Cdsw-class: Compute dynamic swath windows

In protViz/prozor: Minimal Protein Set Explaining Peptide Spectrum Matches

Compute dynamic swath windows

Description

initialize

create equidistant breaks

quantile breaks

sampling breaks

barplot showing the number of precursors per window

Table with window boundaries and statistics

summary of the binning process (see objectiveMS1Function for more details)

moves window start and end to region with as few as possible precursor masses

shows the generated DIA cycle

Arguments

list	of masses
nbins	number of bins default 25
maxwindow	largest window size
minwindow	smallest window size
digits	mass precision default 2
digigits	mass precision
max	number of bins
plot	default TRUE
overlap	size of window overlap default 1 m/z

Value

array of masses

array with masses

array with masses

data.frame with columns: - from (window start) - to (window end) - mid (window centre), width (window width) - counts expected number of precursors

list with optimization scores

data.frame with optimized windows

Fields

masses

MS1 masses

breaks

the breaks

nbins

number of bins

digits

mass accuracy in result

Methods

asTable(overlap = 1)

make windows

error()

show error

optimizeWindows(digits = 1, maxbin = 15, plot = FALSE, overlap = 0)

optimizes the windows

quantile_breaks(digits = 2)

same number of MS1 in each window but might violate hard constraints

sampling_breaks(maxwindow = 150, minwindow = 5, digits = 2, plot = FALSE)

starts with quantile breaks but mixes with uniform data to satisfy had constraints

Examples

data(masses)
cdsw <- Cdsw(masses)
tmp <- cdsw$sampling_breaks(maxwindow=100,plot=TRUE)
cdsw$plot()
cdsw$asTable()
cdsw$breaks
cdsw$optimizeWindows()
cdsw$showCycle()

protViz/prozor documentation built on Oct. 17, 2023, 6:39 p.m.