ptw (version 1.9-11)

lcms: Parts of 3 proteomic LC-MS samples

Description

The lcms data consists of a 100 x 2000 x 3 array lcms, a vector time of length 2000 and a vector mz of length 100. The LC-MS data in the array are a subset of a larger set measured on a tryptic digest of E. coli proteins. Peak picking leads to the object ldms.pks (see example section).

Usage

data(lcms)

Source

Nijmegen Proteomics Facility, Department of Laboratory Medicine, Radboud University Nijmegen Medical Centre

References

Bloemberg, T.G., et al. (2010) "Improved parametric time warping for Proteomics", Chemometrics and Intelligent Laboratory Systems, 104 (1), 65 -- 74.

Examples

## the lcms.pks object is generated in the following way:
## Not run: 
# data(lcms)
# pick.peaks <- function(x, span) {
#   span.width <- span * 2 + 1
#   loc.max <- span.width + 1 -
#       apply(embed(x, span.width), 1, which.max)
#   loc.max[loc.max == 1 | loc.max == span.width] <- NA
#   
#   pks <- loc.max + 0:(length(loc.max)-1)
#   pks <- pks[!is.na(pks)]
#   pks.tab <- table(pks)
#   
#   pks.id <- as.numeric(names(pks.tab)[pks.tab > span])
#   
#   cbind(rt = pks.id, I = x[pks.id])
# }
# 
# ## bring all samples to the same scale, copied from ptw man page
# lcms.scaled <- aperm(apply(lcms, c(1,3), 
#                            function(x) x/mean(x) ), c(2,1,3))
# lcms.s.z <- aperm(apply(lcms.scaled, c(1,3), 
#                         function(x) padzeros(x, 250) ), c(2,1,3))
# lcms.pks <- lapply(1:3,
#                    function(ii) {
#                      lapply(1:nrow(lcms.s.z[,,ii]),
#                             function(jj)
#                             cbind("mz" = jj,
#                                   pick.peaks(lcms.s.z[jj,,ii], 5)))
#                    })
# ## End(Not run)