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1
Mass spectrometry / Re: Experimental design for multiple-batch study
Last post by djb17 -
Given that, how different are the distributions?
Say there are 3 conditions, where all samples were randomly assigned to. It would be fine to have one batch with 30/40/50 samples from each treatment (assuming they are run in a randomized order). However, it wouldn't be good to have a distribution of something like 50/0/60. Even worst would be 10/0/100.

I'm talking about the extreme case (e.g. 10/0/100). So is it correct to say that, even if the pooled QC was created from all of the samples in the experiment, the resulting data would have issues because of the unbalanced distribution of the samples (after correction, normalization, etc...)?

If this is the case, what happens during the experiment as a result of the imbalance that leads unusable/low-quality data?

Thank you so much for your feedbacks! Learning so much from you all  :D
2
XCMS Online / Zero Files to Save
Last post by xjessicak6 -
Hello!

I am currently trying to upload an mzxml data file as a dataset on XCMS online, and whenever I try I keep on getting the message "Warning: There is/are zero file(s) to save."

Does anyone know why I am constantly getting this message, and how to fix this issue?

Thank you!
3
Birmingham Metabolomics Training Centre / Birmingham Metabolomics Training Centre - 2020 face-to-face course list
Last post by BMTC -

Birmingham Metabolomics Training Centre 2020 face-to-face course list

We offer a range of metabolomics courses suitable for scientists with a range of experience in metabolomics, from introductory courses for those interested in learning more about the study, to experienced PDRA's looking to expand their knowledge of equipment and sampling.

birmingham.ac.uk/bmtc



2020 Course list:


Multiple Biofluid and Tissue Types, From Sample Preparation to Analysis Strategies for Metabolomics
10 - 12 February 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Multiple-biofluid-and-tissue-types-from-sample-preparation-to-analysis-strategies-for-metabolomics-February-2020.aspx

This 3-day course provides a theoretical overview and hands-on training to apply multiple sample preparation and UPLC-MS methods to characterise the metabolomes of complex biological samples using the mass spectrometer (Xevo QToF G2-XS - a maximum of 4 people working on the instrument in a session). The course is led by experts in the field who have experience of the analysis of microbial, plant and mammalian samples, and illustrates the different approaches that are available to analyse a range of biological samples and applying complementary liquid chromatography approaches to maximise the coverage of the metabolome.

Introduction to Metabolomics for the Microbiologist
27 - 29 April 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Introduction-to-Metabolomics-for-the-Microbiologist-April-2020.aspx

This three-day course introduces how untargeted metabolomics can be applied to study microbial systems in academic and industrial research. The course provides an overview of the metabolomics pipeline, experimental design, sample preparation and data acquisition. The course is led by experts in the field of metabolomics and will include lectures, hands-on laboratory sessions in sample preparation and data acquisition and computer workshops focused on data processing and data analysis.

Metabolomics with the Q Exactive
30 March - 1 April 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Metabolomics-with-the-Q-Exactive-April-2020.aspx

This 3-day course introduces you to using the Q Exactive mass spectrometer in your metabolomics investigations. The course is led by experts in the field of metabolomics and includes lectures, laboratory sessions and computer workshops to provide a detailed overview of the metabolomics pipeline applying the Q Exactive mass spectrometer.

Metabolite Identification with the Q Exactive and LTQ Orbitrap Elite
2 - 3 April 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Metabolite-identification-with-the-Q-Exactive-and-LTQ-Orbitrap-Elite-April-2020.aspx

This 2-day course provides a hands-on approach to teach attendees about the latest techniques and tools available to perform metabolite identification in non-targeted metabolomics studies. The course is led by experts working within the field of metabolomics, and will include a significant proportion of hands-on experience of using mass spectrometers, software tools and databases. A maximum of four people will be working on each mass spectrometer (Q Exactive and LTQ-Orbitrap Elite) in a session.

Multiple Biofluid and Tissue Types, From Sample Preparation to Analysis Strategies for Metabolomics
23 - 25 September 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Multiple-biofluid-and-tissue-types-from-sample-preparation-to-analysis-strategies-for-metabolomics-September-2020.aspx

This 3-day course provides a theoretical overview and hands-on training to apply multiple sample preparation and UPLC-MS methods to characterise the metabolomes of complex biological samples using the mass spectrometer (Xevo QToF G2-XS - a maximum of 4 people working on the instrument in a session). The course is led by experts in the field who have experience of the analysis of microbial, plant and mammalian samples, and illustrates the different approaches that are available to analyse a range of biological samples and applying complementary liquid chromatography approaches to maximise the coverage of the metabolome.

Introduction to Metabolomics for the Microbiologist
7 - 9 October 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Introduction-to-Metabolomics-for-the-Microbiologist-October-2020.aspx

This three-day course introduces how untargeted metabolomics can be applied to study microbial systems in academic and industrial research. The course provides an overview of the metabolomics pipeline, experimental design, sample preparation and data acquisition. The course is led by experts in the field of metabolomics and will include lectures, hands-on laboratory sessions in sample preparation and data acquisition and computer workshops focused on data processing and data analysis.

