lcms {ptw} | R Documentation

## 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)

[Package ptw version 1.9-13 Index]