prozor (version 0.3.1)

Cdsw-class: 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

# NOT RUN {
data(masses)
cdsw <- Cdsw(masses)
tmp <- cdsw$sampling_breaks(maxwindow=100,plot=TRUE)
cdsw$plot()
cdsw$asTable()
cdsw$breaks
cdsw$optimizeWindows()
cdsw$showCycle()
# }