createExperimentsFragmentOptimisation {topdownr} | R Documentation |
This function is used to create a tree-like list
of
all combinations of a user-given set of MS1 and TMS2 settings for an
fragment optimisation experiment. The list could be written to an
Orbitrap Fusion Lumos method xml file using writeMethodXmls()
.
createExperimentsFragmentOptimisation(ms1, ..., groupBy = c("AgcTarget", "replication"), nMs2perMs1 = 10, scanDuration = 0, replications = 2, randomise = TRUE)
ms1 |
|
... |
further named arguments with |
groupBy |
|
nMs2perMs1 |
|
scanDuration |
|
replications |
|
randomise |
|
list
, able to be written via xml2::as_xml_document()
writeMethodXmls()
,
expandMs1Conditions()
,
expandTms2Conditions()
## build experiments within R ms1 <- expandMs1Conditions( FirstMass=400, LastMass=1200, Microscans=as.integer(10) ) targetMz <- cbind(mz=c(560.6, 700.5, 933.7), z=rep(1, 3)) common <- list( OrbitrapResolution="R120K", IsolationWindow=1, MaxITTimeInMS=200, Microscans=as.integer(40), AgcTarget=c(1e5, 5e5, 1e6) ) cid <- expandTms2Conditions( MassList=targetMz, common, ActivationType="CID", CIDCollisionEnergy=seq(7, 35, 7) ) hcd <- expandTms2Conditions( MassList=targetMz, common, ActivationType="HCD", HCDCollisionEnergy=seq(7, 35, 7) ) etd <- expandTms2Conditions( MassList=targetMz, common, ActivationType="ETD", ETDReactionTime=as.double(1:2) ) etcid <- expandTms2Conditions( MassList=targetMz, common, ActivationType="ETD", ETDReactionTime=as.double(1:2), ETDSupplementalActivation="ETciD", ETDSupplementalActivationEnergy=as.double(1:2) ) uvpd <- expandTms2Conditions( MassList=targetMz, common, ActivationType="UVPD" ) exps <- createExperimentsFragmentOptimisation( ms1=ms1, cid, hcd, etd, etcid, uvpd, groupBy=c("AgcTarget", "replication"), nMs2perMs1=10, scanDuration=0.5, replications=2, randomise=TRUE ) ## use different settings for CID cid560 <- expandTms2Conditions( MassList=cbind(560.6, 1), common, ActivationType="CID", CIDCollisionEnergy=seq(7, 21, 7) ) cid700 <- expandTms2Conditions( MassList=cbind(700.5, 1), common, ActivationType="CID", CIDCollisionEnergy=seq(21, 35, 7) ) exps <- createExperimentsFragmentOptimisation( ms1=ms1, cid560, cid700, groupBy=c("AgcTarget", "replication"), nMs2perMs1=10, scanDuration=0.5, replications=2, randomise=TRUE ) ## use a CSV (or excel) file as input myCsvContent <- " ActivationType, ETDReactionTime, UVPDActivationTime UVPD,,1000 ETD,1000, " myCsvSettings <- read.csv(text=myCsvContent, stringsAsFactors=FALSE) myCsvSettings # ActivationType ETDReactionTime UVPDActivationTime # 1 UVPD NA 1000 # 2 ETD 1000 NA exps <- createExperimentsFragmentOptimisation( ms1 = data.frame(FirstMass=500, LastMass=1000), ## TMS2 myCsvSettings, ## other arguments groupBy="ActivationType" )