SCTK Cell QC Report

In singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

require(singleCellTK)
require(ggplot2)
require(umap)
require(dplyr)

preprocessMeta <- function(meta, ignore=c("geneSetCollection", "sample")){
  meta <- meta[!names(meta) %in% ignore]
  lapply(meta, function(y){
    while(is.list(y)) {
      if (length(y) != 0){
       y <- y[[1]]  
      } else {
       y <- "NULL"
      }
    }

    if(is.vector(y)) {
      y <- paste(y,collapse=' ')
    }

    if(is.null(y)) {
      y <- "NULL"
    }

    return(y)
  })
}

formatPlotList <- function(plotlist, samples) {
  if (length(samples) > 1) {
    return(plotlist)
  }

  plotlist <- list(Sample = list(plotlist))
  names(plotlist$Sample) <- samples
  return(plotlist)
}

sce.qc <- params$object
subTitle <- params$subTitle
studyDesign <- params$studyDesign
samples <- unique(colData(sce.qc)$sample)

reduceDims<- grep('UMAP', reducedDimNames(sce.qc), value = TRUE)
if (length(reduceDims) != 0) {
  reduceDimUsed <- reduceDims[1]
} else {
  reduceDims<- grep('TSNE', reducedDimNames(sce.qc), value = TRUE)
  if (length(reduceDims) == 0) {
    stop("No reduced dimension are available for QC visualization!")
  } else {
    reduceDimUsed <- reduceDims[1]
  }
}

---

subtitle: "r subTitle"

r studyDesign

Introduction

Comprehensive quality control (QC) of single-cell RNA-seq data was performed with the singleCellTK package. This report contains information about each QC tool and visualization of the QC metrics for each sample. For more information on running this pipeline and performing quality control, see the documentation. If you use the singleCellTK package for quality control, please include a reference in your publication.

description_runPerCellQC <- descriptionRunPerCellQC()

i="General quality control metrics"
cat(paste0('# ', i, ' \n'))
cat("\n")

perCellData <- c("sum", "detected", "percent_top_50")
skipCellData <- any(!perCellData %in% names(colData(sce.qc)))

if (skipCellData) {
  cat("runPerCellQC did not complete successfully. The section of General quality control metrics is skipped")
  plotsQCMetrics <- NULL
} else {
  plotsQCMetrics<- tryCatch(
    {plotRunPerCellQCResults(sce.qc, 
                             sample = colData(sce.qc)$sample, 
                             combinePlot="none")},
    error = function(e) {
      cat("runPerCellQC did not complete successfully. The section of General quality control metrics is skipped")
      skipCellData <- TRUE
      return(NA)
    }
  )
}

if (!skipCellData) {

  if (length(samples) == 1) {
    plotsQCMetrics <- list(Violin=plotsQCMetrics)
    names(plotsQCMetrics$Violin)[names(plotsQCMetrics$Violin) == "TopPercent"] <- "Gene_Subset_Top50_Percent"
    names(plotsQCMetrics$Violin)[names(plotsQCMetrics$Violin) == "subsets_mito_sum"] <- "Gene_Subset_Sum"
    names(plotsQCMetrics$Violin)[names(plotsQCMetrics$Violin) == "subsets_mito_detected"] <- "Gene_Subset_Features"
  }
  cat(description_runPerCellQC$introduction)
  cat(description_runPerCellQC$runPerCellQC)
  cat(description_runPerCellQC$plotRunPerCellQCResults)
  cat(description_runPerCellQC$output)
  cat(description_runPerCellQC$sum)
  cat(description_runPerCellQC$detected)
  cat(description_runPerCellQC$percentTop)
  cat(description_runPerCellQC$subsets)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
cat(paste0('## Sum {.tabset .tabset-fade} \n\n'))
plotsQCMetrics$Violin$Sum
cat("\n\n")
cat(paste0('## Total {.tabset .tabset-fade} \n\n'))
plotsQCMetrics$Violin$Detected
cat("\n\n")
cat(paste0('## Subsets mito sum {.tabset .tabset-fade} \n\n'))
plotsQCMetrics$Violin$Gene_Subset_Sum
cat("\n\n")
cat(paste0('## Subsets mito detected {.tabset .tabset-fade} \n\n'))
plotsQCMetrics$Violin$Gene_Subset_Features
cat("\n\n")
cat(paste0('## Subsets mito percent {.tabset .tabset-fade} \n\n'))
plotsQCMetrics$Violin$Gene_Subset_Top50_Percent
cat("\n\n")
cat(paste0('## Session info {.tabset .tabset-fade} \n\n'))

