title: Parse Kuono et al. data author: John Reid output: html_document
library(knitr) library(rmarkdown) # # knitr options # opts_chunk$set( fig.path = 'figures/Kuono-', stop_on_error = TRUE, fig.width = 12.5, fig.height = 8)
library(rmarkdown) library(devtools) load_all('../..') render('parse-Kouno.Rmd')
# suppressMessages(loadfonts()) # # Stylesheet # options(markdown.HTML.stylesheet = system.file("inst/Rmd/foghorn.css", package="DeLorean"))
Kouno et al. investigated the transcriptional network controlling how THP-1 human myeloid monocytic leukemia cells differentiate into macrophages. Load their data from the CSV provided as supplementary information in their paper.
library(dplyr) expr <- read.csv('../../data/gb-2013-14-10-r118-s3.csv')
Their cell labels have been messed up but Excel, so regenerate these.
time.points <- c("0h", "1h", "6h", "12h", "24h", "48h", "72h", "96h") obs.times <- c(0, 1, 6, 12, 24, 48, 72, 96) cell.ids <- ( as.vector( sapply(1:length(time.points), function(t) sapply(1:120, function(c) sprintf("%s-%03d", time.points[t], c))))) expr$cell <- factor(cell.ids, levels=cell.ids) kouno.cell.meta <- data.frame( cell=expr$cell, capture=factor( as.vector( sapply(1:length(time.points), function(t) rep(time.points[t], 120))), ordered=TRUE, levels=time.points)) %>% mutate(obstime=obs.times[capture]) kouno.gene.meta <- data.frame(gene=names(expr %>% select(-cell, -X)))
Kouno et al.'s data includes single cell expression values for
r nrow(kouno.gene.meta)
genes in r nrow(kouno.cell.meta)
cells
spread over r length(unique(kouno.cell.meta$capture))
time points.
Melt the data into a long format and log2 transform.
kouno.l <- melt(expr, variable.name="gene", value.name="expr") kouno.l <- kouno.l %>% mutate(log.expr=log2(expr))
Plot the raw expression and the log transformed expression.
ggplot(kouno.l, aes(x=expr)) + geom_histogram() ggplot(kouno.l, aes(x=log.expr)) + geom_histogram()
The log2 expression looks normally distributed. We will use this for as input to the DeLorean package. Cast the long format back into a matrix for use in the DeLorean package.
kouno.expr <- kouno.l %>% acast(gene ~ cell, value.var="log.expr")
Save the data in a format suitable for DeLorean package.
save(kouno.expr, kouno.gene.meta, kouno.cell.meta, file='../../data/KounoDeLorean.rda')
R version and packages used:
sessionInfo()
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