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 pancreatic cancer compared to normal tissue. The analysis is described in more detail in a paper (Dick, 2021). 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~).

datasets <- pdat_pancreatic(2020)

pdat1 <- lapply(datasets, pdat_pancreatic)
comptab1 <- lapply(pdat1, get_comptab)
comptab2 <- lapply(pdat1, get_comptab, "nAA", "MW")

Differences are calculated as (median value for up-regulated proteins) - (median value for down-regulated proteins). Dashed lines enclose the 50% confidence region for highest probability density.

par(mar = c(4, 4, 1, 1))
diffplot(comptab1, labtext = NA)

In the table, values of ΔZ_C and Δn_H2O are multiplied by 1000, values of 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; T – tumor; N – normal; LCM – laser capture microdisecction; FFPE – formalin-fixed paraffin-embedded; DM – diabetes mellitus.
• n_AA – protein length; MW – molecular weight per residue.

library(xtable)
out <- xsummary2(comptab1, comptab2)
# round values and include dataset tags
tags <- sapply(sapply(strsplit(datasets, "="), "[", -1), paste, collapse = ";")
out <- cbind(out[, 1:2], tags = tags, out[, 3:16])
out[, 6:17] <- round(out[, 6:17], 4)
file <- paste0("pancreatic.csv")
write.csv(out, file, row.names = FALSE, quote = 2)

Data Sources

Gene names or other identifiers were converted to UniProt accession numbers using the UniProt mapping tool, except for IPI accession numbers, which were converted using the DAVID 6.7 conversion tool.

a. Tables 2 and 3 of @LHE+04. b. Tables 1 and 2 of @CYD+05. c. Table 2 of @CGB+05. d. Table 1 of @CTZ+09. e. IPI numbers from Supplementary Table S2 of @MLC+11. f. Supplementary Table 3 of @PCS+11. g. Extracted from the SI Table of @TMW+11. h. Supplementary Tables 2 and 3 of @KBK+12. i. SI Table S3 of @KHO+13, filtered to include proteins with an expression ratio >2 [or <0.5] in at least 5 of the 7 experiments and ratio >1 [or <1] in all experiments. j. Supplementary Table 2 of @KPC+13. k. l. Supplementary Tables S3 and S4 of @WLL+13a, including proteins with >3/2 or <2/3 fold change in at least 3 of 4 iTRAQ experiments for different pooled samples. m. Supplementary Tables 2 and 3 of @YKK+13 (data file provided by Youngsoo Kim). n. SI Table S5 of @ZNWL13. o. SI Table S5 of @ISI+14, filtered to exclude proteins marked as "not passed", i.e. having inconsistent regulation. p. Table S6, Sheet 2 of @BZQ+14. q. Table 1 of @MZH+14. r. Table S6 of @BHB+15. s. Supplementary Table of @KKC+16. t. Supplementary Table S3 of @CHO+18. u. Table S1 of @SWW+18, filtered to exclude proteins with opposite expression changes in different patients. v. Gene names extracted from Figure 1b of @ZAH+19.

Acknowledgement

Thanks to Youngsoo Kim for providing a data file.

References

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