runPerCellMeta <- sce.qc@metadata$scater
x <- preprocessMeta(runPerCellMeta[[samples[1]]]$addPerCellQC)
t(as.data.frame(x)) %>%
  knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
  kableExtra::scroll_box(width = "80%")

cat("\n")
cat(description_runPerCellQC$parameter)

r cat("\n\n")

Doublet Detection

description_Scrublet <- descriptionScrublet()

i="Scrublet"
cat(paste0('## ', i, ' \n'))

scrubletData <- c("scrublet_score", "scrublet_call")
skipScrublet <- any(!scrubletData %in% names(colData(sce.qc)))

if (skipScrublet) {
  cat("runScrublet did not complete successfully. The section of Scrublet is skipped")
  plotsScrublet <- NULL
} else {
    plotsScrublet<- tryCatch(
      {plotScrubletResults(sce.qc, 
                           reducedDimName=reduceDimUsed,
                           sample = colData(sce.qc)$sample,
                           combinePlot = "none")},
    error = function(e) {
      cat("runScrublet did not complete successfully. The section of Scrublet is skipped")
      skipScrublet <- TRUE
      return(NA)
    }
  )
}

if (!skipScrublet) {
  plotsScrublet <- formatPlotList(plotsScrublet, samples)
  cat(description_Scrublet$introduction)
  cat(description_Scrublet$runScrublet)
  cat(description_Scrublet$plotScrubletResults)
  cat(description_Scrublet$output)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples) {
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n\n")

  cat("#### Scrublet Doublet Score {.tabset .tabset-fade} \n")
  print(plotsScrublet$Sample[[sample]][["scatter_doubletScore"]])
  cat("\n\n")

  cat("#### Density Score {.tabset .tabset-fade} \n")
  print(plotsScrublet$Sample[[sample]][["density_doubletScore"]])
  cat("\n\n")

  cat("#### Violin Score {.tabset .tabset-fade} \n ")
  print(plotsScrublet$Sample[[sample]][["violin_doubletScore"]])
  cat("\n\n")

  cat("#### Scrublet Doublet Assignment {.tabset .tabset-fade} \n\n")
  print(plotsScrublet$Sample[[sample]][["scatter_doubletCall"]])
  cat("\n\n")  

  cat("#### Parameters {.tabset .tabset-fade} \n\n")
  runScrubletMeta <- sce.qc@metadata$runScrublet
  # if(length(samples) == 1) {
  #   runScrubletMeta <- list(runScrubletMeta)
  #   names(runScrubletMeta) <- sample
  # }

  x <- preprocessMeta(runScrubletMeta[[sample]])
  cat(t(as.data.frame(x)) %>%
    knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
    kableExtra::scroll_box(width = "80%"))
  cat(description_Scrublet$additionalParam)
  cat("\n\n")
}

r cat("\n")

description_DoubletFinder <- descriptionDoubletFinder()

i="DoubletFinder"
cat(paste0('## ', i, ' \n'))


doubletFinderData <- grep("doubletFinder_doublet", names(colData(sce.qc)), value=TRUE)
skipFinder <- length(doubletFinderData)==0  

if (skipFinder) {
  cat("runDoubletFinder did not complete successfully. The section of DoubletFinder is skipped")
  plotDoubletFinder <- NULL
} else {
  plotDoubletFinder<- tryCatch(
    {plotDoubletFinderResults(inSCE = sce.qc, 
                              reducedDimName=reduceDimUsed,
                              sample = colData(sce.qc)[['sample']],
                              combinePlot = "none")},
    error = function(e) {
      cat("runDoubletFinder did not complete successfully. The section of DoubletFinder is skipped")
      skipFinder <- TRUE
      return(NA)
    }
  )
}

