In protViz/cswd: Computing Dynamic SWATH Windows

!!!Caution work in progress!!!

Introduction

Function optimizes Extraction windows so we have the same number of precursor per window. To do it uses spectral library or non redundant blib.

Prerequisites

library(cdsw)

Constant with method

cdsw <- Cdsw(masses)
cdsw$plot()

knitr::kable(cdsw$asTable())

Error

constError <-cdsw$error()

Classical Method based on quantile

Same number of MS1 precursors in each window

cdsw$quantile_breaks()

cdsw$plot()

knitr::kable(cdsw$asTable())

Error

quantileError <- cdsw$error()

Adjust windows

Shifts window start and an to a mass range with few MS1 peaks.

knitr::kable(cdsw$optimizeWindows(maxbin=10,plot=TRUE))

Iterative Distribution Mixing based cdsw

Requirements

• Mass range can be specified (mass_range)
• Maximal window size can be specified (max_window_size). This is because windows should not be to large because of optimal collision energy (personal communication by Bernd R.).
• Minimal window size can be specified (min_window_size).
• target number of windows can be specified (nr_windows).
• boundaries between windows are placed in regions were no precursors are observed.

cdsw$sampling_breaks(maxwindow = 100,plot = TRUE)

cdsw$plot()

knitr::kable(cdsw$asTable())

Error

mixedError <-cdsw$error()

Errors

barplot(c(const = constError$score1, quantile = quantileError$score1, mixed = mixedError$score1),ylab="Manhattan distance")
barplot(c(const = constError$score2, quantile = quantileError$score2, mixed = mixedError$score2),ylab="Euclidean distance")

Session info

Here is the output of sessionInfo() on the system on which this document was compiled:

sessionInfo()

protViz/cswd documentation built on May 19, 2020, 1:03 a.m.