16:07:08 <RRSAgent> RRSAgent has joined #hcls2
16:07:08 <RRSAgent> logging to http://www.w3.org/2011/06/16-hcls2-irc
16:07:12 <michel> rrsagent, make logs public
16:07:37 <michel> zakim, this is tmo
16:07:37 <Zakim> ok, michel; that matches SW_HCLS(TMO)11:00AM
16:08:57 <michel> Fred gave his use case
16:14:53 <mscottm> mscottm has joined #hcls2
16:17:01 <Bosse> Bosse has joined #hcls2
16:18:34 <michel> https://docs.google.com/document/d/1BeaU3VJW1S_R3eB5ncrcW9wJ-lMU4xdmxCdjH8E0i5s/edit?hl=en_US
16:21:04 <iker> http://code.google.com/p/lindenb/source/browse/trunk/src/xsl/dbsnp2rdf.xsl
16:22:43 <iker> here is an example of the transformation using this XSLT http://code.google.com/p/lindenb/wiki/Xsltstream
16:23:08 <bbalsa> bbalsa has joined #HCLS2
16:23:45 <BobP> BobP has joined #hcls2
16:24:03 <BobP> scribenick BobP
16:24:33 <BobP> Scott discussing possible massive join.
16:24:53 <BobP> Scott: Trick is to know which xml query to need
16:25:18 <BobP> Michel: NCBI is Oracle
16:26:28 <BobP> Michel: We need just the SNPs, do not need to extend further
16:28:29 <BobP> Michel and Iker discussing xml schema
16:29:03 <BobP> Iker: XML schema is really long.
16:30:42 <iker> https://docs.google.com/document/d/1BeaU3VJW1S_R3eB5ncrcW9wJ-lMU4xdmxCdjH8E0i5s/edit?hl=en_US&pli=1
16:31:08 <michel> https://docs.google.com/document/d/1lKdDSb2uBBIeTEQAv2CyTHN_aVW63k9si1hmmilOMi0/edit?hl=en_US&authkey=CJGUtcwF
16:31:40 <BobP> Above link is for the axioms!
16:32:06 <BobP> Sorry - is for the paper.
16:33:03 <Zakim> + +1.781.431.aacc
16:33:45 <epichler> epichler has joined #HCLS2
16:34:07 <BobP> Scott: Agree w need to come up with data of some sort
16:34:33 <BobP> ... problem: warfarin is used in many situations; Ex heart valve etc
16:35:18 <BobP> ... warfarin used for many things. So cohort is more general than a given disease
16:35:45 <BobP> ... 'bedridden' is one of the indications, not really a disease cohort
16:36:16 <BobP> Michel: pharmGKB is from trials data
16:36:57 <mscottm> Above: I was talking about a potentially massive SQL query that would be used to access the key data elements in the SNPdb database (local copy).
16:38:35 <BobP> Scott: Have large list of to-do. Been contacted by editor re progress.
16:38:45 <BobP> ... deadline is July 7.
16:39:22 <BobP> ... due in three weeks. What are the main bottlenecks?
16:39:39 <iker> +1 timeline
16:40:35 <BobP> Elgar: Found couple of papers on methodology for predictors for warfarin dosing
16:40:45 <BobP> ... most of papers are in google doc
16:41:33 <BobP> ... tested predictors against other methods out there
16:41:51 <BobP> ... 5 predictors: 2 clinical, 2 gene tables, 1 other
16:42:24 <BobP> ... seems that pgx algorithms best > 50%
16:42:51 <BobP> ... for methods, might be interesting to contact the authors to get data
16:42:59 <Zakim> -??P30
16:43:42 <epichler> Finkelman et al. 2011
16:44:10 <epichler> Journal of the American College of Cardiology Vol. 57, No. 5, 2011
16:44:32 <epichler> Tatonetti et al. BMC Bioinformatics 2010, 11(Suppl 9):S9
16:46:19 <BobP> Elgar will contact authors
16:46:39 <BobP> Scott: Can validate our modelling w their methodology
16:47:05 <BobP> Elgar: Here are their methods based on these feature vectors
16:48:19 <BobP> Scott: So using best predictor, then use table method
16:48:42 <BobP> Elgar: We enable being able to ask certain queries.
