Nothing
## ----setup, echo=FALSE, results="hide"----------------------------------------
knitr::opts_chunk$set(tidy = FALSE,
cache = FALSE,
dev = "png",
message = FALSE, error = FALSE, warning = TRUE)
## ----libs---------------------------------------------------------------------
library(qPLEXanalyzer)
library(gridExtra)
data(human_anno)
data(exp2_Xlink)
## ----Import-------------------------------------------------------------------
MSnset_data <- convertToMSnset(exp2_Xlink$intensities,
metadata = exp2_Xlink$metadata,
indExpData = c(7:16),
Sequences = 2,
Accessions = 6)
MSnset_data
## ----Filter, fig.width=6, fig.height=5, fig.cap="Figure 1: Density plots of raw intensities for TMT-10plex experiment."----
intensityPlot(MSnset_data, title = "Peptide intensity distribution")
## ----boxplot, fig.width=6, fig.height=5, fig.cap="Figure 2: Boxplot of raw intensities for TMT-10plex experiment."----
intensityBoxplot(MSnset_data, title = "Peptide intensity distribution")
## ----rliplot, fig.width=6, fig.height=5, fig.cap="Figure 3: RLI of raw intensities for TMT-10plex experiment."----
rliPlot(MSnset_data, title = "Relative Peptide intensity")
## ----Corrplot, fig.width=6, fig.height=6, fig.cap="Figure 4: Correlation plot of peptide intensities"----
corrPlot(MSnset_data)
## ----hierarchicalplot, fig.width=6, fig.height=5, fig.cap="Figure 5: Clustering plot of peptide intensitites"----
exprs(MSnset_data) <- exprs(MSnset_data) + 0.01
hierarchicalPlot(MSnset_data)
## ----pcaplot, fig.width=6, fig.height=5, fig.cap="Figure 6: PCA plot of peptide intensitites"----
pcaPlot(MSnset_data, labelColumn = "BioRep", pointsize = 3)
## ----coverageplot, fig.width=6, fig.height=1.5, fig.cap="Figure 7: Peptide sequence coverage plot"----
mySequenceFile <- system.file("extdata", "P03372.fasta", package = "qPLEXanalyzer")
coveragePlot(MSnset_data,
ProteinID = "P03372",
ProteinName = "ESR1",
fastaFile = mySequenceFile)
## ----norm, fig.width=7, fig.height=7, fig.cap="Figure 8: Peptide intensity distribution with various normalization methods"----
MSnset_data <- MSnset_data[, -5]
p1 <- intensityPlot(MSnset_data, title = "No normalization")
MSnset_norm_q <- normalizeQuantiles(MSnset_data)
p2 <- intensityPlot(MSnset_norm_q, title = "Quantile")
MSnset_norm_ns <- normalizeScaling(MSnset_data, scalingFunction = median)
p3 <- intensityPlot(MSnset_norm_ns, title = "Scaling")
MSnset_norm_gs <- groupScaling(MSnset_data,
scalingFunction = median,
groupingColumn = "SampleGroup")
p4 <- intensityPlot(MSnset_norm_gs, title = "Within Group Scaling")
grid.arrange(p1, p2, p3, p4, ncol = 2, nrow = 2)
## ----annotation, eval=FALSE---------------------------------------------------
# library(UniProt.ws)
# library(dplyr)
# proteins <- unique(fData(MSnset_data)$Accessions)[1:10]
# columns <- c("ENTRY-NAME", "PROTEIN-NAMES", "GENES")
# hs <- UniProt.ws::UniProt.ws(taxId = 9606)
# first_ten_anno <- UniProt.ws::select(hs, proteins, columns, "UNIPROTKB") %>%
# as_tibble() %>%
# mutate(GeneSymbol = gsub(" .*", "", GENES)) %>%
# select(Accessions = "UNIPROTKB",
# Gene = "ENTRY-NAME",
# Description = "PROTEIN-NAMES",
# GeneSymbol) %>%
# arrange(Accessions)
# head(first_ten_anno)
## ----annotationReal, echo=FALSE-----------------------------------------------
library(dplyr)
proteins <- unique(fData(MSnset_data)$Accessions)[1:10]
filter(human_anno, Accessions%in%proteins) %>%
as_tibble() %>%
arrange(Accessions) %>%
head()
## ----summarize----------------------------------------------------------------
MSnset_Pnorm <- summarizeIntensities(MSnset_norm_gs,
summarizationFunction = sum,
annotation = human_anno)
## ----pepIntensity, fig.width=6, fig.height=5, fig.cap="Figure 9: Summarized protein intensity"----
peptideIntensityPlot(MSnset_data,
combinedIntensities = MSnset_Pnorm,
ProteinID = "P03372",
ProteinName = "ESR1")
## ----regress, fig.width=6, fig.height=4, fig.cap="Figure 10: Correlation between bait protein and enriched proteins before and after regression"----
data(exp3_OHT_ESR1)
MSnset_reg <- convertToMSnset(exp3_OHT_ESR1$intensities_qPLEX2,
metadata = exp3_OHT_ESR1$metadata_qPLEX2,
indExpData = c(7:16),
Sequences = 2,
Accessions = 6)
MSnset_P <- summarizeIntensities(MSnset_reg,
summarizationFunction = sum,
annotation = human_anno)
MSnset_P <- rowScaling(MSnset_P, scalingFunction = mean)
IgG_ind <- which(pData(MSnset_P)$SampleGroup == "IgG")
Reg_data <- regressIntensity(MSnset_P,
controlInd = IgG_ind,
ProteinId = "P03372")
## ----diffexp------------------------------------------------------------------
contrasts <- c(DSG.FA_vs_FA = "DSG.FA - FA")
diffstats <- computeDiffStats(MSnset_Pnorm, contrasts = contrasts)
diffexp <- getContrastResults(diffstats,
contrast = contrasts,
controlGroup = "IgG")
## ----MAplot, fig.width=6,fig.height=4, fig.cap="Figure 11: MA plot of the quantified proteins"----
maVolPlot(diffstats, contrast = contrasts, plotType = "MA", title = contrasts)
## ----volcano, fig.width=6, fig.height=4, fig.cap="Figure 12: Volcano plot of the quantified proteins"----
maVolPlot(diffstats, contrast = contrasts, plotType = "Volcano", title = contrasts)
## ----info,echo=TRUE-----------------------------------------------------------
sessionInfo()
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