In uzh/ezRun: An R meta-package for the analysis of Next Generation Sequencing Data

```r

knitr::opts_chunk$set(echo = TRUE,warning=FALSE, message=FALSE, out.width = "49%")

This report requires summary files form mothur

debug <- FALSE

```r
## 
heatmapOrgAbundPlot <- summaryHeatmap(orgDFforHeatmap, 
                                      isGroupThere, 
                                      dataset=dataset, 
                                      numberOfTopNCategories)
heatmapFuncAbundPlot <- summaryHeatmap(funcDFforHeatmap, 
                                       isGroupThere, 
                                       dataset=dataset, 
                                       numberOfTopNCategories)

diffTableOrg <- metagMetatrDifferentialAnalysis_tableAndPlots(orgDFforHeatmap,
                                                              dataset,
                                                              group,sampleGroup,refGroup,
                                                              N=numberOfTopNCategories)
diffTableFunc <- metagMetatrDifferentialAnalysis_tableAndPlots(funcDFforHeatmap,
                                                               dataset,
                                                               group,sampleGroup,refGroup,
                                                               N=numberOfTopNCategories)

boxBarPlotOrgData <- orgFuncHeatmaptoBoxPlotPrep(orgDFforHeatmap,
                                                 dataset,group,N=10)
boxBarPlotFuncData <-  orgFuncHeatmaptoBoxPlotPrep(funcDFforHeatmap,
                                                   dataset,group,N=10)
boxPlotOrg <- ggplot(boxBarPlotOrgData,aes(x=boxBarPlotOrgData[[group]],
                                           y=abund,fill=boxBarPlotFuncData[[group]]))+
    geom_boxplot()+stat_compare_means(size=2) +
    facet_wrap(vars(ID)) + labs(fill=group) + 
    theme(axis.title.x = element_blank(),strip.text.x = element_text(size = 4.5))
boxPlotFunc <- ggplot(boxBarPlotFuncData,aes(x=boxBarPlotFuncData[[group]],
                                             y=abund,fill=boxBarPlotFuncData[[group]]))+
    geom_boxplot()+stat_compare_means(size=2) +
    facet_wrap(vars(ID)) + labs(fill=group) + 
    theme(axis.title.x = element_blank(),strip.text.x = element_text(size = 4.5))
barPlotOrg <- ggplot(boxBarPlotOrgData,aes(x=sample,y=abund,fill=ID))+
    geom_bar(stat="identity")   
barPlotFunc <- ggplot(boxBarPlotFuncData,aes(x=sample,y=abund,fill=ID))+
    geom_bar(stat="identity")   

listOfOrgFuncHeatmapDF <- lapply(listOfAnnotatedAbundTable,orgFuncHeatmapPrep,
                                 diffTableFunc=diffTableFunc)
names(listOfOrgFuncHeatmapDF) <- names(listOfAnnotatedAbundTable)
listOfOrgBasedOrgFuncHeatmap <- lapply(names(listOfOrgFuncHeatmapDF),                                    function(x)summaryHeatmap(data.frame(t(listOfOrgFuncHeatmapDF[[x]])),                                                              FALSE,numberOfTopNCategories=5, plotTitle=x))
listOfOrgBasedOrgFuncHeatmapForGrid <- lapply(listOfOrgBasedOrgFuncHeatmap[c(1,4)], function(x)x()[[4]])
###
listOfFuncBasedOrgFuncHeatmap <- lapply(names(listOfOrgFuncHeatmapDF),
                                        function(x)summaryHeatmap(listOfOrgFuncHeatmapDF[[x]],                                                              FALSE,numberOfTopNCategories=5, plotTitle=x))
listOfFuncBasedOrgFuncHeatmapForGrid <- lapply(listOfFuncBasedOrgFuncHeatmap[c(1,4)], function(x)x()[[4]])

Started on r format(Sys.time(), "%Y-%m-%d %H:%M:%S")

Data pre-processing {.tabset}

Abundance-based analysis: heatmap and table

Heatmap

heatmapOrgAbundPlot()

Most differentially abundant organisms

DT::datatable(diffTableOrg$tableToReport)

Abundance-based analysis: barplots and boxplots

Barplot of top organims abundance in the samples

plot(barPlotOrg)

Boxplot of top organims abundance in the samples

plot(boxPlotOrg)

Function expression-based analysis: heatmap and table

Heatmap

heatmapFuncAbundPlot()

Top differentially expressed functions

DT::datatable(diffTableFunc$tableToReport)

Function expression-based analysis: barplots and boxplots

Barplot of top function abundance in the samples

plot(barPlotFunc)

Boxplot of top function abundance in the samples

plot(boxPlotFunc)

Function-based heatmaps in the organisms

grid.arrange(arrangeGrob(grobs = listOfFuncBasedOrgFuncHeatmapForGrid, ncol=2))

Organism-based heatmaps in the functions

grid.arrange(arrangeGrob(grobs = listOfOrgBasedOrgFuncHeatmapForGrid, ncol=2))

uzh/ezRun documentation built on May 4, 2024, 3:23 p.m.