## ----styleSweave, eval=TRUE, echo=FALSE, results="asis"-------------------- BiocStyle::latex(use.unsrturl=FALSE) ## ----include=FALSE--------------------------------------------------------- library(knitr) opts_chunk$set( concordance=TRUE ) ## ----options, echo=FALSE--------------------------------------------------- options(prompt=" ", continue=" ") ## ----CranPck, eval=TRUE, echo=TRUE----------------------------------------- Cran.pck <- c("reshape2", "ggplot2", "ggrepel", "ggalluvial", "FactoMineR", "factoextra", "plot3D", "plot3Drgl", "ggplotify", "UpSetR", "gprofiler2") ## ----installCranPck, eval=FALSE, echo=TRUE--------------------------------- # Select.package.CRAN <- "FactoMineR" # if (!require(package=Select.package.CRAN, # quietly=TRUE, character.only=TRUE, warn.conflicts=FALSE)) { # install.packages(pkgs=Select.package.CRAN, dependencies=TRUE) # }# if(!require(package=Cran.pck[i], quietly=TRUE, character.only=TRUE)) ## ----BioconductorPck, eval=TRUE, echo=TRUE--------------------------------- Bioconductor.pck <- c("SummarizedExperiment", "S4Vectors", "DESeq2", "Mfuzz", "ComplexHeatmap") ## ----BiocManagerPck, eval=FALSE, echo=TRUE--------------------------------- # if (!require(package="BiocManager", # quietly=TRUE, character.only=TRUE, warn.conflicts=FALSE)) { # install.packages("BiocManager") # }# if(!require(package="BiocManager", quietly=TRUE, character.only=TRUE)) ## ----BiocconductorVersion, eval=FALSE, echo=TRUE--------------------------- # BiocManager::install(version="3.18") ## ----installBioconductorpck, eval=FALSE, echo=TRUE------------------------- # Select.package.Bioc <- "DESeq2" # if(!require(package=Select.package.Bioc, # quietly=TRUE, character.only=TRUE, warn.conflicts=FALSE)){ # BiocManager::install(pkgs=Select.package.Bioc) # }## if(!require(package=Select.package.Bioc, quietly=TRUE, character.only=TRUE)) ## ----library, eval=TRUE, echo=TRUE----------------------------------------- library(MultiRNAflow) ## ----LoadMus1, echo=TRUE, eval=TRUE---------------------------------------- data("RawCounts_Antoszewski2022_MOUSEsub500") ## ----LoadFission, echo=TRUE, eval=TRUE------------------------------------- data("RawCounts_Leong2014_FISSIONsub500wt") ## ----LoadLeuk, echo=TRUE, eval=TRUE---------------------------------------- data("RawCounts_Schleiss2021_CLLsub500") ## ----LoadMus2, echo=TRUE, eval=TRUE---------------------------------------- data("RawCounts_Weger2021_MOUSEsub500") ## ----ColnamesExample, echo=TRUE, eval=TRUE--------------------------------- data("RawCounts_Leong2014_FISSIONsub500wt") colnames(RawCounts_Leong2014_FISSIONsub500wt) ## ----ExampleParametersData, echo=FALSE, eval=TRUE-------------------------- data("RawCounts_Leong2014_FISSIONsub500wt") ## ----ExampleParameters, echo=TRUE, eval=TRUE------------------------------- resSEexample <- DATAprepSE(RawCounts=RawCounts_Leong2014_FISSIONsub500wt, Column.gene=1, Group.position=NULL, Time.position=2, Individual.position=3) ## ----DATAprepSEleuk, eval=TRUE--------------------------------------------- SEresleuk500 <- DATAprepSE(RawCounts=RawCounts_Schleiss2021_CLLsub500, Column.gene=1, Group.position=2, Time.position=4, Individual.position=3, VARfilter=0, SUMfilter=0, RNAlength=NULL) ## ----DATAprepSEleuk_res, eval=TRUE----------------------------------------- names(S4Vectors::metadata(SEresleuk500)) str(S4Vectors::metadata(SEresleuk500)$Results) ## ----NormalizationLeukemia, eval=TRUE-------------------------------------- SEresNORMleuk500 <- DATAnormalization(SEres=SEresleuk500, Normalization="vst", Blind.rlog.vst=FALSE, Plot.Boxplot=FALSE, Colored.By.Factors=TRUE, Color.Group=NULL, path.result=NULL) ## ----NormalizationLeukemia_res, eval=TRUE---------------------------------- ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresNORMleuk500)$Results ## Save the results of Normalization in an object resNORMleuk500 <- resleuk500[[1]][[1]] ### names(S4Vectors::metadata(SEresNORMleuk500)) str(resleuk500, max.level=3) ## ----NormalizationLeukemia_metadata, eval=TRUE----------------------------- resNORMleuk500$normMethod print(resNORMleuk500$normBoxplot) ## ----NormalizationLeukemia_data, eval=TRUE--------------------------------- normData <- SummarizedExperiment::assays(SEresNORMleuk500) names(SummarizedExperiment::assays(SEresNORMleuk500)) ## ----NormalizationCLLcolor, eval=TRUE-------------------------------------- colorLeuk <- data.frame(Name=c("NP", "P"), Col=c("black", "red")) ## ----PCALeukemia, warning=FALSE, message=FALSE, eval=TRUE------------------ SEresPCALeuk500 <- PCAanalysis(SEresNorm=SEresNORMleuk500, gene.deletion=NULL, sample.deletion=NULL, Plot.PCA=FALSE, Mean.Accross.Time=FALSE, Color.Group=NULL, Cex.label=0.9, Cex.point=0.8, epsilon=0.2, Phi=25, Theta=140, motion3D=FALSE, path.result=NULL, Name.folder.pca=NULL) ## ----PCALeukemia_res, warning=FALSE, message=FALSE, eval=TRUE-------------- ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresPCALeuk500)$Results ## Save the results of normalization in an object resPCALeuk500 <- resleuk500[[1]][[2]] ### names(S4Vectors::metadata(SEresPCALeuk500)) str(resleuk500, max.level=3, give.attr=FALSE) names(resPCALeuk500) ## ----NormalizationLeukemia_PCA2d_temporalLinks, eval=TRUE------------------ print(resPCALeuk500$PCA_2DtemporalLinks) ## ----NormalizationLeukemia_PCA3d_temporalLinks, eval=TRUE------------------ print(resPCALeuk500$PCA_3DtemporalLinks) ## ----NormalizationLeukemia_PCA3d_temporalLinks_P, eval=TRUE---------------- print(resPCALeuk500$PCA_BiologicalCondition_P$PCA_3DtemporalLinks) ## ----PCAleukColor, warning=FALSE, message=FALSE, eval=TRUE----------------- colorLeuk <- data.frame(Name=c("NP","P"), Col=c("black","red")) ## ----HCPCleukemia, warning=FALSE, message=FALSE, eval=TRUE----------------- SEresHCPCLeuk500 <- HCPCanalysis(SEresNorm=SEresPCALeuk500, gene.deletion=NULL, sample.deletion=NULL, Plot.HCPC=FALSE, Phi=25,Theta=140, Cex.point=0.7, epsilon=0.2, Cex.label=0.9, motion3D=FALSE, path.result=NULL, Name.folder.hcpc=NULL) ## ----HCPCleukemia_res, warning=FALSE, message=FALSE, eval=TRUE------------- ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresHCPCLeuk500)$Results ## Save the results of HCPC in an object resHCPCLeuk500 <- resleuk500[[1]][[3]] ### names(S4Vectors::metadata(SEresHCPCLeuk500)) str(resleuk500, max.level=3, give.attr=FALSE) names(resHCPCLeuk500) ## ----NormalizationLeukemia_Dendrogram, eval=TRUE--------------------------- print(resHCPCLeuk500$Dendrogram) ## ----NormalizationLeukemia_SampleDistribution, eval=TRUE------------------- print(resHCPCLeuk500$Cluster_SampleDistribution) ## ----NormalizationLeukemia_PCA3d_HCPC, eval=TRUE--------------------------- print(resHCPCLeuk500$PCA3DclustersHCPC) ## ----MfuzzLeuk, warning=FALSE, message=FALSE, eval=TRUE-------------------- SEresMfuzzLeuk500 <- MFUZZanalysis(SEresNorm=SEresHCPCLeuk500, DataNumberCluster=NULL, Method="hcpc", Membership=0.7, Min.std=0.1, Plot.Mfuzz=FALSE, path.result=NULL, Name.folder.mfuzz=NULL) ## ----MFUZZleukemia_res, warning=FALSE, message=FALSE, eval=TRUE------------ ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresMfuzzLeuk500)$Results ## Save the results of Mfuzz in an object resMfuzzLeuk500 <- resleuk500[[1]][[4]] ### names(S4Vectors::metadata(SEresMfuzzLeuk500)) str(resleuk500, max.level=3, give.attr=FALSE) names(resMfuzzLeuk500) ## ----MfuzzLeukemia_ClusterPlot, eval=TRUE---------------------------------- print(resMfuzzLeuk500$ClustersNumbers) ## ----MfuzzLeukemia_Mfuzz_P, eval=TRUE-------------------------------------- print(resMfuzzLeuk500$Mfuzz.Plots.Group_P) ## ----DATAplotExpressionGenesLeukemia, warning=FALSE, message=FALSE, eval=TRUE---- SEresEVOleuk500 <- DATAplotExpressionGenes(SEresNorm=SEresMfuzzLeuk500, Vector.row.gene=c(25, 30), Color.Group=NULL, Plot.Expression=FALSE, path.result=NULL, Name.folder.profile=NULL) ## ----DEleukemia_res, warning=FALSE, message=FALSE, eval=TRUE--------------- ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresEVOleuk500)$Results ## Save the results of DE analysis in an object resEVOleuk500 <- resleuk500[[1]][[5]] ### names(S4Vectors::metadata(SEresEVOleuk500)) str(resleuk500, max.level=3, give.attr=FALSE) names(resEVOleuk500) ## ----MfuzzLeukemia_Profile1gene, eval=TRUE--------------------------------- print(resEVOleuk500$ARL4C_profile) ## ----ProfileCLLcolor, warning=FALSE, message=FALSE, eval=TRUE-------------- colorLeuk <- data.frame(Name=c("NP", "P"), Col=c("black", "red")) ## ----DELeuk, warning=FALSE, message=FALSE, eval=TRUE----------------------- SEresDELeuk500 <- DEanalysisGlobal(SEres=SEresEVOleuk500, pval.min=0.05, pval.vect.t=NULL, log.FC.min=1, LRT.supp.info=FALSE, Plot.DE.graph=FALSE, path.result=NULL, Name.folder.DE=NULL) ## data("Results_DEanalysis_sub500") ## SEresDELeuk500 <- Results_DEanalysis_sub500$DE_Schleiss2021_CLLsub500 ## ----DEresultsLeukemia, warning=FALSE, message=FALSE, eval=TRUE------------ DEsummaryLeuk <- SummarizedExperiment::rowData(SEresDELeuk500) ## ----GlossaryLeukemia, warning=FALSE, message=FALSE, eval=TRUE------------- resDELeuk500 <- S4Vectors::metadata(SEresDELeuk500)$Results[[2]][[2]] resGlossaryLeuk <- resDELeuk500$Glossary ## ----DEleukAlluvium, warning=FALSE, message=FALSE, eval=TRUE--------------- print(resDELeuk500$DEplots_TimePerGroup$Alluvial.graph.Group_P) ## ----DEleukLineTemporalGroup, warning=FALSE, message=FALSE, eval=TRUE------ print(resDELeuk500$DEplots_TimePerGroup$NumberDEgenes.acrossTime.perTemporalGroup.Group_P) ## ----DEleukUpDownBarplot, warning=FALSE, message=FALSE, eval=TRUE---------- print(resDELeuk500$DEplots_TimePerGroup$NumberDEgenes_UpDownRegulated_perTimeperGroup) ## ----DEleukVennBarplot, warning=FALSE, message=FALSE, eval=TRUE------------ print(resDELeuk500$DEplots_TimePerGroup$VennBarplot.withNumberUpRegulated.Group_P) ## ----DEleukAlluvium1tmin, warning=FALSE, message=FALSE, eval=TRUE---------- print(resDELeuk500$DEplots_TimePerGroup$AlluvialGraph_DE.1tmin_perGroup) ## ----DEleukSpecificBarplot, warning=FALSE, message=FALSE, eval=TRUE-------- print(resDELeuk500$DEplots_GroupPerTime$NumberSpecificGenes_UpDownRegulated_perBiologicalCondition) ## ----DEleukSignatureBarplot, warning=FALSE, message=FALSE, eval=TRUE------- print(resDELeuk500$DEplots_TimeAndGroup$Number_DEgenes_SignatureGenes_UpDownRegulated_perTimeperGroup) ## ----DEleukSummaryDE, warning=FALSE, message=FALSE, eval=TRUE-------------- print(resDELeuk500$DEplots_TimeAndGroup$Number_DEgenes1TimeMinimum_Specific1TimeMinimum_Signature1TimeMinimum_perBiologicalCondition) ## ----VolcanoMA_CLL, warning=FALSE, message=FALSE, eval=TRUE---------------- SEresVolcanoMAleuk <- DEplotVolcanoMA(SEresDE=SEresDELeuk500, NbGene.plotted=2, SizeLabel=3, Display.plots=FALSE, Save.plots=FALSE) ## ----Volcanoleukemia_res, warning=FALSE, message=FALSE, eval=TRUE---------- ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresVolcanoMAleuk)$Results ## Save the results of DEplotVolcanoMA in an object resVolMAleuk500 <- resleuk500[[2]][[3]] ### names(S4Vectors::metadata(SEresVolcanoMAleuk)) str(resleuk500, max.level=3, give.attr=FALSE) names(resVolMAleuk500) ## ----Leuk_namesVolcanoMA, eval=TRUE---------------------------------------- str(resVolMAleuk500$Volcano, max.level=2, give.attr=FALSE) ## ----Leuk_VolcanoP_t2t0, eval=TRUE----------------------------------------- print(resVolMAleuk500$Volcano$P$P_t2_vs_t0) ## ----Leuk_MA_P_t2t0, eval=TRUE--------------------------------------------- print(resVolMAleuk500$MA$P$P_t2_vs_t0) ## ----Heatmaps_CCL, warning=FALSE, message=FALSE, eval=TRUE----------------- SEresHeatmapLeuk <- DEplotHeatmaps(SEresDE=SEresVolcanoMAleuk, ColumnsCriteria=c(18, 19), Set.Operation="union", NbGene.analysis=20, SizeLabelRows=5, SizeLabelCols=5, Display.plots=FALSE, Save.plots=FALSE) ## ----Heatmapleukemia_res, warning=FALSE, message=FALSE, eval=TRUE---------- ## Save 'Results' of the metadata in an object resleuk500 <- S4Vectors::metadata(SEresHeatmapLeuk)$Results ## Save the results of DEplotHeatmaps in an object resHeatmapLeuk <- resleuk500[[2]][[4]] ### names(S4Vectors::metadata(SEresHeatmapLeuk)) str(resleuk500, max.level=3, give.attr=FALSE) names(resHeatmapLeuk) ## ----Leuk_Heatmaps, eval=TRUE---------------------------------------------- print(resHeatmapLeuk$Heatmap_Correlation) print(resHeatmapLeuk$Heatmap_Zscore) ## ----GSEAquickAnalysis_CLL, warning=FALSE, message=FALSE, eval=TRUE-------- SEresgprofiler2Leuk <- GSEAQuickAnalysis(Internet.Connection=FALSE, SEresDE=SEresHeatmapLeuk, ColumnsCriteria=c(18), ColumnsLog2ordered=NULL, Set.Operation="union", Organism="hsapiens", MaxNumberGO=20, Background=FALSE, Display.plots=FALSE, Save.plots=FALSE) ## ## head(SEresgprofiler2Leuk$GSEAresults) ## ----GSEAprepro_CLL, warning=FALSE, message=FALSE, eval=TRUE--------------- SEresPreprocessingLeuk <- GSEApreprocessing(SEresDE=SEresDELeuk500, ColumnsCriteria=c(18, 19), Set.Operation="union", Rnk.files=FALSE, Save.files=FALSE) ## ----DATAprepSEmus1, echo=TRUE, eval=TRUE---------------------------------- SEresPrepMus1 <- DATAprepSE(RawCounts=RawCounts_Antoszewski2022_MOUSEsub500, Column.gene=1, Group.position=1, Time.position=NULL, Individual.position=2) ## ----NormalizationMouse1, echo=TRUE, eval=TRUE----------------------------- SEresNormMus1 <- DATAnormalization(SEres=SEresPrepMus1, Normalization="rle", Blind.rlog.vst=FALSE, Plot.Boxplot=TRUE, Colored.By.Factors=TRUE, Color.Group=NULL, path.result=NULL) ## ----NormalizationMouseColor, eval=TRUE------------------------------------ colMus1 <- data.frame(Name=c("N1wtT1wt", "N1haT1wt", "N1haT1ko", "N1wtT1ko"), Col=c("black", "red", "green", "blue")) ## ----PCAMouse1, eval=TRUE-------------------------------------------------- SEresPCAMus1 <- PCAanalysis(SEresNorm=SEresNormMus1, sample.deletion=NULL, gene.deletion=NULL, Plot.PCA=TRUE, Mean.Accross.Time=FALSE, Color.Group=NULL, Cex.label=0.8, Cex.point=0.7, epsilon=0.2, Phi=25,Theta=140, motion3D=FALSE, path.result=NULL) ## ----PCAMouseColor, eval=TRUE---------------------------------------------- colMus1 <- data.frame(Name=c("N1wtT1wt", "N1haT1wt", "N1haT1ko", "N1wtT1ko"), Col=c("black", "red", "green", "blue")) colMus1 ## ----HCPCmouse1, warning=FALSE, message=FALSE, eval=TRUE------------------- SEresHCPCMus1 <- HCPCanalysis(SEresNorm=SEresNormMus1, gene.deletion=NULL, sample.deletion=NULL, Plot.HCPC=FALSE, Cex.label=0.8, Cex.point=0.7, epsilon=0.2, Phi=25, Theta=140, motion3D=FALSE, path.result=NULL) ## ----DATAplotExpressionGenesMouse, warning=FALSE, message=FALSE, eval=TRUE---- resEVOmus1500 <- DATAplotExpressionGenes(SEresNorm=SEresNormMus1, Vector.row.gene=c(10), Color.Group=NULL, Plot.Expression=TRUE, path.result=NULL) ## ----ProfileMouseColor, warning=FALSE, message=FALSE, eval=TRUE------------ colMus1 <- data.frame(Name=c("N1wtT1wt", "N1haT1wt", "N1haT1ko", "N1wtT1ko"), Col=c("black", "red", "green", "blue")) ## ----DEmouse, warning=FALSE, message=FALSE, eval=TRUE---------------------- SEresDEMus1 <- DEanalysisGlobal(SEres=SEresPrepMus1, pval.min=0.05, pval.vect.t=NULL, log.FC.min=1, LRT.supp.info=FALSE, Plot.DE.graph=FALSE, path.result=NULL, Name.folder.DE=NULL) ## data("Results_DEanalysis_sub500") ## SEresDEMus1 <- Results_DEanalysis_sub500$DE_Antoszewski2022_MOUSEsub500 ## ----DEresultsMouse1, warning=FALSE, message=FALSE, eval=TRUE-------------- DEsummaryMus1 <- SummarizedExperiment::rowData(SEresDEMus1) ## ----GlossaryMouse1, warning=FALSE, message=FALSE, eval=TRUE--------------- resDEMus1 <- S4Vectors::metadata(SEresDEMus1)$Results[[2]][[2]] resGlossaryMus1 <- resDEMus1$Glossary ## ----VennBarplotMouse1, warning=FALSE, message=FALSE, eval=TRUE------------ print(resDEMus1$VennBarplot) ## ----SpecificAndNoSpecificMouse1, warning=FALSE, message=FALSE, eval=TRUE---- print(resDEMus1$NumberDEgenes_SpecificAndNoSpecific) ## ----SpecificGenesMouse1, warning=FALSE, message=FALSE, eval=TRUE---------- print(resDEMus1$NumberDEgenes_SpecificGenes) ## ----VolcanoMAMus1, warning=FALSE, message=FALSE, eval=TRUE---------------- SEresVolcanoMAMus1 <- DEplotVolcanoMA(SEresDE=SEresDEMus1, NbGene.plotted=2, SizeLabel=3, Display.plots=FALSE, Save.plots=FALSE) ## ----HeatmapsMus1, warning=FALSE, message=FALSE, eval=TRUE----------------- SEresVolcanoMAMus1 <- DEplotHeatmaps(SEresDE=SEresDEMus1, ColumnsCriteria=2,#c(2,4), Set.Operation="union", NbGene.analysis=20, SizeLabelRows=5, SizeLabelCols=5, Display.plots=FALSE, Save.plots=FALSE) ## ----GSEAquickAnalysis_Mus, warning=FALSE, message=FALSE, eval=TRUE-------- SEresgprofiler2Mus1 <- GSEAQuickAnalysis(Internet.Connection=FALSE, SEresDE=SEresDEMus1, ColumnsCriteria=2, ColumnsLog2ordered=NULL, Set.Operation="union", Organism="mmusculus", MaxNumberGO=10, Background=FALSE, Display.plots=FALSE, Save.plots=FALSE) ## ## head(4Vectors::metadata(SEresgprofiler2Mus1)$Rgprofiler2$GSEAresults) ## ----GSEAprepro_Mus1, warning=FALSE, message=FALSE, eval=TRUE-------------- SEresPreprocessingMus1 <- GSEApreprocessing(SEresDE=SEresDEMus1, ColumnsCriteria=2, Set.Operation="union", Rnk.files=FALSE, Save.files=FALSE) ## ----DATAprepSEfission, echo=TRUE, eval=TRUE------------------------------- SEresPrepFission <- DATAprepSE(RawCounts=RawCounts_Leong2014_FISSIONsub500wt, Column.gene=1, Group.position=NULL, Time.position=2, Individual.position=3) ## ----NormalizationFission, eval=TRUE--------------------------------------- SEresNormYeast <- DATAnormalization(SEres=SEresPrepFission, Normalization="rlog", Blind.rlog.vst=FALSE, Plot.Boxplot=FALSE, Colored.By.Factors=TRUE, Color.Group=NULL, Plot.genes=FALSE, path.result=NULL) ## ----PCAfission, warning=FALSE, message=FALSE, eval=TRUE------------------- SEresPCAyeast <- PCAanalysis(SEresNorm=SEresNormYeast, gene.deletion=NULL, sample.deletion=NULL, Plot.PCA=FALSE, Mean.Accross.Time=FALSE, Cex.label=0.8, Cex.point=0.7, epsilon=0.3, Phi=25,Theta=140, motion3D=FALSE, path.result=NULL) ## ----HCPCfission, warning=FALSE, message=FALSE, eval=TRUE------------------ SEresHCPCyeast <- HCPCanalysis(SEresNorm=SEresNormYeast, gene.deletion=NULL, sample.deletion=NULL, Plot.HCPC=FALSE, Cex.label=0.9, Cex.point=0.7, epsilon=0.2, Phi=25,Theta=140, motion3D=FALSE, path.result=NULL) ## ----MfuzzFission, warning=FALSE, message=FALSE, eval=TRUE----------------- SEresMfuzzYeast <- MFUZZanalysis(SEresNorm=SEresNormYeast, DataNumberCluster=NULL, Method="hcpc", Membership=0.5, Min.std=0.1, Plot.Mfuzz=FALSE, path.result=NULL) ## ----DATAplotExpressionGenesFission, warning=FALSE, message=FALSE, eval=TRUE---- SEresEVOyeast <- DATAplotExpressionGenes(SEresNorm=SEresNormYeast, Vector.row.gene=c(17), Plot.Expression=TRUE, path.result=NULL) ## ----DEanalysisFISSION, warning=FALSE, message=FALSE, eval=TRUE------------ # DEyeastWt <- DEanalysisGlobal(SEres=SEresPrepFission, log.FC.min=1, # pval.min=0.05, pval.vect.t=NULL, # LRT.supp.info=FALSE, Plot.DE.graph =FALSE, # path.result=NULL, Name.folder.DE=NULL) data("Results_DEanalysis_sub500") DEyeastWt <- Results_DEanalysis_sub500$DE_Leong2014_FISSIONsub500wt ## ----DEresultsFission, warning=FALSE, message=FALSE, eval=TRUE------------- DEsummaryFission <- SummarizedExperiment::rowData(DEyeastWt) ## ----GlossaryFission, warning=FALSE, message=FALSE, eval=TRUE-------------- resDEyeast <- S4Vectors::metadata(DEyeastWt)$Results[[2]][[2]] resGlossaryFission <- resDEyeast$Glossary ## ----VolcanoMA_FISSION, warning=FALSE, message=FALSE, eval=TRUE------------ SEresVolcanoMAFission <- DEplotVolcanoMA(SEresDE=DEyeastWt, NbGene.plotted=2, SizeLabel=3, Display.plots=FALSE, Save.plots=TRUE) ## ----Heatmaps_FISSION, warning=FALSE, message=FALSE, eval=TRUE------------- SEresHeatmapFission <- DEplotHeatmaps(SEresDE=DEyeastWt, ColumnsCriteria=2, Set.Operation="union", NbGene.analysis=20, Color.Group=NULL, SizeLabelRows=5, SizeLabelCols=5, Display.plots=TRUE, Save.plots=FALSE) ## ----GSEAquickAnalysis_Fission, warning=FALSE, message=FALSE, eval=TRUE---- SEresGprofiler2Fission <- GSEAQuickAnalysis(Internet.Connection=FALSE, SEresDE=DEyeastWt, ColumnsCriteria=2, ColumnsLog2ordered=NULL, Set.Operation="union", Organism="spombe", MaxNumberGO=20, Background=FALSE, Display.plots=FALSE, Save.plots=FALSE) ## ## head(SEresGprofiler2Fission$GSEAresults) ## ----GSEAprepro_Fission, warning=FALSE, message=FALSE, eval=TRUE----------- SEresPreprocessingYeast <- GSEApreprocessing(SEresDE=DEyeastWt, ColumnsCriteria=2, Set.Operation="union", Rnk.files=FALSE, Save.files=FALSE) ## ----DATAprepSEmus22, eval=TRUE-------------------------------------------- SEresPrepMus2 <- DATAprepSE(RawCounts=RawCounts_Weger2021_MOUSEsub500, Column.gene=1, Group.position=1, Time.position=2, Individual.position=3) ## ----NormalizationMouse2, eval=TRUE---------------------------------------- SEresNormMus2 <- DATAnormalization(SEres=SEresPrepMus2, Normalization="vst", Blind.rlog.vst=FALSE, Plot.Boxplot=FALSE, Colored.By.Factors=TRUE, Color.Group=NULL, path.result=NULL) ## ----NormalizationMus2color, eval=TRUE------------------------------------- colMus2 <- data.frame(Name=c("BmKo", "BmWt" ,"CrKo", "CrWt"), Col=c("red", "blue", "orange", "darkgreen")) ## ----PCAMus2, warning=FALSE, message=FALSE, eval=TRUE---------------------- SEresPCAmus2 <- PCAanalysis(SEresNorm=SEresNormMus2, gene.deletion=NULL, sample.deletion=NULL, Plot.PCA=FALSE, motion3D=FALSE, Mean.Accross.Time=FALSE, Color.Group=NULL, Cex.label=0.6, Cex.point=0.7, epsilon=0.2, Phi=25, Theta=140, path.result=NULL, Name.folder.pca=NULL) ## ----PCAmus2color, warning=FALSE, message=FALSE, eval=TRUE----------------- colMus2 <- data.frame(Name=c("BmKo", "BmWt", "CrKo", "CrWt"), Col=c("red", "blue", "orange", "darkgreen")) ## ----HCPCmus2500, warning=FALSE, message=FALSE, eval=TRUE------------------ SEresHCPCmus2 <- HCPCanalysis(SEresNorm=SEresNormMus2, gene.deletion=NULL, sample.deletion=NULL, Plot.HCPC=FALSE, Phi=25,Theta=140, Cex.point=0.6, epsilon=0.2, Cex.label=0.6, motion3D=FALSE, path.result=NULL, Name.folder.hcpc=NULL) ## ----MfuzzMus2, warning=FALSE, message=FALSE, eval=TRUE-------------------- SEresMfuzzLeuk500 <- MFUZZanalysis(SEresNorm=SEresNormMus2, DataNumberCluster=NULL, Method="hcpc", Membership=0.5, Min.std=0.1, Plot.Mfuzz=FALSE, path.result=NULL, Name.folder.mfuzz=NULL) ## ----DATAplotExpressionGenesMusBmCrKoWt, warning=FALSE, message=FALSE, eval=TRUE---- SEresEVOmus2 <- DATAplotExpressionGenes(SEresNorm=SEresNormMus2, Vector.row.gene=c(17), Color.Group=NULL, Plot.Expression=FALSE, path.result=NULL) ## ----PreprocessPCAHcpcMusBmCrKoWt, warning=FALSE, message=FALSE, eval=TRUE---- colMus2 <- data.frame(Name=c("BmKo", "BmWt", "CrKo", "CrWt"), Col=c("red", "blue", "orange", "darkgreen")) ## ----UsbMusBmCrKoWt, warning=FALSE, message=FALSE, eval=TRUE--------------- Sub3bc3T <- RawCounts_Weger2021_MOUSEsub500[, seq_len(73)] SelectTime <- grep("_t0_", colnames(Sub3bc3T)) SelectTime <- c(SelectTime, grep("_t1_", colnames(Sub3bc3T))) SelectTime <- c(SelectTime, grep("_t2_", colnames(Sub3bc3T))) Sub3bc3T <- Sub3bc3T[, c(1, SelectTime)] SEresPrepMus23b3t <- DATAprepSE(RawCounts=Sub3bc3T, Column.gene=1, Group.position=1, Time.position=2, Individual.position=3) ## ----DEMusBmCrKoWt, warning=FALSE, message=FALSE, eval=TRUE---------------- SEresDE3tMus2 <- DEanalysisGlobal(SEres=SEresPrepMus23b3t, pval.min=0.05, pval.vect.t=NULL, log.FC.min=1, LRT.supp.info=FALSE, Plot.DE.graph=FALSE, path.result=NULL, Name.folder.DE=NULL) ## ----DEresultsMus2, warning=FALSE, message=FALSE, eval=TRUE---------------- DEsummaryMus2 <- SummarizedExperiment::rowData(SEresDE3tMus2) ## ----GlossaryMus2, warning=FALSE, message=FALSE, eval=TRUE----------------- resDEmus2 <- S4Vectors::metadata(SEresDE3tMus2)$Results[[2]][[2]] resGlossaryMus2 <- resDEmus2$Glossary ## ----DEgenesSpecificgenesMus2, warning=FALSE, message=FALSE, eval=TRUE----- resDEmus2$DEplots_GroupPerTime$NumberDEgenes_SpecificAndNoSpecific_perBiologicalCondition ## ----SpecificgenesMus2, warning=FALSE, message=FALSE, eval=TRUE------------ resDEmus2$DEplots_GroupPerTime$NumberSpecificGenes_UpDownRegulated_perBiologicalCondition ## ----VennBarplotMus2, warning=FALSE, message=FALSE, eval=TRUE-------------- resDEmus2$DEplots_GroupPerTime$VennBarplot_BiologicalConditions_atTime.t1 ## ----AlluvialSpe1minMus2, warning=FALSE, message=FALSE, eval=TRUE---------- resDEmus2$DEplots_GroupPerTime$AlluvialGraph_SpecificGenes1tmin_perBiologicalCondition ## ----AlluvialSignature1min, warning=FALSE, message=FALSE, eval=TRUE-------- print(resDEmus2$DEplots_TimeAndGroup$Alluvial_SignatureGenes_1TimeMinimum_perGroup) ## ----VolcanoMA_Mouse2, warning=FALSE, message=FALSE, eval=TRUE------------- SEresVolcanoMAmus2 <- DEplotVolcanoMA(SEresDE=SEresDE3tMus2, NbGene.plotted=2, SizeLabel=3, Display.plots=FALSE, Save.plots=FALSE) ## ----Heatmaps_Mouse2, warning=FALSE, message=FALSE, eval=TRUE-------------- SEresHeatmapMus2 <- DEplotHeatmaps(SEresDE=SEresDE3tMus2, ColumnsCriteria=2:5, Set.Operation="union", NbGene.analysis=20, SizeLabelRows=5, SizeLabelCols=5, Display.plots=FALSE, Save.plots=FALSE) ## ----GSEAquickAnalysis_Mouse2, warning=FALSE, message=FALSE, eval=TRUE----- SEresGprofiler2Mus2 <- GSEAQuickAnalysis(Internet.Connection=FALSE, SEresDE=SEresDE3tMus2, ColumnsCriteria=2:5, ColumnsLog2ordered=NULL, Set.Operation="union", Organism="mmusculus", MaxNumberGO=20, Background=FALSE, Display.plots=FALSE, Save.plots=FALSE) ## ## head(SEresGprofiler2Mus2$GSEAresults) ## ----GSEAprepro_Mouse2, warning=FALSE, message=FALSE, eval=TRUE------------ SEresPreprocessingMus2 <- GSEApreprocessing(SEresDE=SEresDE3tMus2, ColumnsCriteria=2:5, Set.Operation="union", Rnk.files=FALSE, Save.files=TRUE) ## ----sessionInfo, echo=FALSE, results="asis"------------------------------- utils::toLatex(sessionInfo())