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Topic: XCMS peak integration visualization (Read 1379 times) previous topic - next topic

XCMS peak integration visualization

I have quick question on peak integration visualization using xcms. What function should I use to visualize the peak integration after peak picking, ret correction, and grouping? I am not sure if getEIC will help. I am looking for something like I have attached. I want to see how my preprocessing methods have worked. I have attached image as an example for reference.

Thank you for your time.

Re: XCMS peak integration visualization

Reply #1
I would have a question which is very related to the one already asked here.
I can manage to plot EICs from grouped xcmsSet objects with something like the code below.

Code: [Select]
xeic.raw <- getEIC(test, rt = "raw", groupidx=1:4, sampleidx=4)
plot(xeic.raw, test, groupidx=1)

However, I was wondering if this is also possible for XCMS objects before they have been grouped. I would also like to check the performance of the peak integration.

Would be great if someone could help out with that.

Anyway thank you a lot for your time and efforts.


Re: XCMS peak integration visualization

Reply #2
In case anybody ever has the same problem:

Code: [Select]
Peaks_of_all_samples_for_one_found_feature <- getEIC(xcmsSet_object, groupidx = 1183)  #in this case the extracted feature is 1183
plot(Leucine, x) #this is the plot.xcmsEIC however, apparently the "xcmsEIC"-part must not be used for that command