Metabolomics with the Q Exactive
2 - 4 November 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Metabolomics-with-the-Q-Exactive-April-2020.aspx

This 3-day course introduces you to using the Q Exactive mass spectrometer in your metabolomics investigations. The course is led by experts in the field of metabolomics and includes lectures, laboratory sessions and computer workshops to provide a detailed overview of the metabolomics pipeline applying the Q Exactive mass spectrometer.

Metabolite Identification with the Q Exactive and LTQ Orbitrap Elite
5 - 6 November 2020
https://www.birmingham.ac.uk/facilities/metabolomics-training-centre/courses/2020/Metabolite-identification-with-the-Q-Exactive-and-LTQ-Orbitrap-Elite-November-2020.aspx

This 2-day course provides a hands-on approach to teach attendees about the latest techniques and tools available to perform metabolite identification in non-targeted metabolomics studies. The course is led by experts working within the field of metabolomics, and will include a significant proportion of hands-on experience of using mass spectrometers, software tools and databases. A maximum of four people will be working on each mass spectrometer (Q Exactive and LTQ-Orbitrap Elite) in a session.



If you have any questions or queries about our courses, please do get in touch with our operations team: bmtc@contacts.bham.ac.uk
4
Mass spectrometry / Re: Experimental design for multiple-batch study
Last post by CoreyG -
Hi djb17,

It is always a good idea to randomize samples across batches. There are special cases where you might want to perform block randomization, such as what Jan described.
I guess you could say that the goal is to make systematic/technical variation orthogonal to biological variation.

Given that, how different are the distributions?
Say there are 3 conditions, where all samples were randomly assigned to. It would be fine to have one batch with 30/40/50 samples from each treatment (assuming they are run in a randomized order). However, it wouldn't be good to have a distribution of something like 50/0/60. Even worst would be 10/0/100.

For pooled QCs. It's a good idea to create the pooled samples and put them with the biological samples as soon as possible. This ensures they will capture as much technical variation as possible i.e. all the variation from sample storage, defrosting, extraction, running etc.
This is especially important when batches are processed separately (extracted separately or stored in different freezers).

Cheers,
Corey
6
Mass spectrometry / Re: Experimental design for multiple-batch study
Last post by djb17 -
Thanks for the reply.

It's not an experiment where we have 'paired samples', so we are okay with respect to that.

I wonder if it would be okay if an experiment set up where:

  • There are multiple batches.
  • Within each batch, samples with different conditions are not evenly distributed.
  • A pooled sample consisting of small amounts of all samples in batches is created. QC samples are analyzed in addition to the samples in each batch (which ideally would allow for inter + intra batch drift).

After the batch correction (inter + intra) using QC samples, will the quality of the data be okay given that the distribution of the conditions were not even?

Thanks again.
7
Mass spectrometry / Re: Experimental design for multiple-batch study
Last post by Jan Stanstrup -
Yes...
If you have "paired samples" where you are not interested in the differences within the pairs it can reduce variance to put them in the same batch. For example if you have several persons you might consider having the same person in the same batch for all time course samples.

But as you say. Spread evenly conditions and randomize within the batch.

Use plenty of QC samples so that you afterwards can correct for potential intra- and inter-batch drifts.
8
Mass spectrometry / Experimental design for multiple-batch study
Last post by djb17 -
Hi all,

I have been thinking about setting up an experiment with around 600 samples (3 batches of 200) with 3 different conditions. Would it be optimal to set up the batches such that the proportion of 3 different conditions are the same throughout the different batches?

Thank you.
9
XCMS / Re: Centroiding of profile-mode DDA data, MS2-level
Last post by Tony -
Hi,

sure, I tried:
cent_file <- pickPeaks(x = raw_file, refineMz = "descendPeak", signalPercentage = 33, msLevel. = 1, verbose = TRUE)

I receive:
Error in (function (classes, fdef, mtable)  :
  unable to find an inherited method for function ‘pickPeaks’ for signature ‘"missing"’

the raw file is a DDA-sample.
MSn experiment data ("OnDiskMSnExp")
Object size in memory: 2.67 Mb
- - - Spectra data - - -
 MS level(s): 1 2
 Number of spectra: 7205
 MSn retention times: 0:0 - 21:60 minutes
- - - Processing information - - -
Data loaded [Thu Sep 19 13:36:33 2019]
 MSnbase version: 2.11.6
- - - Meta data  - - -
phenoData
  rowNames:   xyz.mzML
  varLabels: sampleNames
  varMetadata: labelDescription
Loaded from:
  xyz.mzML
protocolData: none
featureData
  featureNames: F1.S0001 F1.S0002 ... F1.S7205 (7205 total)
  fvarLabels: fileIdx spIdx ... spectrum (35 total)
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'

kind regards
Tony
10
XCMS / Re: Centroiding of profile-mode DDA data, MS2-level
Last post by johannes.rainer -
Hm, that's interesting. Could be that the error comes from smooth, not from pickPeaks. Could you try your code again with only pickPeaks (i.e. skip the smooth step)?

If so, we'll have to add the msLevel. parameter also to the smooth method -

cheers, jo