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

require(singleCellTK)
require(celda)
require(knitr)
require(gridExtra)
require(ggplot2)
require(dplyr)
library(kableExtra)

sce <- params$sce
analysisName <- params$analysisName
pdf <- params$pdf
showSession <- params$showSession


dev <- ifelse(isTRUE(pdf), c("png"), c("png", "pdf"))
knitr::opts_chunk$set(
  echo = TRUE,
  cache = FALSE,
  cache.lazy = FALSE,
  # don't do lazy-loading for big objects
  cache.comments = FALSE,
  fig.align = "center",
  fig.keep = "all",
  dev = dev
)

table <- getDiffAbundanceResults(sce, analysisName)

Differential Abundance FET

This report will visualize results from the diffAbundanceFET function, which calculates the cell counting and fraction by dividing all cells to groups specified by the arguments, together with statistical summary by performing Fisher Exact Tests (FET). The differential abundance analysis presented here is r params$analysisName.

table <- table %>% mutate_if(is.numeric, round, digits = 4)
kable(table, style = 'html', row.names = F) %>%
  kable_styling(bootstrap_options = "striped") %>%
  scroll_box(width = "100%", height = "800px")

Session Information

sessionInfo()

compbiomed/singleCellTK documentation built on May 8, 2024, 6:58 p.m.