Package: geva 1.15.0

Itamar José Guimarães Nunes

geva: Gene Expression Variation Analysis (GEVA)

Statistic methods to evaluate variations of differential expression (DE) between multiple biological conditions. It takes into account the fold-changes and p-values from previous differential expression (DE) results that use large-scale data (*e.g.*, microarray and RNA-seq) and evaluates which genes would react in response to the distinct experiments. This evaluation involves an unique pipeline of statistical methods, including weighted summarization, quantile detection, cluster analysis, and ANOVA tests, in order to classify a subset of relevant genes whose DE is similar or dependent to certain biological factors.

Authors:Itamar José Guimarães Nunes [aut, cre], Murilo Zanini David [ctb], Bruno César Feltes [ctb], Marcio Dorn [ctb]

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NEWS

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

Peer review:

Bug tracker:https://github.com/sbcblab/geva/issues

On BioConductor:geva-1.13.0(bioc 3.20)geva-1.12.0(bioc 3.19)

classificationdifferentialexpressiongeneexpressionmicroarraymultiplecomparisonrnaseqsystemsbiologytranscriptomics

4.30 score 2 stars 4 scripts 132 downloads 66 exports 5 dependencies

Last updated 23 days agofrom:d89cefb62a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winOKOct 30 2024
R-4.5-linuxOKOct 30 2024
R-4.4-winOKOct 30 2024
R-4.4-macOKOct 30 2024
R-4.3-winOKOct 30 2024
R-4.3-macOKOct 30 2024

Exports:analysis.paramsas.SVTablecentroidsclassification.tableclassification.table<-cluster.methodelem.classelem.class<-factorsfactors<-featureTablefeatureTable<-get.distance.methodget.summary.methodget.variation.methodgeva.clustergeva.dclustergeva.finalizegeva.hclustergeva.ideal.examplegeva.input.correctgeva.input.filtergeva.input.rename.rowsgeva.merge.inputgeva.quantilesgeva.quickgeva.read.tablesgeva.summarizegroup.relsgroupsgroupsetsgroupsets<-infolistinfolist<-inputdatainputnamesinputvaluesinputweightsoffsetsoptions.cl.score.methodoptions.cluster.methodoptions.dcluster.methodoptions.distanceoptions.factoring.p.adjustoptions.hc.methodoptions.hc.metricoptions.quantilesoptions.summaryoptions.variationplotqareasizesqcountqindexesquantilesquantiles.methodresults.tablescoresshowsvsv.datasv.scoressvattrsvtabletop.genestyped.listvariation

Dependencies:dbscanfastclustergenericsmatrixStatsRcpp

Gene Expression Variation Analysis (GEVA)

Itamar José Guimarães Nunes^[Structural Bioinformatics and Computational Lab (SBCB) -- Federal University of Rio Grande do Sul (UFRGS)], Murilo Zanini David^[Graduate Program in Ecology -- Federal University of Rio Grande do Sul (UFRGS)], \linebreak, Bruno César Feltes\footnotemark[1], and Marcio Dorn\footnotemark[1]

Rendered fromgeva.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2021-03-10
Started: 2021-01-20

