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Messages - anlin00007

1
CAMERA / Downstream analysis after CAMERA
Hi All,

I am using xcms + camera for metabolomics analysis. After get the "annotated diffreport" file from camera, what should I do next for the database search? How to consider the "isotope" and "adducts" columns that generated by CAMERA?

Thanks
2
XCMS / Re: Fold Change Calculation in XCMS
Quote from: "hpbenton"
Umm.... I guess you could take the median or really just about any other stat. If there was reason to believe that the distribution was not normal then the median would make sense.

If could just be a difference be due to normalisation. (?) There are other ways of calculating the fold change, including bayesian methods (ref below). I just did a quick pubmed search I'm  sure there are more.

Cheers,

Paul

J Comput Biol. 2001;8(6):585-614.
Bayesian estimation of fold-changes in the analysis of gene expression: the PFOLD algorithm.
http://www.ncbi.nlm.nih.gov/pubmed/11747614

Hi Paul,

The fold change data is from xcmsonline results. So I guess the xcmsonline use other way to calculate fold change, like bayesian methods as you mentioned?
3
XCMS Online / Re: Fold Change Calculation in XCMS
Quote from: "Metasaur"
Sorry-i can't help with your problem. Is there any chance you could send me the sample data or post to the board? For some reason the data files on the homepage don't contain anything.
This would be of great help to me - Thanks!

featureidx   name   updown   METLIN_MSMS   fold   log2fold   pvalue   mzmed   rtmed   maxint   dataset1_mean   dataset2_mean
17   M351T28   DOWN   y   7.235694657   -2.855131528   2.43142E-05   351.1642528   27.50725   1174.720703   3023.966694   0

The data above is from the result table of COKE vs PEPSI xcmsonline demo. As we can see, the dataset2_mean is 0, however, there is a value in fold change. I wonder if there is some other method to substitute the 0 with a putative value.
4
XCMS Online / Fold Change Calculation in XCMS
Hi All,

Recently I found the XCMSonline has some other ways to calculate the fold change, not just mean1/mean2. For example, in the demo COKE vs Pepsi, the 17th record in the diffreport table. The fold change of that record is 7.235695, however, the mean of dataset2 is 0. I suppose there must be another way to calculate such kind of fold change. Can anyone tell me related method?
Thanks
5
XCMS / Fold Change Calculation in XCMS
Hi All,

Recently I found the XCMSonline has some other ways to calculate the fold change, not just mean1/mean2. For example, in the demo COKE vs Pepsi, the 17th record in the diffreport table. The fold change of that record is 7.235695, however, the mean of dataset2 is 0. I suppose there must be another way to calculate such kind of fold change. Can anyone tell me related method?
Thanks
6
XCMS / Re: ppm for UPLC and QTOF
Hi Paul,

I found in the log file of TNTvsSHAM project, they mentioned information below:
6. Diffreport
    class1     SHAM
    class2     TNT
    statistics.threshold.pvalue     0.001
    statistics.diffReport.value     into
I checked user manual of XCMS, but I did find any parameter in diffreport function that relate to "statistics.threshold.pvalue" and "statistics.diffReport.value". Do you know how to set up these parameters?
7
XCMS / Re: ppm for UPLC and QTOF
Quote from: "hpbenton"
anlin,

I dont' know what parameters you used in xcmsOnline. Are they identical settings? It seems a bit odd to have the prefilter set at 0 and 0. This would mean to look at peaks with 0 intensity that have 0 scans ie all noise and peaks/any signal. This could well be the reason for the difference. If the settings are identical check that the versions of xcms are the same between xcmsOnline and xcms.



Paul

Paul,

You are right the prefilter should be set up with other value. But I am little confused about the definition about "intensity" and "scan". Does it mean the number of occurrence for one mass trace among the test samples?
8
XCMS / Re: ppm for UPLC and QTOF
Quote from: "hpbenton"
anlin,

With CAMERA the results have been annotated. If you mean putting a metabolite name to them it depends on how and what you're using for identification. Searches such as Metlin allow for adduct searches and so consequently you can put the mzmed directly into metlin and tell it that it is an M+H ion (or whatever the CAMERA result is). KEGG searches will require the removal of the adduct to make the neutral mass.