if (!skipFinder) {
  plotDoubletFinder <- formatPlotList(plotDoubletFinder, samples)
  resolutions <- grep("doubletFinder_doublet_score_resolution_", colnames(colData(sce.qc)), value = TRUE)
  resolutions <- gsub("doubletFinder_doublet_score_resolution_", "", resolutions)

  cat(description_DoubletFinder$introduction)
  cat(description_DoubletFinder$runDoubletFinder)
  cat(description_DoubletFinder$plotDoubletFinderResults)
  cat(description_DoubletFinder$output)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples) {
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n")
  for (resolution in resolutions) {
    cat(paste0("#### Resolution: ", resolution, " {.tabset .tabset-fade} \n"))
    cat("\n")

    cat("##### DoubletFinder Doublet Score {.tabset .tabset-fade} \n\n")
    print(plotDoubletFinder$Sample[[sample]][[paste0("Scatter_Score_resolution_", resolution)]])
    cat("\n\n")

    cat("##### Density of Doublet Score {.tabset .tabset-fade} \n\n")
    print(plotDoubletFinder$Sample[[sample]][[paste0("Density_resolution_", resolution)]])
    cat("\n\n")

    cat("##### Violin of Doublet Score {.tabset .tabset-fade} \n\n")
    print(plotDoubletFinder$Sample[[sample]][[paste0("violin_resolution_", resolution)]])
    cat("\n\n")

    cat("##### DoubletFinder Doublet Assignment {.tabset .tabset-fade} \n\n")
    print(plotDoubletFinder$Sample[[sample]][[paste0("Scatter_Call_resolution_", resolution)]])
    cat("\n\n")

    cat("##### Parameters {.tabset .tabset-fade} \n\n")
    DoubletFinderMeta <- sce.qc@metadata$runDoubletFinder
    # if(length(samples) == 1) {
    #   DoubletFinderMeta <- list(DoubletFinderMeta)
    #   names(DoubletFinderMeta) <- sample
    # }

    x <- preprocessMeta(DoubletFinderMeta[[sample]])
    cat(t(as.data.frame(x)) %>%
      knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
      kableExtra::scroll_box(width = "80%"))

    cat(description_DoubletFinder$seuratRes)
    cat(description_DoubletFinder$seuratNfeatures)
    cat(description_DoubletFinder$seuratPCs)
    cat(description_DoubletFinder$seuratFormationRate)
    cat("\n\n")
  }
}

r cat("\n")

description_DoubletCells<- descriptionDoubletCells()

i="DoubletCells"
cat(paste0('## ', i, ' \n'))

doubletCellData <- c("scran_doubletCells_score")
skipDoubletCell <- any(!doubletCellData %in% names(colData(sce.qc)))

if (skipDoubletCell) {
  cat("runDoubletCells did not complete successfully. The section of DoubletCells is skipped")
  plotDoubletCells <- NULL
} else {
  plotDoubletCells<- tryCatch(
    {plotDoubletCellsResults(inSCE = sce.qc, 
                             reducedDimName=reduceDimUsed,
                             sample = colData(sce.qc)[['sample']],
                             combinePlot = "none")},
    error = function(e) {
      cat("runDoubletCells did not complete successfully. The section of DoubletCells is skipped")
      skipDoubletCell <- TRUE
      return(NA)
    }
  )
}

if(!skipDoubletCell) {
  plotDoubletCells <- formatPlotList(plotDoubletCells, samples)
  cat(description_DoubletCells$introduction)
  cat(description_DoubletCells$runDoubletCells)
  cat(description_DoubletCells$plotDoubletCellsResults)
  cat(description_DoubletCells$output)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples){
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n\n")

