progressiveAlignment-class {flagme} | R Documentation |
Performs a progressive peak alignment (clustalw style) of multiple GCMS peak lists
progressiveAlignment(pD, cA, D=50, gap=.5, verbose=TRUE, usePeaks=TRUE, df=30, compress=TRUE, type=2)
pD |
a |
cA |
a |
D |
retention time penalty |
gap |
gap parameter |
verbose |
logical, whether to print information |
usePeaks |
logical, whether to use peaks (if |
df |
distance from diagonal to calculate similarity |
compress |
logical, whether to store the similarity matrices in sparse form |
type |
numeric, two different type of alignment function |
The progressive peak alignment we implemented here for multiple GCMS
peak lists is analogous to how clustalw
takes a set of pairwise
sequence alignments and progressively builds a multiple alignment. More
details can be found in the reference below.
progressiveAlignment
object
Mark Robinson
Mark D Robinson (2008). Methods for the analysis of gas chromatography - mass spectrometry data PhD dissertation University of Melbourne.
peaksDataset
, multipleAlignment
require(gcspikelite) ## paths and files gcmsPath <- paste(find.package("gcspikelite"), "data", sep="/") cdfFiles <- dir(gcmsPath, "CDF", full=TRUE) eluFiles <- dir(gcmsPath, "ELU", full=TRUE) ## read data, peak detection results pd <- peaksDataset(cdfFiles[1:2], mz=seq(50,550), rtrange=c(7.5,8.5)) pd <- addAMDISPeaks(pd, eluFiles[1:2]) ca <- clusterAlignment(pd, gap=.5, D=.05, df=30, metric=1, type=1) pa <- progressiveAlignment(pd, ca, gap=.6, D=.1, df=30, type=1)