In jedick/JMDplots: Plots from Papers by Jeffrey M. Dick

library(JMDplots)
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 that are differentially expressed in halophiles under hyperosmotic or hypoosmotic conditions. The analysis is described in more detail in a paper (Dick et al., 2020). Abbreviations:

• Z_C – average oxidation state of carbon.
• n_H2O – stoichiometric hydration state per residue (Dick et al., 2020) computed using the QEC basis species (glutamine, glutamic acid, cysteine, H~2~O, O~2~).
• pI – isoelectric point; GRAVY – grand average of hydropathicity.
• n_AA – protein length; MW – molecular weight per residue.

datasets <- pdat_osmotic_halo(2020)

pdat1 <- lapply(datasets, pdat_osmotic_halo)
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 up-regulated proteins) - (median value for down-regulated proteins). Circles and squares represent hyperosmotic and hypoosmotic experiments, respectively.

layout(matrix(c(0, 2, 1, 2, 1, 3, 0, 3), nrow = 2))
par(cex = 1, mar = c(4, 4, 1, 1), mgp = c(2.5, 1, 0))
pch <- ifelse(grepl("hypoosmotic", datasets), 0, 1)
diffplot(comptab1, labtext = NA, contour = FALSE, pch = pch)
diffplot(comptab2, c("pI", "GRAVY"), labtext = NA, contour = FALSE, pch = pch)
diffplot(comptab3, c("nAA", "MW"), labtext = NA, contour = FALSE, pch = pch)

In the table, values of ΔZ_C, Δn_H2O, and ΔGRAVY are multiplied by 1000, values of ΔpI and ΔMW are multiplied by 100, and negative values are shown in bold. Abbreviations:

• n~down~ – number of down-regulated proteins; n~up~ – number of up-regulated proteins.

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("osmotic_halo.csv")
write.csv(out, file, row.names = FALSE, quote = 2)

Data Sources

a. b. Tables 1 and 2 of @LRB+09. c. d. Table S-1 of @ZLZ+16. Values of reporter intensities at each condition (6%, 10%, and 17.5% NaCl) were quantile normalized (R function preprocessCore::normalize.quantiles); normalized values were used to compute intensity ratios (6% / 10% NaCl and 17.5% / 10% NaCl). Only proteins with expression ratios > 1.3 in either direction [@ZLZ+16], p-values < 0.05, and at least 2 peptides were included. e. f. Tables S2 and S3 of @LLYL17. g. h. Supporting Table 1C of @JSP+19. Only proteins with at least 2-fold expression difference and marked as significant were included.

References

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