  cat("#### DoubletCells Doublet Score {.tabset .tabset-fade} \n\n ")
  print(plotDoubletCells$Sample[[sample]][["scatter_doubletScore"]])
  cat("\n\n")

  cat("#### Density Score {.tabset .tabset-fade} \n\n")
  print(plotDoubletCells$Sample[[sample]][["density_doubletScore"]])
  cat("\n\n")

  cat("#### Violin Score {.tabset .tabset-fade} \n\n")
  print(plotDoubletCells$Sample[[sample]][["violin_doubletScore"]])
  cat("\n\n")

  cat("#### Parameters {.tabset .tabset-fade} \n\n")
  DoubletCellMeta <- sce.qc@metadata$runDoubletCell
  # if(length(samples) == 1) {
  #   DoubletCellMeta <- list(DoubletCellMeta)
  #   names(DoubletCellMeta) <- sample
  # }

  x <- preprocessMeta(DoubletCellMeta[[sample]])
  cat(t(as.data.frame(x)) %>%
    knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
    kableExtra::scroll_box(width = "80%"))
  cat(description_DoubletCells$parameter)
  cat("\n\n")
}

r cat("\n")

descriprion_CxdsResults<- descriptionCXDS()

i="Cxds"
cat(paste0('## ', i, ' \n'))

cvdsData <- c("scds_cxds_score", "scds_cxds_call")
skipCxds <- any(!cvdsData %in% names(colData(sce.qc)))

if (skipCxds) {
  cat("runCxds did not complete successfully. The section of Cxds is skipped")
  plotCxds <- NULL
} else {
  plotCxds<- tryCatch(
    {plotCxdsResults(inSCE = sce.qc, 
                              reducedDimName=reduceDimUsed,
                              sample = colData(sce.qc)[['sample']],
                              combinePlot = "none")},
    error = function(e) {
      cat("runCxds did not complete successfully. The section of Cxds is skipped")
      skipCxds <- TRUE
      return(NA)
    }
  )
}

if (!skipCxds) {
  plotCxds <- formatPlotList(plotCxds, samples)
  cat(descriprion_CxdsResults$introduction)
  cat(descriprion_CxdsResults$runCxds)
  cat(descriprion_CxdsResults$plotCxdsResults)
  cat(descriprion_CxdsResults$output)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples){
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n\n")

  cat("#### Cxds Doublet Score {.tabset .tabset-fade} \n\n")
  plot(plotCxds$Sample[[sample]][["scatter_doubletScore"]])
  cat("\n\n")

  cat("#### Density Score {.tabset .tabset-fade} \n\n")
  plot(plotCxds$Sample[[sample]][["density_doubletScore"]])
  cat("\n\n")

  cat("#### Violin Score {.tabset .tabset-fade} \n\n")
  plot(plotCxds$Sample[[sample]][["violin_doubletScore"]])
  cat("\n\n")

  cat("#### Cxds Doublet Assignment {.tabset .tabset-fade} \n\n")
  plot(plotCxds$Sample[[sample]][["scatter_doubletCall"]])
  cat("\n\n")

  cat("#### Parameters {.tabset .tabset-fade} \n\n")
  CxdsMeta <- sce.qc@metadata$runCxds
  # if(length(samples) == 1) {
  #   CxdsMeta <- list(CxdsMeta)
  #   names(CxdsMeta) <- sample
  # }

  x <- preprocessMeta(CxdsMeta[[sample]])
  cat(t(as.data.frame(x)) %>%
    knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
    kableExtra::scroll_box(width = "80%"))

  cat(descriprion_CxdsResults$nTop)
  cat(descriprion_CxdsResults$binThresh)
  cat(descriprion_CxdsResults$verb)
  cat(descriprion_CxdsResults$retRes)
  cat(descriprion_CxdsResults$estNdbl)
  cat("\n\n")
}

r cat("\n")

descriprion_BcdsResults<- descriptionBCDS()

i="Bcds"
cat(paste0('## ', i, ' \n'))

bcdsData <- c("scds_bcds_score", "scds_bcds_call")
skipBcds <- any(!bcdsData %in% names(colData(sce.qc)))

