We're planning a face change to METLIN in the near future with some added extra's. We'll see to it that there is also an option of removing the metabolites with insilico MS/MS data from the searches. We haven't published anything on the MS/MS generation yet we have used a lot of the competitive fragment modeling ideas.
Ah .. Sorry I thought I knew you from Dr. González - my Bilbao circle misinforms me.
First let me say that I'm sorry to hear that you are unhappy with our efforts. We have been doing a lot of developments with MS/MS data in the past few months and while not all of the spectra perfectly align, based on our initial review of the data with compounds that we did not have MS/MS data on, we feel that the in silico data does add value.
To address your concerns that the spectra are not labeled clearly as "in silico" we will make the words “in silico” bigger so that it is now clearer. If you do not think that the in silico spectra are usable for your research in their current form please feel free to ignore them on the site. We have heard directly from many users that this new addition has been very helpful, and while not perfect they are happy to have this new information.
Finally let me thank Dr. Salek who contacted me via the METLIN contact page to alert me to this thread. I have attached an image of the where you can contact us from the METLIN website.
You could also look at XCMS Online. In the mobile app we have release a quick EIC sorter named Hot or Not. This allows you to quickly annotate the good and bad EICs in the dataset. The annotations can then be used as a filter in the table view.
Unfortunately, browser support for java is being phased out. With this and the added security issues with java we are developing a new uploader which is still in beta at the moment but is being set to high priority. For the time being I recommend using the HTML5 uploader. You can see a video on how to change your uploader type via the XCMS Institute videos here: https://xcmsonline.scripps.edu/landing_ ... =institute and direct link to the video here: https://www.youtube.com/watch?v=qaCv-Q9hVFk
I hope this helps questions are answered the fastest via our direct email on contact page.
Cheers,
Paul
~~ H. Paul Benton Scripps Research Institute If you have an error with XCMS Online please send me the JOBID and submit an error via the XCMS Online contact page
With the new update we have had a few sporadic bugs. We noticed this one the other day and have a fix in our internal development system. We need to do a few more tests and create a unit test for it before release. Release however, should be soon. However, in the mean time please email me directly either via the xcmsonline email or mine. You can find me on the scripps site. I'm hesitant to put down my email address for fear of spam.
Cheers,
Paul ~~ H. Paul Benton Scripps Research Institute If you have an error with XCMS Online please send me the JOBID and submit an error via the XCMS Online contact page
This has happened because one or more than one of the p-values were not calculated and are NA's. This could be due to the all classes having the same intensity values and so the test could not be completed for that feature. For q-value calculation the p-value distribution is required. Missing values make the distribution uncertain and so q-values are therefore not calculated.
If you use the downloaded results, there is a column called 'npeaks' next to this column is each class label. You can then uses these column to filter out the features that are present in just one class, two classes etc. You can of course start to filter with more filters eg a p-value and or fold change filter as well.
Currently, XCMS Online does not support MSe data nor MS/MS data. There is some work in the development pipeline to use MS/MS data for identification. However, MSe data can be very difficult to correlate to the correct precursor. Other methods similar to MSe also suffer from these problems.
All features are seen in the results table which pass the minfrac cut off. Minfrac is a robustness filter to make sure that the feature is seen reproducibly across the class group. If minfrac is set at 50% (ie 0.5) then we have to see feature X in at least 50% of the samples for class 1. For example, if we have 3 classes WT, MUT-1, MUT-2. Each class has 6 samples each. A feature will appear in the report if the feature is seen/detected in at least 3 samples (50%) of any one class. So, we could see feature X in the samples of WT 3 times but not see them in the MUT-1 samples or the MUT-2 samples and the feature X would still appear in the report. However, if feature Y was seen 2 times in the samples of class WT, 1 sample of MUT-1 and in 2 samples of MUT-2 then it would not pass the minfrac filter.
Hope this helps and sorry for the delay in response.
I'm not sure that I understand. The features are significant when they the p-value, for that individual feature, falls below the designated alpha value in the statistics tab. However, regardless of this all detected features (with the exception of the features removed by minfrac) will appear in the results table. Features that are significant will have EIC, boxplots and spectral plots. If you are not seeing these please submit an error report via the xcmsonline contact page.
Maximum intensity corrosponds to the peak height. This value is know to be highly variable in a dataset for the same peak. However, peak area is a much more robust measurement. There are certain situations where peak height is desired however, mostly this is just to get the correct plotting parameters for the EIC's
XCMS doesn't calculate the adducts and isotopes. An extension package called CAMERA developed by Steffen Neumanns group takes care of this part of the analysis. The paper is an easy read and highly worth while. There is also the programtic explanation of camera here : http://www.bioconductor.org/packages/re ... CAMERA.pdf
As for XCMS Online there are some additional steps which are performed to check accuracy of the hits. This area is a hot topic for development and hopefully we will be releasing some new code early next year.
http://www.ncbi.nlm.nih.gov/pubmed/22111785 Anal Chem. 2012 Jan 3;84(1):283-9. doi: 10.1021/ac202450g. Epub 2011 Dec 12. CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets. Kuhl C1, Tautenhahn R, Böttcher C, Larson TR, Neumann S.
On XCMS Online you can see what parameters you have used by viewing the parameter set or after the job is completed looking at the log file. The parameters below do not match the default XCMS Online Waters TOF parameter set. However, you may have changed these parameters. I would need the parameter id to know more specifically.
