ptw (version 1.9-16)

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 (samples 1, 2 and 5) of a larger set measured on a tryptic digest of E. coli proteins (see source section). Separate objects mz and rt give the values for the first two axis.

Peak picking leads to the object ldms.pks (see example section).

Usage

data(lcms)

References

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

Examples

# NOT RUN {
## 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)))
                   })
# }