See also: IRC log
<scribe> scribenick: mscottm2
Jason: I simply wanted to read in a MAGE-ML file and create an RDF representation that is true to the MAGE-ML.
<JimMcCusker> Hi all
Jason: There were useful documents hosted by ArrayExpress describing the MAGE model. I have a copy that can be served from a local tomcat if you are interested.
I wanted RDF that I could browse in IO's Knowledge Explorer ASAP in order to explore the model.
scribe: It doesn't read in CEL files or other data files yet.
Jim: Jason - Have you tried running this against a non-MAGE-ML source like GEO?
Jason: Yes, with varying results.
Scott: (to Jason) Can you host the code at github or similar so that we have a URL to point IG note readers to?
Jason: Yes, but I can't update the code for a few months.
Michael: There are places to
enter metadata at GEO but it usually isn't done so it is
effectively unavailable.
... Imperial College has some nice multi-factor experiment
sets. Interesting graph. I'll see if I can dig it up.
<michael> the accession is e-mimr-12
Jim: You are using your own namespaces as well as MAGE-OM?
Jason: Yes, still writing own namespaces into the RDF.
Scott: (to Jim) Is a possible combination of Jason and your code: Use Jason's to traverse the MAGE-OM model for some of the decisions in MAGETAB2RDF
Jim: yes.
... I used Limpopo to read in MAGETAB.
Michael: MAGE-ML has more historical use. You can find some old code that I wrote for Resolver that reads it but most use MAGETAB.
<michael> use of MAGE-ML is pretty much deprecated for MAGE-TAB
Limpopo MAGE-TAB Parser - http://limpopo.sourceforge.net/extensions.html
Michael: Which class does the translation to the triples?
Jason: That's done in rdflib.
Looks like it's rdflib version 2.4.
... document.py is the class that does the main RDF production
work, using rdflib.
<JimMcCusker> http://code.google.com/p/surfrdf/
Michael: factor , value - every
one of your assays will be associated with a value from each of
the factors
..Example: one bioassay will be at the 1 second time point with
a 100 mg. dosage, can be joined with other bioassays based on
the factor / value set.
<JimMcCusker> http://dl.dropbox.com/u/9752413/cshals-2012/combineResults.py
<JimMcCusker> http://dl.dropbox.com/u/9752413/cshals-2012/importArrayExpress.py
<JimMcCusker> http://code.google.com/p/magetab2rdf/wiki/Mappings
Scott: Any plans to read CEL files into Knowledge Explorer and output analysis results in RDF?
Jason: Yes, that was the original plan. We just have other priorities at the moment.
Scott: Could you hand part of the process to an R script (bioconductor) for affy files (that is run on an R server / service)?
<jasone> Knime: http://www.knime.org/
Jason: Could offer Knowledge Explorer services in Knime (Pipeline tool).
Scott: <re-explains motivations for IG note, asks Jim about R scripts and demo apps>
Jim: Targetting GenePattern with output. Use RDF Data Cube vocabulary to express the output set.
<JimMcCusker> http://publishing-statistical-data.googlecode.com/svn/trunk/specs/src/main/html/cube.html
Jim: Have refined MAGETAB converter. Used OBI and EFO. Now also uses PROV.
Scott: We should align with ArrayExpress (James Malone et al).
Jim: I'm happy to share my code with James Malone and others.
<JimMcCusker> http://dl.dropbox.com/u/9752413/PROV-Examples/E-MTAB-327.rdf.ttl
Scott: So, how can this stuff be used by a bioinformaticist who knows nothing of RDF? (from an R script)
<JimMcCusker> https://github.com/jimmccusker/lobi
<JimMcCusker> http://lodspeakr.org
Jim: Project - Linked Open Biomedical Investigations has a java tool, extends a tool called LODspeaker that you point at a triplestore and it publishes it as linked data for you and UI's based on templates.
<michael> have to go, thanks much!
Jim: I know that there's a bridge from python into R, but is the reverse true?
Jason: Yes, there is.
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