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  • Nov 19 20:21

    wenbostar on master

    Updated Heatmap function (compare)

  • Nov 19 19:58

    wenbostar on master

    Updated Heatmap function (compare)

  • Nov 19 19:35

    wenbostar on master

    Updated Heatmap function (compare)

  • Nov 19 06:21

    wenbostar on master

    Updated Heatmap function (compare)

  • Nov 19 05:45

    wenbostar on master

    Updated to support latest Heatm… Merge branch 'master' of https:… (compare)

  • Oct 31 15:28
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  • Oct 18 12:41
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    wenbostar on master

    Update README.md (compare)

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  • Oct 17 19:38
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Bo
@wenbostar
@cdshekhar , can you send me your .csv XCMS file and .txt file so that I can debug based on this file? I'm sure this is the easiest way to find the problem.
And if it's possible, maybe you can open an new issue to describe you problem and upload your data, your R script in this issue.
wtpku
@wtpku
Dear Bo. You did an excelent job. However, i met with something error in using metaX. I am trying to use the Normalization module in metaX pacakage to fix my data. Although it did work with your example data, it returns "Error in checkForRemoteErrors(val) :
one node produced an error: error in runFit!" with my data. So i wonder if it is the problem of my data? But i did exactly as your example data.
By the way, i work in OS 10.14.1 and Rstudio Version 1.1.456 . Thanks
Information about traceback():
8: stop("one node produced an error: ", firstmsg, domain = NA)
7: checkForRemoteErrors(val)
6: staticClusterApply(cl, fun, length(x), argfun)
5: clusterApply(cl = cl, x = splitList(X, nchunks), fun = lapply,
FUN = fun, ...)
4: do.call(c, clusterApply(cl = cl, x = splitList(X, nchunks), fun = lapply,
FUN = fun, ...), quote = TRUE)
3: parLapply(cl, unique(qcData$ID_batch), .runFit1, qcData = qcData,
maxOrder = maxOrder)
2: doQCRLSC(para, cpu = 1)
1: doQCRLSC(para, cpu = 1)
Bo
@wenbostar
Bo
@wenbostar
@wtpku , can you send the data file to me?
wtpku
@wtpku
I'm sorry, i thought it was your email. But how?
Bo
@wenbostar
You can send me your data file and your script by email: wenbostar@gmail.com
wtpku
@wtpku
Thank you. On it
Bo
@wenbostar
I just edited your latest reply by deleting the data in the text. It's too long.
wtpku
@wtpku
Right. Thank you
Bo
@wenbostar
I received your data. I will take a look later.
wtpku
@wtpku
ok~
Bo
@wenbostar
Hi @wtpku , I just replied.
Please let me know if you have any questions.
zhangshaohui666
@zhangshaohui666
hi,@wenbostar , I want get ROC curve ,but the code in ROC.R , I cat't get if
image.png
Bo
@wenbostar
Could you open an issue providing more details about what your data type at github?
zhangshaohui666
@zhangshaohui666
image.png
the csv format for mrtaX
metaX
image.png
the parameter I choose doROC = TRUE, but I can't get the ROC curve
zhangshaohui666
@zhangshaohui666
Thank you for your reply
Bo
@wenbostar
@zhangshaohui666, could you send me your input data and R code so that I can reproduce the problem?
zhangshaohui666
@zhangshaohui666
ok I will send you email ,thank you
zhangshaohui666
@zhangshaohui666
Can you received my data@?@wenbostar
message is returned
zhangshaohui666
@zhangshaohui666
Bo
@wenbostar
@zhangshaohui666, I received the data. I will look into this issue and get back to you soon.
zhangshaohui666
@zhangshaohui666
thank 有
thank you
Bo
@wenbostar
Hi @zhangshaohui666, it looks your data has 4 groups and each group only has a few samples.
In this case, I don't think it's useful to generate an ROC plot.
In addition, there are two types of ROC analyses in metaX, one is classical univariate ROC analysis and the other is machine learning-based ROC analysis. Please find more details in metaX paper and the user's manual.
Bo
@wenbostar
The ROC analysis in metaXpipe function is the classical univariate ROC analysis which only gives you an AUROC value for each feature (or peak).
Bo
@wenbostar
If you really want to generate ROC for each feature, you can use calcAUROC function.
> x
 [1] 154726.20 147118.79  94937.37 111939.91 130151.19 105717.01 142826.74
 [8] 130269.16 106451.72 116157.33 123448.17 127098.84 132293.73 122711.53
[15] 120620.91 159892.17
> y
 [1] "F" "F" "F" "F" "F" "F" "F" "F" "H" "H" "H" "H" "H" "H" "H" "H"
> metaX:::calcAUROC(x,y,plot=TRUE)
image.png
This is an example for you.
zhangshaohui666
@zhangshaohui666
OK thank you
Bo
@wenbostar
@zhangshaohui666, it looks the version of metaX you used is a very old one. You can download the latest version at https://github.com/wenbostar/metaX.
zhangshaohui666
@zhangshaohui666
ok
ccgBiotechLover
@ccgBiotechLover
图片.png
图片.png
ccgBiotechLover
@ccgBiotechLover
图片.png
Dear author, I tried to importDataFromMetaboAnalyst() as the manual does, and wanted to run metaboliteAnnotation(), however, "Error in metaboliteAnnotation(para, db, delta = 10, mode = 1, unit = "ppm", :
please check your rawPeaks data, don't find valid mz column!
" returned. Another question is, what shall I input the parameter "db" when I run "metaboliteAnnotation", since I got an error message "Save data to file: metaX_result_neg/neg-peak2identification.txt
Error in paste("java -jar ", paste("\"", javabin, "\"", sep = ""), " -i ", :
找不到对象'db'
". Looking forward to your reply.
Bo
@wenbostar
@ccgBiotechLover , I will send you an example to show how to use this function in the next few days.
ccgBiotechLover
@ccgBiotechLover
@wenbostar ,looking forward to your reply, thank you.