New to mass spec data analysis
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@dan_reichert-12756
Last seen 7.6 years ago

I am new to Mass Spec data analysis and am trying to find a good start to the analysis of a fairly large data set.  I would like to use XCMS as I think it is my best option at this point.  I have looked at and used XCMSonline but would like more freedom than that allows.  Does anybody know of some links to good, entry level, data analysis tutorials?  Or maybe you have some script that you commonly use for untargeted metabolomics analysis you are willing to share, I can read and use most of xcms R code I have encountered but am having some trouble putting it all together at once.

Thank you

data analysis xcms Tutorial • 1.9k views
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Johannes Rainer ★ 2.1k
@johannes-rainer-6987
Last seen 28 days ago
Italy

If you're starting with xcms I suggest you use the new xcms user interface which will be officially available with the upcoming Bioconductor release (version 3.5, will be released end of April). If you want to use it already now, you can try to get it from github (https://github.com/sneumann/xcms).

library(devtools)
install_github("sneumann/xcms")

While usually not suggested, you can install developmental versions directly from github (safe here, since xcms is pretty stable and we don't plan to change anything prior release).

One big advantage of this version of xcms is that the help pages have been extended. All parameters and functions are described. A starting point might be the "new_functionality" vignette. Play with that and try to understand your data and look at the raw signal you've got

Finding the correct settings for e.g. the chromatographic peak detection is however tricky and really depends on your setting. So there won't be any default settings that work for all methods. The best is to define them based on what you expect (e.g. what retention time width your peaks will most likely have), run the peak detection and investigate (ideally if you've got internal controls) how the peaks look like, i.e. whether the peak detection succeeded in identifying the peaks (thinking it over, I might add an example to the "new_functionality" vignette). A tool that helps to determine good initial settings for your data is the IPO Bioconductor package.

Also, since your data set is large, I suggest that you first start investigating using a subset, ideally, if you have, pooled samples (also, run IPO on these to determine the best initial settings for peak detection).

Hope this helps a little.

cheers, jo

 

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Hello Johannes sir, I was going through the above comment but everything is not understandable I need your kind help, as I am a beginner, please guide me with any tutorial or step-by-step description by which I can analyze the metabolomics data generated from LC-MS.

Still, now I have read the LC-MS data into r studio with readMSData command no idea what things to do further. I know there are some steps further e.g.,. peak picking, alignment, etc. can you tell me the outline/workflow and how can I analyze the data?

Thanks in advance.

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Sure! We have several tutorials. A good starting point is always the package vignette - in your case, for LC-MS data analysis, I suggest to start with the xcms vignette (which is installed along with the package; it is also available here online).

Then, there is also the xcmsTutorials tutorial - that comes with a docker image etc. To view the tutorial online you can click on the "Articles" in the linked page.

Finally, we are working on a more complete workflow for the whole data analysis (actually, a compendium of different tutorials related to LC-MS metabolomics analysis). It's still work in progress, but you can already access the current version here.

Hope these help you to get started.

Best, jo

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Thanks for your kind responses.

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