<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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