library(knitr)
## use pngquant to reduce size of PNG images
knit_hooks$set(pngquant = hook_pngquant)
pngquant <- "--speed=1 --quality=0-25"
# in case pngquant isn't available (R-Forge?)
if (!nzchar(Sys.which("pngquant"))) pngquant <- NULL 

This vignette from the R package JMDplots version r packageDescription("JMDplots")$Version shows chemical metrics for proteins coded by genes that are differentially expressed in hyperosmotic and hypoosmotic shock in yeast. The analysis is described in more detail in a paper (Dick, 2021). Abbreviations:

options(width = 90)
datasets <- pdat_yeast_stress(2020)
pdat1 <- lapply(datasets, pdat_yeast_stress)
comptab1 <- lapply(pdat1, get_comptab)
comptab2 <- lapply(pdat1, get_comptab, "pI", "GRAVY")
comptab3 <- lapply(pdat1, get_comptab, "nAA", "MW")

Differences are calculated as (median value for proteins coded by up-regulated genes) - (median value for proteins coded by down-regulated genes). Circles and squares stand for hyperosmotic and hypoosmotic experiments, respectively.

par(mar = c(4, 4, 1, 1))
pch <- ifelse(grepl("sorbitol", datasets), 1, 0)
diffplot(comptab1, labtext = NA, pch = pch)

In the table, values of ΔZC, ΔnH2O, and ΔGRAVY are multiplied by 1000, values of ΔpI and ΔMW are multiplied by 100, and negative values are shown in bold. Abbreviations:

library(xtable)
out <- xsummary3(comptab1, comptab2, comptab3)
# round values and include dataset tags
tags <- sapply(sapply(strsplit(datasets, "="), "[", -1), paste, collapse = ";")
out <- cbind(out[, 1:2], tags = tags, out[, 3:19])
out[, 6:20] <- round(out[, 6:20], 4)
file <- paste0("yeast_stress.csv")
write.csv(out, file, row.names = FALSE, quote = 2)

Data Sources

a. – l. complete_dataset.txt of @GSK+00, filtered to include genes with an expression ratio > log~2~(1.5) or < log~2~(1/1.5) at any time in the "1M sorbitol" or "Hypo-osmotic shock" experiments.

References



jedick/JMDplots documentation built on April 12, 2025, 1:35 p.m.