if (skipBcds) {
  cat("runBcds did not complete successfully. The section of Bcds is skipped")
  plotBcds <- NULL
} else {
  plotBcds<- tryCatch(
    {plotBcdsResults(inSCE = sce.qc, 
                              reducedDimName=reduceDimUsed,
                              sample = colData(sce.qc)[['sample']],
                              combinePlot = "none")},
    error = function(e) {
      cat("runBcds did not complete successfully. The section of Bcds is skipped")
      skipBcds <- TRUE
      return(NA)
    }
  )
}

if (!skipBcds) {
  plotBcds <- formatPlotList(plotBcds, samples)
  cat(descriprion_BcdsResults$introduction)
  cat(descriprion_BcdsResults$runBcds)
  cat(descriprion_BcdsResults$plotBcdsResults)
  cat(descriprion_BcdsResults$output)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples){
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n\n")

  cat("#### Bcds Doublet Score {.tabset .tabset-fade} \n\n")
  plot(plotBcds$Sample[[sample]][["scatter_doubletScore"]])
  cat("\n\n")

  cat("#### Density Score {.tabset .tabset-fade} \n\n")
  plot(plotBcds$Sample[[sample]][["density_doubletScore"]])
  cat("\n\n")

  cat("#### Violin Score {.tabset .tabset-fade} \n\n")
  plot(plotBcds$Sample[[sample]][["violin_doubletScore"]])
  cat("\n\n")

  cat("#### Bcds Doublet Assignment {.tabset .tabset-fade} \n\n")
  plot(plotBcds$Sample[[sample]][["scatter_doubletCall"]])
  cat("\n\n")

  cat("#### Parameters {.tabset .tabset-fade} \n\n")
  BcdsMeta <- sce.qc@metadata$runBcds
  # if(length(samples) == 1) {
  #   BcdsMeta <- list(BcdsMeta)
  #   names(BcdsMeta) <- sample
  # }

  x <- preprocessMeta(BcdsMeta[[sample]])
  cat(t(as.data.frame(x)) %>%
    knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
    kableExtra::scroll_box(width = "80%"))

  cat(descriprion_BcdsResults$nTop)
  cat(descriprion_BcdsResults$srat)
  cat(descriprion_BcdsResults$nmax)
  cat(descriprion_BcdsResults$varImp)
  cat("\n\n")
}

r cat("\n")

description_ScdsHybrid<- descriptionScdsHybrid()

i="ScdsHybrid"
cat(paste0('## ', i, ' \n'))

hybridData <- c("scds_hybrid_score", "scds_hybrid_call")
skipScdsHybrid <- any(!hybridData %in% names(colData(sce.qc)))

if (skipScdsHybrid) {
  cat("runCxdsBcdsHybrid did not complete successfully. The section of ScdsHybrid is skipped")
  plotScdsHybrid <- NULL
} else {
  plotScdsHybrid<- tryCatch(
    {plotScdsHybridResults(inSCE = sce.qc, 
                              reducedDimName=reduceDimUsed,
                              sample = colData(sce.qc)[['sample']],
                              combinePlot = "none")},
    error = function(e) {
      cat("runCxdsBcdsHybrid did not complete successfully. The section of ScdsHybrid is skipped")
      skipScdsHybrid <- TRUE
      return(NA)
    }
  )
}

if (!skipScdsHybrid) {
  plotScdsHybrid <- formatPlotList(plotScdsHybrid, samples)
  cat(description_ScdsHybrid$introduction)
  cat(description_ScdsHybrid$runCxdsBcdsHybrid)
  cat(description_ScdsHybrid$plotScdsHybridResults)
  cat(description_ScdsHybrid$output)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples){
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n\n")

  cat("#### ScdsHybrid Doublet Score {.tabset .tabset-fade} \n\n")
  plot(plotScdsHybrid$Sample[[sample]][["scatter_doubletScore"]])
  cat("\n\n")

