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)
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.
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