Package: miRLAB 1.37.0

Thuc Duy Le

miRLAB: Dry lab for exploring miRNA-mRNA relationships

Provide tools exploring miRNA-mRNA relationships, including popular miRNA target prediction methods, ensemble methods that integrate individual methods, functions to get data from online resources, functions to validate the results, and functions to conduct enrichment analyses.

Authors:Thuc Duy Le, Junpeng Zhang, Mo Chen, Vu Viet Hoang Pham

miRLAB_1.37.0.tar.gz

miRLAB_1.35.0.tgz(r-4.3-any)
miRLAB_1.37.0.tar.gz(r-4.5-noble)miRLAB_1.37.0.tar.gz(r-4.4-noble)
miRLAB_1.37.0.tgz(r-4.4-emscripten)miRLAB_1.37.0.tgz(r-4.3-emscripten)
miRLAB.pdf |miRLAB.html✨
miRLAB/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/pvvhoang/mirlab/issues

On BioConductor:miRLAB-1.37.0(bioc 3.21)miRLAB-1.36.0(bioc 3.20)

mirnageneexpressionnetworkinferencenetwork

4.72 score 11 scripts 231 downloads 4 mentions 32 exports 187 dependencies

Last updated 2 months agofrom:8fe9ef1be3. Checks:OK: 1 WARNING: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 29 2024
R-4.5-linuxWARNINGNov 29 2024
R-4.3-macWARNINGSep 28 2024

Exports:BordaBordaTopkbRankconvertDcovDiffExpAnalysisElasticexperimentExtopkfilterAndComparegetDataGOBPenrichmentHoeffdingICPPam50IDAidentifymiRTargetsByEnsembleidentifymiRTargetsByICPPam50ImputeNormDataKEGGenrichmentKendallLassoMIPearsonRDCReadReadExtResultreadHeaderSpearmanValidateAllValidationValidationTZscore

Dependencies:abindamapannotateAnnotationDbiAnnotationForgeaskpassbackportsbase64encbdsmatrixBHBiobaseBiocFileCacheBiocGenericsBiocManagerbiomaRtBiostringsbitbit64bitopsblobbootbslibcachemCategorycaToolscheckmateclicliprclueclustercodetoolscolorspacecorpcorcpp11crayonctccurldata.tableDBIdbplyrDelayedArrayDEoptimRdigestdownloaderdplyrenergyentropyevaluatefansifarverfastICAfastmapfilelockfontawesomeforeachforeignFormulafsgenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggmggplot2glmnetglueGO.dbGOstatsgplotsgraphgridExtraGSEABasegslgtablegtoolshighrHmischmshtmlTablehtmltoolshtmlwidgetshttrhttr2igraphimputeinumInvariantCausalPredictionIRangesisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglatticelibcoinlifecyclelimmalmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmboostmemoisemgcvmimemunsellmvtnormnlmennetnnlsopensslorg.Hs.eg.dbpartykitpcalgpillarpkgconfigplogrplyrpngprettyunitsprogresspurrrquadprogR.methodsS3R.ooR.utilsR6rappdirsRBGLRColorBrewerRcppRcppArmadilloRcppEigenRCurlreadrRgraphvizrlangrmarkdownrobustbaserpartRSQLiterstudioapirvestS4ArraysS4VectorssassscalesselectrsfsmiscshapeSparseArraystabsstatmodstringistringrSummarizedExperimentsurvivalsysTCGAbiolinksTCGAbiolinksGUI.datatibbletidyrtidyselecttinytextzdbUCSC.utilsutf8vcdvctrsviridisviridisLitevroomwithrxfunXMLxml2xtableXVectoryamlzlibbioczoo

miRLAB

Thuc Duy Le

Rendered frommiRLAB-vignette.Rmdusingknitr::rmarkdownon Nov 29 2024.

Last update: 2021-10-07
Started: 2015-07-16

Readme and manuals

Help Manual

Help pageTopics
A dry lab for exploring miRNA-mRNA relationshipsmiRLAB-package miRLAB
Ensemble method for miRNA target prediction using Borda count electionBorda
Ensemble method for miRNA target prediction using Borda count election with topk targetsBordaTopk
Extract topk predicted targets of a miRNA Rank all the targets of a miRNA and extract the topk targetsbRank
Convert miRNA symbols from a miRBase version to anotherconvert
miRNA target prediction with the Distance correlation methodDcov
Differentially expressed analysisDiffExpAnalysis
miRNA target prediction with the Elastic-net regression coefficient methodElastic
Function for validate the results from all 12 methods.experiment
Extract top k miRNA-mRNA interactionsExtopk
Filter and compare the validation results from 12 methods Keep the miRNAs that have at least noVal confirmed targets and compare the validation results from all methods.filterAndCompare
getData from GDCgetData
Functional enrichment analysisGOBPenrichment
miRNA target prediction with the Hoeffding correlation coefficient methodHoeffding
Identify miRNA targets by ICP and PAM50ICPPam50
miRNA target prediction with the IDA methodIDA
Identify the top miRNA targets by an ensemble method with ICP-PAM50, Pearson and LassoidentifymiRTargetsByEnsemble
Identify the top miRNA targets by ICP and PAM50identifymiRTargetsByICPPam50
Filter, impute, and normalise data.ImputeNormData
Functional enrichment analysis KEGG enrichment analysis for a gene listKEGGenrichment
miRNA target prediction with the Kendall correlation coefficient methodKendall
miRNA target prediction with the Lasso methodLasso
miRNA target prediction with mutual information methodMI
miRNA target prediction with the Pearson correlation coefficient methodPearson
miRNA target prediction with the Randomized Dependence Coefficient methodRDC
Read dataset from csv fileRead
Read results from other methodsReadExtResult
Read the header of the datasetreadHeader
miRNA target prediction with the Spearman correlation coefficient methodSpearman
Stardarsise the dataset Stadardise the dataset to have mean=0 and std=1 in each column.Standardise
Validate the targets of all miRNA using both experimentally confirmed and transfection dataValidateAll
Validate the targets of a miRNAValidation
Validate the targets of a miRNA using transfection dataValidationT
miRNA target prediction with the Z-score methodZscore