In protViz/cswd: Computing Dynamic SWATH Windows

!!!Caution work in progress!!!

library(bibliospec)
knitr::opts_chunk$set(echo = FALSE,
                      warning = FALSE,
                      message = FALSE,
                      results = "hide",
                      fig.width = 7,
                      fig.height = 4.5)

blib <- Blib()
datdir <- "inst/singleProteomeDats/"
files <- dir(datdir)
files <- grep("*\\.dat$", files, value=TRUE)

# blib$build(file.path(datdir,files), outfile = "inst/singleProteomeDats/All0_0.blib", cutoff=0.0)
# blib$build(file.path(datdir,files), outfile = "inst/singleProteomeDats/All0_95.blib", cutoff=0.95)
#
#
# blib$build(file.path(datdir,grep("Yeast",files,value=TRUE)), outfile = "inst/singleProteomeDats/YEAST0_95.blib", cutoff=0.95)
# blib$build(file.path(datdir,grep("ecoli",files,value=TRUE)), outfile = "inst/singleProteomeDats/ECOLI0_95.blib", cutoff=0.95)
# blib$build(file.path(datdir,grep("hela",files,value=TRUE)), outfile = "inst/singleProteomeDats/HELA0_95.blib", cutoff=0.95)

Data overview

library(bibliospec)
library(cdsw)

dbfile <- file.path(path.package("cdsw"), "extdata/tripleProteomeBlib/ECOLI0_95.blib")

All95 <- Bibliospec(dbfile)

peaks95 <- All95$getSpectraMeta()

peaks95 <- data.frame(mz = peaks95$precursorMZ, numpeaks = peaks95$numPeaks)
ms2coutns95 <- rep(peaks95$mz, peaks95$numpeaks)

par(mfrow=c(1,2))

h95 <- hist( peaks95$mz, breaks=400, xlab="MS1", main="" )
ms2h95 <- hist(ms2coutns95,breaks=400, xlab="MS2", ylab="MS2 peak frequency", main="")

mzStart <- 400
mzEnd <- 1100
nrWindows <- 20

Windows based on MS1 Information

\pagebreak

Classic

library(cdsw)
cdsw <- Cdsw( peaks95$mz[peaks95$mz>mzStart&peaks95$mz < mzEnd], nbins=nrWindows, digits=1 )
cdsw$constant_breaks(digits = 1)
cdsw$plot()
cdsw$showCycle()

knitr::kable(cdsw$asTable())

Quantile

cdsw$quantile_breaks(digits = 1)
cdsw$plot()
cdsw$showCycle()

knitr::kable(cdsw$asTable())

Quantile constrained

cdsw$sampling_breaks(maxwindow = 120,digits = 1,plot=TRUE)
cdsw$plot()
cdsw$showCycle()

knitr::kable(cdsw$asTable())

Optimizing ms2 peak distribution

Equalizing for number of MS2 in each DIA map.

Classic

library(cdsw)
cdsw <- Cdsw(ms2coutns95[ms2coutns95>mzStart& ms2coutns95 < mzEnd], nbins=nrWindows, digits=1 )

cdsw$constant_breaks(digits = 1)
cdsw$plot()
cdsw$showCycle()

knitr::kable(cdsw$asTable())


quantable::write.tab(cdsw$asTable(), file="d:/projects/p1000/tripleProteome/TripleProteomeWindows20Classic.txt")

Optimized Window

knitr::kable(cdsw$optimizeWindows(plot=TRUE))
quantable::write.tab(cdsw$optimizeWindows(), file="d:/projects/p1000/tripleProteome/TripleProteomeWindows20ClassicOptimized.txt")

Quantile

cdsw$quantile_breaks(digits = 1)
cdsw$plot()
cdsw$showCycle()

knitr::kable(cdsw$asTable())

Quantile Constrained

cdsw$sampling_breaks(maxwindow = 120,digits = 1,plot=TRUE)
cdsw$plot()
cdsw$showCycle()

knitr::kable(cdsw$asTable())
quantable::write.tab(cdsw$asTable(), file="d:/projects/p1000/tripleProteome/TripleProteomeWindows20VariableContstrained.txt")

Optimized Window

knitr::kable(cdsw$optimizeWindows(plot=TRUE))
quantable::write.tab(cdsw$optimizeWindows(), file="d:/projects/p1000/tripleProteome/TripleProteomeWindows20VariableContstrainedOptimized.txt")