library("pRolocdata")
library("MSnbase")
data("hyperLOPIT2015ms3r1psm")
vars <- c("Sequence", "Protein.Descriptions", "X..Proteins",
"Protein.Group.Accessions", "Modifications", "q.Value", "PEP",
"IonScore", "X..Missed.Cleavages", "Isolation.Interference....",
"Ion.Inject.Time..ms.", "Intensity", "Charge", "m.z..Da.", "MH...Da.",
"Delta.Mass..PPM.", "RT..min.", "markers")
hlpsms <- ms2df(selectFeatureData(hyperLOPIT2015ms3r1psm, fcol = vars))
names(hlpsms) <- gsub("\\.", "", names(hlpsms))
names(hlpsms) <- gsub("XProteins", "NbProteins", names(hlpsms))
names(hlpsms) <- gsub("XMissedCleavages", "NbMissedCleavages", names(hlpsms))
for (i in seq_along(hlpsms))
if (is(hlpsms[[i]], "factor"))
hlpsms[[i]] <- as.character(hlpsms[[i]])
## 2020-08-12: subset the data.frame to save space, but keep the STAT1 and STAT3
## features (used in the vignette)
stats <- grep("STAT", hlpsms$ProteinDescriptions)
set.seed(123)
k <- sample(nrow(hlpsms), 3000)
hlpsms <- hlpsms[sort(union(k, stats)), ]
save(hlpsms, file = "../../data/hlpsms.rda", compress = "xz", compression_level = 9)
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