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91
Other / Re: Peak alignment with large dataset (over 2500 samples and growing)
Last post by Jan Stanstrup -
MZMine is know to use a lot of memory. I imagine that is where your bottleneck is. But you should check that.

XCMS is much more memory efficient. Be aware that each core will use a certain amount of memory. So on a system like yours not using all cores will use less memory and might save you if memory is your bottleneck. Also don't use 80 cores on processes that are bottlenecked by HDD reads (like reading the raw data).

That said, with 10,000 samples you really need to be careful about how greedy you need to be in terms of how low in intensity you want to pick.
92
Other / Peak alignment with large dataset (over 2500 samples and growing)
Last post by metabolon1 -
Dear all,

I am trying to process over 2500 files from a UPLC-QTOF-MS dataset. The goal is to eventually increase this number to 10,000 and beyond. Currently I am using MZmine 2. I am fortunate to have access to a big server (80 core, 350+ GB RAM). However, it seems that the peak alignment step is not optimized for this number of samples. See my other post for more details about this issue: https://github.com/mzmine/mzmine2/issues/518

Any ideas on a more efficient peak alignment method? As far as I can tell, the raw data are already pretty well aligned; the UPLC seems to be fairly consistent. My main objective right now is to get all the samples/peaks into a single matrix.

I am actively trying different approaches, but it all takes time. I am hoping that someone else who has trod this ground before can offer advice to help save time and effort.

Many thanks!
93
XCMS Online / About the MSMS matching through XCMS online
Last post by lijied -
Hello,

I am a new user of XCMS online and I have some questions about the XCMS data processing. I used the "single function" to process 2 technical replicate MSMS files. The Putative ID's (METLIN) of the analysis log shows that the analysis "Found 178 total, MS^2 spectra to match".

However, I couldn't find any information about these matches. I checked the results table as well. Could anyone please let me know where I can find the MSMS matching information in the result? Thank you very much. 
95
Tools / Re: Data from waters - mass measure in centroid mode
Last post by Jan Stanstrup -
What values are you comparing? How do you get a single m/z value from the profile mode data to compare to?
So there is the profile mode data, Waters centroided m/z and the msconvert centroided m/z. The last two will be different due to different centroiding algorithms. The documentation says the CWT method is not very good. You could use Waters centroiding (if that is the one that is good?) if you centroid in masslynx first (to new raw file) and then convert without any additional processing.

Alternatively the R package MSnbase might have more advanced alternatives: https://github.com/lgatto/MSnbase/blob/11c336ebdc3e78cfa404803eb907346b046cd38b/vignettes/v03-MSnbase-centroiding.Rmd
96
Tools / Data from waters - mass measure in centroid mode
Last post by Schmitz -
Dear all

We work with a synapt G2, Waters, drived with masslynx software. We work in profile mode currently and we apply the correction along the run.

When I convert my data with MS convert, and I check with insilico viewer the peak picking, I observe that the value is the value corresponding to the profile value in masslynx but not to the centroid value. This induces an error of 10 to 15 ppm compared to the exact mass value, instead of 2 to 5 ppm.

Do anyone have a solution to this problem? I checked the filter lockmass refiner but it didn’t work (first filter lockmass refiner then filter peak picking with CWT algorithm).

Thanks
99
Birmingham Metabolomics Training Centre / Introduction to Metabolomics for the Environmental Scientist Training Course
Last post by eppsd -
Venue: Birmingham Metabolomics Training Centre, School of Biosciences, University of Birmingham, Birmingham, UK.
Dates: 28 February - 1 March 2019
Level: The course is suitable for individuals with no previous experience of metabolomics.

Overview
This 2-day NERC-funded Advanced Training Short Course provides environmental scientists with an overview of the metabolomics pipeline. The course is intended for environmental scientist with little or no previous experience of metabolomics and who are interested to discover how this relatively new and powerful approach could be integrated into their research. Experts working in the NERC Metabolomics facility NBAF-B will teach the course.

Topics include:
  • Introduction to environmental metabolomics with case studies
  • Experimental design and quality control
  • Sample collection and preparation
  • Overview of analytical laboratory techniques (mass spectrometry and NMR spectroscopy)
  • Short practical demonstrations and a tour of the metabolomics facilities
  • Overview of data processing and statistics for metabolomics
  • Introduction to metabolite identification
  • Q&A session with an opportunity for course leads to provide advice on your own metabolomics studies

Bursaries: A limited number of bursaries are available for PhD students funded by NERC.

For further information and registration details, please visit http://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/sample-analysis.aspx or contact bmtc@contacts.bham.ac.uk.
100
Birmingham Metabolomics Training Centre / Introduction to Metabolomics for the Clinical Scientist Training Course
Last post by eppsd -
Venue: Birmingham Metabolomics Training Centre, School of Biosciences, University of Birmingham, Birmingham, UK.
Dates: 11 March 2019 | 25 October 2019
Level: The course is suitable for individuals with no previous experience of metabolomics.

Overview
This 1-day course in partnership with the Phenome Centre Birmingham provides clinicians with an overview of the metabolomics pipeline highlighting the benefits of this technique to the medical field and an introduction to the Phenome Centre Birmingham and the MRC-NIHR National Phenome Centre.

The course provides a suitable introduction to metabolomics prior to taking additional training courses at either the Birmingham Metabolomics Training Centre or the Imperial International Phenome Training Centre.  

Topics include:
  • Introduction to the Phenome Centre Birmingham, showcasing facilities and expertise available.
  • Introduction to metabolomics
  • Importance of experimental design and sample collection
  • Overview of the technologies available for data acquisition including discovery phase profiling and targeted analysis for the validation of biomarkers
  • Overview of data analysis approaches
  • Case studies – large-scale metabolic phenotyping, translation to targeted assays and clinical practice
  • Question and answer session with the experts

Bursaries: A limited number of bursaries are available for PhD students funded by NERC.

For further information and registration details, please visit http://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/sample-analysis.aspx or contact bmtc@contacts.bham.ac.uk.