Package: PrInCE 1.23.0

Michael Skinnider

PrInCE: Predicting Interactomes from Co-Elution

PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.

Authors:Michael Skinnider [aut, trl, cre], R. Greg Stacey [ctb], Nichollas Scott [ctb], Anders Kristensen [ctb], Leonard Foster [aut, led]

PrInCE_1.23.0.tar.gz
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PrInCE.pdf |PrInCE.html✨
PrInCE/json (API)

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

Peer review:

Bug tracker:https://github.com/fosterlab/prince/issues

Datasets:

On BioConductor:PrInCE-1.23.0(bioc 3.21)PrInCE-1.22.0(bioc 3.20)

proteomicssystemsbiologynetworkinference

6.38 score 8 stars 25 scripts 168 downloads 6 mentions 29 exports 165 dependencies

Last updated 23 days agofrom:92c3d03087. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-winWARNINGNov 04 2024
R-4.5-linuxWARNINGNov 04 2024
R-4.4-winWARNINGNov 04 2024
R-4.4-macWARNINGNov 04 2024
R-4.3-winWARNINGNov 04 2024
R-4.3-macWARNINGNov 04 2024

Exports:adjacency_matrix_from_data_frameadjacency_matrix_from_listbuild_gaussianscalculate_autocorrelationcalculate_featurescalculate_precisioncheck_gaussianschoose_gaussiansclean_profileclean_profilesco_apexconcatenate_featuresdetect_complexesfilter_profilesfit_curvefit_gaussiansimpute_neighborsis_unweightedis_weightedmake_feature_from_data_framemake_feature_from_expressionmake_initial_conditionsmake_labelsmatch_matrix_dimensionspredict_ensemblepredict_interactionsPrInCEreplace_missing_datathreshold_precision

Dependencies:abindaffyaffyioAnnotationFilteraskpassbackportsbase64encBHbiglmBiobaseBiocBaseUtilsBiocGenericsBiocManagerBiocParallelbslibcachemcheckmatecliclueclustercodetoolscolorspacecpp11crayoncrosstalkcurldata.tableDBIDelayedArrayDEoptimRdigestdoParalleldplyrevaluatefansifarverfastmapfontawesomeforeachforecastforeignformatRFormulafracdifffsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegridExtragtablehighrHmischmshtmlTablehtmltoolshtmlwidgetshttrigraphimputeIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglambda.rlaterlatticelazyevalLiblineaRlifecyclelimmalmtestmagrittrMALDIquantMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeMsCoreUtilsMSnbaseMultiAssayExperimentmunsellmzIDmzRnaivebayesncdf4nlmennetopensslpcaMethodspillarpkgconfigplotlyplyrpreprocessCoreprettyunitsprogresspromisesProtGenericsPSMatchpurrrQFeaturesquadprogquantmodR6rangerrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreshape2Rhdf5librlangrmarkdownrobustbaserpartrstudioapiS4ArraysS4VectorssassscalessnowSparseArrayspeedglmstatmodstringistringrSummarizedExperimentsystestertibbletidyrtidyselecttimeDatetinytextseriesTTRUCSC.utilsurcautf8vctrsviridisviridisLitevsnwithrxfunXMLxtsXVectoryamlzlibbioczoo

Interactome reconstruction from co-elution data with PrInCE

Michael Skinnider

Rendered fromintro-to-prince.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2019-03-12
Started: 2018-12-18

Readme and manuals

Help Manual

Help pageTopics
Create an adjacency matrix from a data frameadjacency_matrix_from_data_frame
Create an adjacency matrix from a list of complexesadjacency_matrix_from_list
Model selection for Gaussian mixture modelsaic gaussian_aic gaussian_aicc gaussian_bic
Deconvolve profiles into Gaussian mixture modelsbuild_gaussians
Calculate the autocorrelation for each protein between a pair of co-elution experiments.calculate_autocorrelation
Calculate the default features used to predict interactions in PrInCEcalculate_features
Calculate precision at each point in a sequencecalculate_precision
Check the format of a list of Gaussianscheck_gaussians
Fit a Gaussian mixture model to a co-elution profilechoose_gaussians
Preprocess a co-elution profileclean_profile
Preprocess a co-elution profile matrixclean_profiles
Calculate the co-apex score for every protein pairco_apex
Combine features across multiple replicatesconcatenate_features
Detect significantly interacting complexes in a chromatogram matrixdetect_complexes
Filter a co-elution profile matrixfilter_profiles
Output the fit curve for a given mixture of Gaussiansfit_curve
Fit a mixture of Gaussians to a chromatogram curvefit_gaussians
Reference set of human protein complexesgold_standard
Impute single missing valuesimpute_neighbors
Test whether a network is unweightedis_unweighted
Test whether a network is weightedis_weighted
Interactome of HeLa cellskristensen
Fitted Gaussian mixture models for the 'kristensen' datasetkristensen_gaussians
Create a feature vector for a classifier from a data framemake_feature_from_data_frame
Create a feature vector from expression datamake_feature_from_expression
Make initial conditions for curve fitting with a mixture of Gaussiansmake_initial_conditions
Make labels for a classifier based on a gold standardmake_labels
Match the dimensions of a query matrix to a profile matrixmatch_matrix_dimensions
Predict interactions using an ensemble of classifierspredict_ensemble
Predict interactions given a set of features and examplespredict_interactions
PrInCE: Prediction of Interactomes from Co-ElutionPrInCE
Replace missing data with median ± random noisereplace_missing_data
Cytoplasmic interactome of Jurkat T cells during apoptosisscott
Fitted Gaussian mixture models for the 'scott' datasetscott_gaussians
Threshold interactions at a given precision cutoffthreshold_precision