View source: R/purityD-dims-purity.R
dimsPredictPuritySingle | R Documentation |
Given a an DI-MS dataset (either mzML or .csv file) calculate the predicted purity for a vector of mz values.
Calculated at a given offset e.g. for 0.5 +/- Da the minOffset would be 0.5 and the maxOffset of 0.5.
A ppm tolerance is used to find the target mz value in each scan.
dimsPredictPuritySingle(
mztargets,
filepth,
minOffset = 0.5,
maxOffset = 0.5,
ppm = 2.5,
mzML = TRUE,
iwNorm = FALSE,
iwNormFun = NULL,
ilim = 0.05,
mzRback = "pwiz",
isotopes = TRUE,
im = NULL,
sim = FALSE
)
mztargets |
vector = mz targets to get predicted purity for |
filepth |
character = mzML file path or .csv file path |
minOffset |
numeric = isolation window minimum offset |
maxOffset |
numeric = isolation window maximum offset |
ppm |
numeric = tolerance for target mz value in each scan |
mzML |
boolean = Whether an mzML file is to be used or .csv file (TRUE == mzML) |
iwNorm |
boolean = if TRUE then the intensity of the isolation window will be normalised based on the iwNormFun function |
iwNormFun |
function = A function to normalise the isolation window intensity. The default function is very generalised and just accounts for edge effects |
ilim |
numeric = All peaks less than this percentage of the target peak will be removed from the purity calculation, default is 5% (0.05) |
mzRback |
character = backend to use for mzR parsing |
isotopes |
boolean = TRUE if isotopes are to be removed |
im |
matrix = Isotope matrix, default removes C13 isotopes (single, double and triple bonds) |
sim |
boolean = TRUE if file is from sim stitch experiment. Default FALSE |
a dataframe of the target mz values and the predicted purity score
mzmlPth <- system.file("extdata", "dims", "mzML", "B02_Daph_TEST_pos.mzML",
package="msPurityData")
predicted <- dimsPredictPuritySingle(c(173.0806, 216.1045), filepth=mzmlPth,
minOffset=0.5, maxOffset=0.5, ppm=5, mzML=TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.