Re: [Psidev-qc-dev] Quality control in Mass-Up (and other topics)

[David T. <dt...@su...>]

Hi, Hugo.

Would you be willing to assemble a draft qcML document that might be
created by your Mass-Up software?  We will be looking at such examples
at our annual HUPO-PSI meeting in a week.  I am providing a pointer to a
draft qcML example of the quality metrics that are produced within the
QuaMeter "IDFree" mode.
https://github.com/HUPO-PSI/qcML-development/blob/master/20180403-1091_Pool_start_v0.8.qc.xml

Thanks,
Dave

On 1/20/2017 1:31 PM, Hugo López Fernández wrote:
> Hello David,
>
> I am Hugo, we met last week in Semmering. I hope this email finds you
> well and that you had a good trip to back home.
>
> As we talked in the EuBIC, I am writing you to let you know more about
> the quality control analysis that we have included in Mass-Up
> (http://sing-group.org/mass-up/). This quality control is intended to
> work with peak lists. We would like to incorporate quality control for
> raw data, specially to detect batch effects as I also commented you.
>
> Basically, the quality control (which is explained with most details
> in the paper http://doi.org/10.1186/s12859-015-0752-4) can be done at
> two levels: at the replicates leve and at the samples level, which
> includes additional information from the intra-sample m/z matching
> process and consensus spectrum creation (this is because our
> collaborators usually want to reduce replicates spectra to a unique
> sample "consensus" spectrum). You can find attached the quality
> control image included in the paper.
>
> At the replicates level, the user can check basic information about
> each individual spectrum (i.e. peak count, m/z range, intensity
> ranges, etc.) and compare all spectra in the dataset. At the samples
> level, the user can check the performance of the intra-sample peak
> matching process, by comparing the percentages of presence (POP)
> counts (i.e.: the counts of peaks that are present in, for example,
> 60%, 80% or 100% of replicates) and the POPs of each sample.
>
> In spite of being a very simple quality control it allowed us to
> detect some problems with datasets and we encourage our collaborators
> to have a quick look at this quality control metrics before any other
> analysis. Unfortunately they usually don't but we must encourage good
> practices, which is the reason why I am developing this other software
> (http://www.sing-group.org/s2p/), also presented in other poster at
> the EuBIC. Basically it is a software to manage, process and integrate
> different data sources (Mascot identifications, MALDI plates, 2D-gel
> spots). It probably will not revolutionize bioinformatics but it is
> allowing the research group to process data efficiently and in a
> reproducible way, a totally different scenario than wen I came here
> six months ago.
>
> As I mentioned previously we also would like to include quality
> control metrics for MALDI-TOF raw data, with special focus in batch
> effect detection (which seems to a common problem here). Regarding
> batch effect, I would like to apply this statistic
> (http://dx.doi.org/10.1093/bioinformatics/btt480) based on guided
> principal component analysis to detect batch effects in MALDI-TOF data
> (some people applied it to LC-MS metabolomic data
> [http://dx.doi.org/10.1016/j.talanta.2014.07.031]). I would like to
> develop this work this year if I get public MALDI-TOF datasets where
> batch effect presence has been publicly reported (I found a few
> reported but I could not get the data to analyze it yet).
>
> I will be happy to answer any question you may have or to receive any
> feedback from you. Looking forward to see you again, in other
> conference or wherever.
>
> Best regards,
>
>     Hugo.
>

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