Best way to deconvolute metabolite data

[JasonBason]

Hello,

I have run a some code to identify and group features. Additionally, I have used dplyr to get a list of differential features specific to each sample.

Within these differential features is a lot of redundancy due to isotopes, in source fragmentation, adducts, etc.

Upon searching for a solution to deconvolute these features (ideally, I would just like the [M+2H] or [M+3H] features), there seems to be multiple solutions.

CAMERA, CliqueMS, the compounding workflow (in MSFeatures)...

I've tried exploring each of these options with varying levels of success (I'm pretty new to programming). Is there some advice that the community could offer? CAMERA in particular seems to be a favorite, but it requires an xcmsSet object rather than the newer XcmsExperiment object.

Alternatively, is there a deisotoping/deconvoluting function within xcms itself?

Thanks!

[jmorim]

I believe you can coerce xcmsExperiments using as(object, 'xcmsSet') which can be used by CAMERA