Package: xcore 1.9.0

Maciej Migdał

xcore: xcore expression regulators inference

xcore is an R package for transcription factor activity modeling based on known molecular signatures and user's gene expression data. Accompanying xcoredata package provides a collection of molecular signatures, constructed from publicly available ChiP-seq experiments. xcore use ridge regression to model changes in expression as a linear combination of molecular signatures and find their unknown activities. Obtained, estimates can be further tested for significance to select molecular signatures with the highest predicted effect on the observed expression changes.

Authors:Maciej Migdał [aut, cre], Bogumił Kaczkowski [aut]

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xcore.pdf |xcore.html✨
xcore/json (API)

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

Peer review:

Datasets:

On BioConductor:xcore-1.9.0(bioc 3.20)xcore-1.8.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

9 exports 0.61 score 62 dependencies

Last updated 2 months agofrom:e1f2e826f1

Exports:%>%addSignaturesfilterSignaturesgetCoveragegetInteractionMatrixmodelGeneExpressionprepareCountsForRegressionregressionDatatranslateCounts

Dependencies:abindaskpassBiobaseBiocBaseUtilsBiocGenericsclicodetoolscpp11crayoncurlDelayedArraydplyredgeRfansiforeachgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesglmnetgluehttrIRangesiteratorsjsonlitelatticelifecyclelimmalocfitmagrittrMatrixMatrixGenericsmatrixStatsmimeMultiAssayExperimentopensslpillarpkgconfigpurrrR6RcppRcppEigenrlangS4ArraysS4VectorsshapeSparseArraystatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselectUCSC.utilsutf8vctrswithrXVectorzlibbioc

xcore vignette

migdal

Rendered fromxcore_vignette.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2022-09-14
Started: 2021-12-07

Readme and manuals

Help Manual

Help pageTopics
re-export magrittr pipe operator%>%
Add molecular signatures to MultiAssayExperimentaddSignatures
Apply function over groups of columnsapplyOverColumnGroups
Apply function over selected column in list of data framesapplyOverDFList
Transform design matrix to factordesign2factor
Estimate linear models goodness of fit statisticestimateStat
Filter signatures by coveragefilterSignatures
Combine p-values using Fisher methodfisherMethod
Calculate regions coveragegetCoverage
Compute interaction matrixgetInteractionMatrix
Calculate variance weighted average coefficients matrixgetVarianceWeightedAvgCoeff
Check if argument is a binary flagisTRUEorFALSE
Calculate Mean Absolute Errormae
Helper summarizing MAE objectmaeSummary
Gene expression modeling pipelinemodelGeneExpression
Ridge regression wrapper for modelGeneExpressionmodelGeneExpression_ridge_regression_wraper
Statistical testing of ridge regression estimates wrapper for modelGeneExpressionmodelGeneExpression_significance_testing_wraper
Calculate Mean Squared Errormse
Process count matrix for expression modelingprepareCountsForRegression
Create MultiAssayExperiment object for expression modelingregressionData
xcore example molecular signaturesremap_mini
Calculate replicate variance weighted averaged Z-scoresrepVarianceWeightedAvgZscore
Significance testing in linear ridge regressionridgePvals
xcore example expression datarinderpest_mini
Calculate $R^2$rsq
Simplify Interaction MatrixsimplifyInteractionMatrix
Combine Z-scores using Stouffer's methodstoufferZMethod
Subset keeping missingsubsetWithMissing
Translate counts matrix rownamestranslateCounts