Hope it helps, again let me know how you get on and if I answered everything :)

cheers,

Paul

Thanks again. I have combined xcms with camera and tested on the TNTvsSHAM public shared dataset. However, my local results have 10440 records, the xcmsonline just provide 9242 records under same parameter. I pasted my code below. Would you please check it? Thanks :)

# Calling Libraries
library(xcms)
library(CAMERA)

files <- list.files(myDir, pattern="*.mzXML", recursive=TRUE, full.names=TRUE)
paste(files)
pd <- xcms:::phenoDataFromPaths(files)
xset <- xcmsSet(files,method="centWave", nSlaves=3, prefilter=c(0,0), ppm=30, peakwidth=c(10,60), snthr=6,mzdiff=0.01)
xset <- group(xset)
## retcor.obiwarp {xcms}
xsetR <- retcor(xset, method="obiwarp",profStep=1,plottype = "deviation")
## group.density {xcms}
xsetR <- group(xsetR,bw=5, mzwid=0.025, minfrac=0.5, minsamp=1)
## fillPeaks-methods {xcms}
xset.finale <- fillPeaks(xsetR)
## Welch t-test (unequal variance)
report <- annotateDiffreport(xset.finale,sortpval=FALSE, nSlaves=3, sigma=6, perfwhm=0.6,
cor_eic_th=0.75, graphMethod="hcs", pval=0.05, calcCiS=TRUE,
calcIso=FALSE, calcCaS=FALSE, maxcharge=3, maxiso=4, minfrac=0.5,
ppm=5, mzabs=0.015, quick=FALSE, psg_list=NULL, rules=NULL,
polarity="positive", multiplier=3, max_peaks=100, intval="into",
pval_th = NULL, fc_th = NULL)

write.csv(report,"report1.csv")
9
XCMS / Re: ppm for UPLC and QTOF
Quote from: "hpbenton"
anlin,

Yes the (welches) T-test is evaluating the probability that the two classes come from the same distribution. Therefore, if the p-value is low there is a high probability that the classes are different. Given your chosen alpha (0.05 or 0.01 or 0.001 etc) you can say that they come from different distributions and therefore are from different classes. The T-stat can be used to find which way around the p-vaule is ie which class is 'upregulated' or 'down regulated'.

Hope it helps,

Paul

Hi Paul,

That's really helpful. Thanks. And I got one more question. After completed XCMS and CAMERA analysis, I got the annotated Diffreport file. If I want to annotate the results based on mz value, can I use the mzmed column as a query directly? Do I need to consider the mass of proton and ppm?
10
XCMS / Re: ppm for UPLC and QTOF
Quote from: "hpbenton"
anlin,

This means that your data has a higher resolution than the 30 ppm norm and the samples have some very close peaks. I would have to try different values but try using 15, then 10, then 5 until the warning stops.Note you can also go too low!

Quote
And for the diffreport, after the t-test, do we still have all the data or it's already been cut off by a default threshold?
I'm not fully sure what you mean. The only threshold you have done is when you did the grouping by using the minfrac parameter. The normal for this parameter is set at 50%. Meaning that a sample needs to be seen in at least 50% of the samples for each class.

Quote
When perform the annotation, can I just use the values in "mzmed" column with considering proton mass and delta mass? Do I need to calculate isotopes and different adducts?
I would have a look at the CAMERA package put together by Steffen Neumann's group. It's a very nice package and will identify you isotopes and adducts in the dataset. If something does not get identified with and adduct then it will be difficult to simply use the mzmed value +H for identification purposes.

Hope it helps, let us know if I didn't really answer the questions :)

Cheers,

Paul

Hi Paul,

Thanks. Your reply is very helpful. For the second question, I just want to know the meaning of t-test in diffreport. Does it measure the differential expression between control and case group?
11
XCMS / ppm for UPLC and QTOF
Hi All,

I am using XCMS for metabolomics analysis. The raw data is from UPLC+QTOF machine. When I use the centwave method and set the ppm as 30, the software always show me the warning: "There are 5533 peak data insertion problems. Please try lowering the 'ppm' parameter."  Which range should be suitable for the ppm in UPLC+QTOF?

And for the diffreport, after the t-test, do we still have all the data or it's already been cut off by a default threshold?

When perform the annotation, can I just use the values in "mzmed" column with considering proton mass and delta mass? Do I need to calculate isotopes and different adducts?