Re: retention time correction for individual sample classes
Reply #3 –
Hi,
Check out the extra= and especially missing= parameter for retcor(). You can set missing probably
to something like 5% of your number of samples to catch those "too few overlapping compounds
between less similar sample classes"
I'd hope that the non-linear aspect is caught by the second round of group/retcor.
Yes, splitting is possible, but when I wrote the c() joining function, I had no idea how to handle
the RT correction. Should they just stay the same ? I had no really good answer.
A hack could involve manually working on the faahko@rt lists, which have the RT
for each raw file before/after the correction:
> str(faahko@rt)
List of 2
$ raw :List of 12
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
$ corrected:List of 12
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
..$ : num [1:1278] 2501 2503 2505 2506 2508 ...
Not sure what you mean here. peakwidt=(5,12) refers to peak picking.
Your issue is the group()ing step. There the important parameter is bw=seconds
for the kernel density estimation that is behind the grouping (cf. 2006 xcms paper
or the xcmsPreprocess vignette.
Maybe some more experimenting with the group/retcor parameters first
to get an acceptable xcmsSet without having to resort to hacking.
Maybe then a more directed hacking approach can tweak even more
out of the data.
You can also check http://metabolomics-forum.com/viewtopic.php?f=26&t=137
and there esp. the lower code snippet to cluster the samples w.r.t. their retention time profiles/deviation.
Yours,
Steffen