Readme and manuals

Help Manual

Help pageTopics
GEVA Generic Methodsanalysis.params as.SVTable centroids classification.table classification.table<- cluster.method elem.class elem.class<- factors factors<- featureTable featureTable<- generics get.distance.method get.summary.method get.variation.method group.rels groups groupsets groupsets<- infolist infolist<- inputdata inputnames inputvalues inputweights offsets qareasizes qcount qindexes quantiles quantiles.method results.table scores sv sv.data sv.scores svattr variation
GEVA Cluster Analysisgeva.cluster options.cl.score.method options.cluster.method options.distance
GEVA Density Clusteringgeva.dcluster options.dcluster.method
Concatenating GEVA calculations into the final resultsgeva.finalize options.factoring.p.adjust
GEVA Hierarchical Clusteringgeva.hcluster options.hc.method options.hc.metric
GEVA ``Ideal'' Example for Package Testinggeva.ideal.example
GEVA Input Post-processinggeva.input.correct geva.input.filter geva.input.rename.rows
GEVA Input Processing and Mergegeva.merge.input geva.read.tables
GEVA Quantiles Detectiongeva.quantiles options.quantiles
All-In-One Function for GEVA Intermediate Proceduresgeva.quick
Summarizes the GEVAInputgeva.summarize options.summary options.variation
GEVA Clustering Resultscluster.method,GEVACluster-method GEVACluster-class lines.GEVACluster plot,GEVACluster,SVTable-method show,GEVACluster-method
GEVA Grouped Summary-Variation Tableanalysis.params,GEVAGroupedSummary-method as.expression.GEVAGroupedSummary as.matrix.GEVAGroupedSummary cluster.method,GEVAGroupedSummary-method GEVAGroupedSummary-class groupsets,GEVAGroupedSummary-method groupsets<-,GEVAGroupedSummary,GEVAGroupSet-method lines.GEVAGroupedSummary plot,GEVAGroupedSummary,missing-method points.GEVAGroupedSummary quantiles,GEVAGroupedSummary-method show,GEVAGroupedSummary-method
GEVA Grouping Resultsanalysis.params,GEVAGroupSet-method as.data.frame.GEVAGroupSet as.expression.GEVAGroupSet as.SVTable.GEVAGroupSet centroids,GEVAGroupSet-method classification.table,GEVAGroupSet-method classification.table<-,GEVAGroupSet,data.frame-method cluster.method,GEVAGroupSet-method color.values.GEVAGroupSet featureTable,GEVAGroupSet-method GEVAGroupSet-class groups,GEVAGroupSet-method infolist,GEVAGroupSet,character-method infolist,GEVAGroupSet,missing-method infolist<-,GEVAGroupSet,list-method length,GEVAGroupSet-method levels.GEVAGroupSet names,GEVAGroupSet-method offsets,GEVAGroupSet-method plot,GEVAGroupSet,GEVAGroupSet-method plot,GEVAGroupSet,missing-method plot,GEVAGroupSet,SVTable-method plot,SVTable,GEVAGroupSet-method points.GEVAGroupSet scores,GEVAGroupSet,character-method scores,GEVAGroupSet,missing-method show,GEVAGroupSet-method sv,GEVAGroupSet-method sv.data,GEVAGroupSet-method
GEVA Input Dataanalysis.params,GEVAInput-method as.array.GEVAInput dim,GEVAInput-method dimnames,GEVAInput-method dimnames<-,GEVAInput,list-method factors,GEVAInput-method factors<-,GEVAInput,character-method factors<-,GEVAInput,factor-method featureTable,GEVAInput-method featureTable<-,GEVAInput,data.frame-method GEVAInput-class head.GEVAInput infolist,GEVAInput,character-method infolist,GEVAInput,missing-method infolist<-,GEVAInput,list-method inputdata,GEVAInput-method inputnames,GEVAInput-method inputvalues,GEVAInput-method inputweights,GEVAInput,logical-method inputweights,GEVAInput,missing-method length,GEVAInput-method levels.GEVAInput names,GEVAInput-method plot,GEVAInput,missing-method show,GEVAInput-method tail.GEVAInput [,GEVAInput,ANY,ANY,ANY-method
GEVA Quantiles Grouping Resultsas.expression.GEVAQuantiles as.SVTable.GEVAQuantiles classification.table,GEVAQuantiles-method classification.table<-,GEVAQuantiles,data.frame-method cluster.method,GEVAQuantiles-method dim,GEVAQuantiles-method GEVAQuantiles-class lines.GEVAQuantiles plot,GEVAQuantiles,SVTable-method qareasizes,GEVAQuantiles-method qcount,GEVAQuantiles-method qindexes,GEVAQuantiles-method quantiles,GEVAQuantiles-method quantiles.method,GEVAQuantiles-method show,GEVAQuantiles-method sv.scores,GEVAQuantiles-method [,GEVAQuantiles,ANY,ANY,ANY-method
GEVA Adjusted Quantiles ResultsGEVAQuantilesAdjusted-class group.rels,GEVAQuantilesAdjusted-method show,GEVAQuantilesAdjusted-method
GEVA Results Table$,GEVAResults-method analysis.params,GEVAResults-method as.expression.GEVAResults dim,GEVAResults-method dimnames,GEVAResults-method featureTable,GEVAResults-method GEVAResults-class head.GEVAResults infolist,GEVAResults,character-method infolist,GEVAResults,missing-method inputdata,GEVAResults-method inputvalues,GEVAResults-method inputweights,GEVAResults,logical-method inputweights,GEVAResults,missing-method length,GEVAResults-method levels.GEVAResults names,GEVAResults-method plot,GEVAResults,missing-method points.GEVAResults quantiles,GEVAResults-method results.table,GEVAResults-method show,GEVAResults-method sv,GEVAResults-method sv.data,GEVAResults-method [,GEVAResults,ANY,ANY,ANY-method
GEVA Summary-Variation Tableanalysis.params,GEVASummary-method as.expression.GEVASummary as.matrix.GEVASummary factors,GEVASummary-method factors<-,GEVASummary,character-method factors<-,GEVASummary,factor-method featureTable,GEVASummary-method get.summary.method.GEVASummary get.variation.method.GEVASummary GEVASummary-class groupsets,GEVASummary-method groupsets<-,GEVASummary,GEVAGroupSet-method groupsets<-,GEVASummary,TypedList-method infolist,GEVASummary,missing-method infolist<-,GEVASummary,list-method inputdata,GEVASummary-method inputnames,GEVASummary-method inputvalues,GEVASummary-method inputweights,GEVASummary,logical-method inputweights,GEVASummary,missing-method plot,GEVASummary,missing-method quantiles,GEVASummary-method show,GEVASummary-method
Summary-Variation Attribute Field$,SVAttribute-method as.character.SVAttribute as.vector.SVAttribute dim,SVAttribute-method names,SVAttribute-method show,SVAttribute-method summary.SVAttribute sv,SVAttribute-method sv.data,SVAttribute-method svattr,character,character-method svattr,integer,integer-method svattr,numeric,numeric-method SVAttribute SVAttribute-class SVChrAttribute SVChrAttribute-class SVIntAttribute SVIntAttribute-class SVNumAttribute SVNumAttribute-class variation.SVAttribute [,SVAttribute,ANY,ANY,ANY-method
Summary-Variation Table$,SVTable-method as.data.frame.SVTable as.matrix.SVTable as.SVTable.data.frame as.SVTable.matrix as.SVTable.SVTable dim,SVTable-method dimnames,SVTable-method format.SVTable head.SVTable is.na.SVTable length,SVTable-method names,SVTable-method plot,SVTable,missing-method points.SVTable show,SVTable-method summary.SVTable sv,SVTable-method sv.data,SVTable-method SVTable svtable SVTable-class tail.SVTable variation.SVTable with.SVTable [,SVTable,ANY,ANY,ANY-method
Top Results from GEVAtop.genes
Type-strict List (TypedList-class)as.list.TypedList as.typed.list.list as.typed.list.TypedList as.typed.list.vector elem.class,TypedList-method elem.class<-,TypedList,character-method show,TypedList-method typed.list TypedList-class [,TypedList,ANY,missing,missing-method [<-,TypedList,character,missing-method