  cat("#### Density Score {.tabset .tabset-fade} \n\n")
  plot(plotScdsHybrid$Sample[[sample]][["density_doubletScore"]])
  cat("\n\n")

  cat("#### Violin Score {.tabset .tabset-fade} \n\n")
  plot(plotScdsHybrid$Sample[[sample]][["violin_doubletScore"]])
  cat("\n\n")

  cat("#### ScdsHybrid Doublet Assignment {.tabset .tabset-fade} \n\n")
  plot(plotScdsHybrid$Sample[[sample]][["scatter_doubletCall"]])
  cat("\n\n")

  cat("#### Parameters {.tabset .tabset-fade} \n\n")
  HybridMeta <- sce.qc@metadata$runCxdsBcdsHybrid
  # if(length(samples) == 1) {
  #   HybridMeta <- list(HybridMeta)
  #   names(HybridMeta) <- sample
  # }

  x <- preprocessMeta(HybridMeta[[sample]])
  cat(t(as.data.frame(x)) %>%
    knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
    kableExtra::scroll_box(width = "80%"))

  cat(description_ScdsHybrid$parameters)
  cat("\n\n")
}

r cat("\n")

Ambient RNA Detection

description_DecontX<- suppressWarnings(descriptionDecontX())

i="DecontX"
cat(paste0('## ', i, ' \n'))

decontXData <- c("decontX_contamination", "decontX_clusters")
skipDecontX <- any(!decontXData %in% names(colData(sce.qc)))

if (skipDecontX) {
  cat("runDecontX did not complete successfully. The section of DecontX is skipped")
  plotDecontX <- NULL
} else {
  plotDecontX<- tryCatch(
    {plotDecontXResults(inSCE = sce.qc, 
                              reducedDimName=reduceDimUsed,
                              sample = colData(sce.qc)[['sample']],
                              combinePlot = "none")},
    error = function(e) {
      cat("runDecontX did not complete successfully. The section of DecontX is skipped")
      skipDecontX <- TRUE
      return(NA)
    }
  )
}

if (!skipDecontX) {
  plotDecontX <- formatPlotList(plotDecontX, samples)
  cat(description_DecontX$introduction)
  cat(description_DecontX$runDecontX)
  cat(description_DecontX$plotDecontXResults)
  cat(description_DecontX$output)
  cat(description_DecontX$contamination)
  cat(description_DecontX$clustering)
}

{.unlisted .unnumbered .toc-ignore .tabset .tabset-fade}

cat("\n")
for (sample in samples){
  cat(paste0("### ", sample, " {.tabset .tabset-fade} \n"))
  cat("\n\n")

  cat("#### DecontX Contamination Score {.tabset .tabset-fade} \n\n")
  plot(plotDecontX$Sample[[sample]][["scatter_decontXContamination"]])
  cat("\n\n")

  cat("#### Density Score {.tabset .tabset-fade} \n\n")
  plot(plotDecontX$Sample[[sample]][["density_decontXContamination"]])
  cat("\n\n")

  cat("#### Violin Score {.tabset .tabset-fade} \n\n")
  plot(plotDecontX$Sample[[sample]][["violin_decontXContamination"]])
  cat("\n\n")

  cat("#### DecontX Clusters {.tabset .tabset-fade} \n\n")
  plot(plotDecontX$Sample[[sample]][["scatter_decontXClusters"]])
  cat("\n\n")

  cat("#### Parameters {.tabset .tabset-fade} \n\n")
  DecontXMeta <- sce.qc@metadata$runDecontX
  # if(length(samples) == 1) {
  #   DecontXMeta <- list(DecontXMeta)
  #   names(DecontXMeta) <- sample
  # }

  x <- preprocessMeta(DecontXMeta[[sample]])
  cat(t(as.data.frame(x)) %>%
    knitr::kable(format = "html") %>% kableExtra::kable_styling() %>%
    kableExtra::scroll_box(width = "80%"))
  cat("\n\n")
}

r cat("\n")

Session Info

sessionInfo()

singleCellTK documentation built on Nov. 8, 2020, 5:21 p.m.