library("MSnID")
data(c_elegans)
test_infer_parsimonious_accessions_old <- function(){
# explicitely adding parameters that will be used for data filtering
msnidObj$msmsScore <- -log10(msnidObj$`MS-GF:SpecEValue`)
msnidObj$absParentMassErrorPPM <- abs(mass_measurement_error(msnidObj))
# quick-and-dirty filter. The filter is too strong for the sake of saving time
# at the minimal set of proteins inference step.
msnidObj <- apply_filter(msnidObj, 'msmsScore > 12 & absParentMassErrorPPM < 2')
msnidObj2 <- infer_parsimonious_accessions(msnidObj)
checkEqualsNumeric(length(proteins(msnidObj2)), 551)
}
# Above is the old function for testing protein inference. I'll leave it for
# now. Below is the new way, where first all the inference will be done
# outside of the test functions.
# explicitely adding parameters that will be used for data filtering
msnidObj$msmsScore <- -log10(msnidObj$`MS-GF:SpecEValue`)
msnidObj$absParentMassErrorPPM <- abs(mass_measurement_error(msnidObj))
# quick-and-dirty filter. The filter is too strong for the sake of saving time
# at the minimal set of proteins inference step.
msnidObj <- apply_filter(msnidObj, 'msmsScore > 12 & absParentMassErrorPPM < 2')
# checking with razor peptide
msnidObj.r <- infer_parsimonious_accessions(msnidObj, unique_only=FALSE)
# checking unique peptides only
msnidObj.u <- infer_parsimonious_accessions(msnidObj, unique_only=TRUE)
test_infer_parsimonious_accessions_number.r <- function(){
checkEqualsNumeric(length(proteins(msnidObj.r)), 551)
}
test_infer_parsimonious_accessions_number.u <- function(){
checkEqualsNumeric(length(proteins(msnidObj.u)), 427)
}
test_infer_parsimonious_accessions_hash.r <- function(){
checkIdentical(digest(psms(msnidObj.r)$accession),
'e8ff9bbf36929ce49850733b3640edc8')
}
test_infer_parsimonious_accessions_hash.u <- function(){
checkIdentical(digest(psms(msnidObj.u)$accession),
'2a375d3ec85d022aeba5d210bca55a53')
}
# Future challenges is to come up with tests that check inference that is
# done outside of MSnID object
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