Dear TPP friends,
I just published a quite extensive open access article about advanced
mass spectrometry data analysis: (An evolving computational platform for
biological mass spectrometry: workflows, statistics and data mining with
MASSyPup64, https://peerj.com/articles/1401/).
It contains an example for the peptide/protein identification with
comet/PeptideProphet/ProteinProphet, with subsequent export of the
results in various formats (Excel, csv, html) and extraction of hits
relevant for the project (e.g. protein names containing "peroxidase").
Running the TPP/ textmining taverna workflow only requires 1) revising/
adjusting the comet.params file (with location of the fasta sequence
DB), 2) defining the .mzML data directory and 3) defining the text
search term for the results (if required). Further parameters may be
adjusted, if desired.
Importantly, the data do not have to be moved to a certain directory
(such as /wwwdata), but are processed where they are ("in place").
Technically speaking, the workflow is constructed with taverna
(http://www.taverna.org.uk/), employing the TPP scripts (4.8), comet
(http://sourceforge.net/projects/comet-ms/) and standard linux commands
(grep, ..). The complete workflow (with dependencies and example data)
runs straight away from the latest release of MASSyPup64,
http://www.bioprocess.org/massypup/. The workflow file is attached to
this email (I hope it arrives, if not, please tell me).
The article also demonstrates, how an Association Analysis of the
peptide hits can be performed with Rattle. This Data Mining strategy is
useful, to detect co- occurring peptides (i.e. with low frequency, but
high confidentiality), e.g. when looking for alternative biomarkers. The
strategy is well known from Market Basket algorithms ("maybe you also
want to buy Parry Hotter 2-8?") and Social Networks ("do you know Peter,
Paul and Marry?") ..
Any comments are welcome!
Best regards, Robert
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