inst/scripts/make-data_zhu2018NC_islets.R

In UCLouvain-CBIO/scpdata: Single-Cell Proteomics Data Package

####---- Zhu et al. 2018, Nature Communications - T1D islets ----####

## Zhu, Ying, Paul D. Piehowski, Rui Zhao, Jing Chen, Yufeng Shen, Ronald J. 
## Moore, Anil K. Shukla, et al. 2018. “Nanodroplet Processing Platform for Deep 
## and Quantitative Proteome Profiling of 10-100 Mammalian Cells.” Nature 
## Communications 9 (1): 882.

library(SingleCellExperiment)
library(scp)
library(tidyverse)
dataDir <- "~/PhD/.localdata/SCP/zhu2018NC_islets/"

# The data was downloaded from ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2018/01/PXD006847

####---- Peptide data ----####

## Load the quantification data
paste0(dataDir, "Islet_t1d_ct_peptides.txt") %>%
    read.table(sep = "\t", header = TRUE) %>%
    mutate(Batch = "peptides") ->
    peps
peps <- readSingleCellExperiment(peps,
                                 ecol = grep("^Intensity.", colnames(peps)),
                                 fnames = "Sequence")
colnames(peps) <- gsub("Intensity.", "", colnames(peps))

####---- Sample annotations ----####

## Create the sample annoation table
annot <- DataFrame(row.names = colnames(peps))
annot$SampleType <- sub("^.*([CT]).*$", "\\1", rownames(annot))
annot$SampleType <- dplyr::recode(annot$SampleType, 
                                  `T` = "T1D",
                                  `C` = "Control")

####---- Protein data ----####

## Load the quantification data
prots <- read.table(paste0(dataDir, "Islet_t1d_ct_proteinGroups.txt"),
                    sep = "\t", header = TRUE)
## Remove unnecessary columns
sel <- !grepl("Peptides.*[CT]|^Identif|^Razor.*[CT]|Sequence.*[CT]|Unique.*[CT]|MS.MS.*[CT]",
              colnames(prots))
prots <- prots[, sel]
## Split protein data based on the quantification method:
## 1. Protein intensity
protsInt <- prots[, !grepl("^iBAQ|^LFQ", colnames(prots))]
protsInt <- readSingleCellExperiment(protsInt, 
                                     ecol = grep("^Intensity.", colnames(protsInt)),
                                     fnames = "Protein.IDs")
colnames(protsInt) <- gsub("Intensity.", "", colnames(protsInt))
## 2. LFQ
protsLFQ <- prots[, !grepl("^iBAQ|^Intensity", colnames(prots))]
protsLFQ <- readSingleCellExperiment(protsLFQ, 
                                     ecol = grep("^LFQ.", colnames(protsLFQ)),
                                     fnames = "Protein.IDs")
colnames(protsLFQ) <- gsub("LFQ.intensity.", "", colnames(protsLFQ))
## 3. iBAQ
protsIBAQ <- prots[, !grepl("^LFQ|^Intensity", colnames(prots))]
protsIBAQ <- readSingleCellExperiment(protsIBAQ, 
                                      ecol = grep("^iBAQ.", colnames(protsIBAQ)),
                                      fnames = "Protein.IDs")
colnames(protsIBAQ) <- gsub("iBAQ.", "", colnames(protsIBAQ))

####---- Create the QFeatures object ----####

el <- ExperimentList(peptides = peps,
                     proteins_intensity = protsInt,
                     proteins_LFQ = protsLFQ,
                     proteins_iBAQ = protsIBAQ)
zhu2018NC_islets <- QFeatures(el, colData = annot)

## Create assay links
zhu2018NC_islets <- addAssayLink(zhu2018NC_islets, 
                                  from = "peptides", to = "proteins_intensity",
                                  varFrom = "Leading.razor.protein", 
                                  varTo = "Majority.protein.IDs")
zhu2018NC_islets <- addAssayLink(zhu2018NC_islets, 
                                  from = "peptides", to = "proteins_LFQ",
                                  varFrom = "Leading.razor.protein", 
                                  varTo = "Majority.protein.IDs")
zhu2018NC_islets <- addAssayLink(zhu2018NC_islets, 
                                  from = "peptides", to = "proteins_iBAQ",
                                  varFrom = "Leading.razor.protein", 
                                  varTo = "Majority.protein.IDs")

# Save data as Rda file
save(zhu2018NC_islets, 
     file = file.path("~/PhD/.localdata/scpdata/zhu2018NC_islets.Rda"),
     compress = "xz", 
     compression_level = 9)