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 prostate 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_prostate(2020)

pdat1 <- lapply(datasets, pdat_prostate)
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; PCa – prostate cancer; BPH – benign prostatic hyperplasia; FFPE – formalin-fixed paraffin-embedded; OCT – optimal cutting temperature compound-embedded; TMA – tissue microarray; GS – Gleason Score; CiRT – common internal retention time.
• 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("prostate.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.

a. Table 2 of @GTR+08. b. Supplementary Tables 3 and 4 of @KPB+10. c. Table S2 of @HZH+12. d. Table S1 of @JHZ+13. e. Supplemental Table S7 of @LCS+14. f. Supplementary Table 1 @CZL+16 (proteins recorded with only Down-regulation or Up-regulation). g. Supplementary Table S3 of @IWT+16, filtered to include proteins listed with FDR < 0.1. h. i. Extracted from Table S4 @GLZ+18. Values were quantile normalized, then ratios were calculated between the median values for each cancer type (acinar and ductal) and corresponding normal tissue; ratios > 1.5 or < 2/3 were used to identify differentially expressed proteins. j. k. Extracted from Supplementary Data 1 of @LAJ+18 (sheet "Area-proteins") by applying quantile normalization to peak areas then calculating median values across all runs and samples for each of BPH , PC (primary prostate cancer), and CRPC (castration resistant prostate cancer). A cutoff of 2-fold in ratios of medians (PC / BPH or CRPC / BPH) was used to identify differentially expressed proteins. l. Table 2 of @MAN+18. m. n. o. p. q. Supporting Information Table S3 of @KRN+19 (G1--G5: PCa grades). r. s. Tables S4d (GS = 6) and S4f (GS ≥ 8 or GS = 6) of @MMF+20 (GS: Gleason Score). t. Supplementary Table S3a of @TOT+19. u. v. Table S5 of @ZYW+19 (LG: low-grade PCa; HG: high-grade PCa). w. Supplemental Table S2 of @KHN+20, filtered to include proteins with log~2~ fold change > 1 or < -1 in at least one experiment. x. Table S2 of @LDM+20. y. Table S2, Sheet D:S3-SWATH_protein_matrix of @SHC+20, filtered to include proteins quantified in at least 50% of both tumor and normal samples and with median fold change > 2 or < 0.5. z. Table S4 of @ZKL+20 (Pten gene knockout vs wild-type). A. Supplementary Tables S3E--S3F of @ZZX+20.

References

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