## ----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())