021-07-16
Reporting missing values for Single Cell Proteomics
Rendered fromreporting_missing_values.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-04-08
Started: 2023-05-22
Single Cell Proteomics data modelling
Rendered fromscp_data_modelling.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-10-03
Started: 2024-04-02
Single Cell Proteomics data processing and analysis
Rendered fromscp.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2024-04-10
Started: 2020-08-18
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Add scplainer Component Analysis Results | addReducedDims |
| Aggregate features over multiple assays | aggregateFeaturesOverAssays |
| Compute the sample over carrier ratio (SCR) | computeSCR |
| Cumulative sensitivity curve | cumulativeSensitivityCurve predictSensitivity |
| Divide assay columns by a reference column | divideByReference |
| Compute the pairwise Jaccard index | jaccardIndex |
| Minimally processed single-cell proteomics data set | leduc_minimal |
| Compute the median coefficient of variation (CV) per cell | medianCVperCell |
| Example MaxQuant/SCoPE2 output | mqScpData |
| Normalize single-cell proteomics (SCP) data | normalizeSCP |
| Compute q-values | pep2qvalue |
| Read single-cell proteomics tabular data | readSCP readSCPfromDIANN readSingleCellExperiment |
| Four metrics to report missing values | reportMissingValues |
| Single cell sample annotation | sampleAnnotation |
| Single Cell QFeatures data | scp1 |
| Annotate single-cell proteomics analysis output | scpAnnotateResults |
| Class to store the results of single-cell proteomics modelling | class:ScpModel ScpModel ScpModel-class scpModelEffects scpModelFilterNPRatio scpModelFilterThreshold scpModelFilterThreshold<- scpModelFormula scpModelInput scpModelNames scpModelResiduals |
| Correct single-cell proteomics data | scpKeepEffect ScpModel-DataCorrection scpRemoveBatchEffect |
| Differential abundance analysis for single-cell proteomics | scpDifferentialAggregate scpDifferentialAnalysis ScpModel-DifferentialAnalysis scpVolcanoPlot |
| Analysis of variance for single-cell proteomics | ScpModel-VarianceAnalysis scpVarianceAggregate scpVarianceAnalysis scpVariancePlot |
| Modelling single-cell proteomics data | ScpModel-Workflow scpModelFilterPlot scpModelWorkflow |
| Component analysis for single cell proteomics | scpComponentAggregate scpComponentAnalysis scpComponentBiplot scpComponentPlot ScpModel-ComponentAnalysis scpModelComponentMethods |
| Class to store the components of an estimated model for a feature | class:ScpModelFit ScpModelFit ScpModelFit-class |