16:48:48 <mscottm> Query the knowledgebase: What would be the best predictor? Compare answer to the answer given by the article's recommended method or algorithm
16:49:41 <iker> +1 this approach
16:57:29 <BobP> Fred discussing integration of data from different contexts and from different purposes
16:57:49 <BobP> Fred: Considering whether clinically useful or validated
16:58:16 <BobP> Scott: Talking to clinical genetics dept, to set up decision pipeline
16:58:44 <BobP> ... decisions based on alleles or snps, use linked data for interoperability
16:59:06 <iker> my regrets but i must leave
16:59:16 <Zakim> -??P64
16:59:46 <BobP> ... extract clinical data, ability relies on the ability to represent the SNPs etc
16:59:59 <BobP> ... even hypotheses might be captured
17:00:48 <BobP> ... seems not practical now to look back 10 years b/c not represented in data
17:01:15 <BobP> ... advantage in modeling is to implement algorithms in a lucid fashion
17:02:20 <BobP> ... if algorithms written using concepts that are traceable, this will be powerful
17:03:13 <BobP> ... clinical data pipeline: one long information flow requires these models and linked data
17:03:58 <BobP> ... model for SNPs can be expanded, here's a way to use the data
17:04:56 <BobP> ... little fuzzy on where comparison is made between querying in linked data, and in table format
17:05:58 <BobP> ... difficult to present to pgx crowd maybe
17:06:55 <BobP> Fred: Concrete example of who uses and for what would be good here.
17:07:48 <BobP> We're talking all about data structures :-)
17:08:35 <BobP> Scott: Need comprehesible explanation for real people.
17:08:45 <BobP> Fred: Who do you want to read this?
17:09:12 <BobP> Scott: Propose a way to deal w pgx data and knowledge so can be harnessed in the clinic
17:09:24 <BobP> ... make use of the knowledge in a clear fashion
17:09:47 <BobP> Fred: Clinician, or researcher, or concerned w some disease?
17:10:27 <BobP> Scott: Somebody in either form of research; concerned w personalized medicine, lots of people
17:11:01 <BobP> ... general approach to data handling. Futuristic for clinics, just trying to deal w patients
17:12:09 <BobP> ... people in pharma, people in genetics (maybe); pgx is relatively young
17:12:57 <BobP> ... not general practicioners; drug development people, but not drug discovery
17:13:20 <BobP> ... downstream from lead discovery, before you go into staged trials
17:15:13 <BobP> Scott: Meeting in London NCRI, I heard gene variants everywhere, in all kinds of projects
17:15:53 <BobP> ... gene variants is a bottleneck. w/o info requirement to id, then people are not sure what they need to do
17:16:24 <BobP> ... danger of 100 diff approaches to refer to SNP, fragmentation; another data hurdle
17:16:49 <BobP> ... not evident until you try to share data; but data sharing is inevitable and is the next step
17:17:28 <BobP> Fred: Sounds like a much needed capability
17:18:20 <BobP> Scott: Thanks to Fred for sanity check!
17:18:36 <Zakim> - +1.781.431.aacc
17:18:37 <Zakim> -??P37
17:18:37 <Zakim> - +1.714.616.aaaa
17:18:39 <Zakim> - +20416aabb
17:18:39 <Zakim> -Bob_Powers
17:18:39 <Zakim> SW_HCLS(TMO)11:00AM has ended
17:18:40 <Zakim> Attendees were Bob_Powers, +1.714.616.aaaa, +20416aabb, +1.781.431.aacc
17:18:41 <epichler> epichler has left #HCLS2
17:30:44 <mscottm2> mscottm2 has joined #hcls2
17:30:47 <mscottm2>   RRSAgent, please draft minutes
17:30:47 <RRSAgent> I have made the request to generate http://www.w3.org/2011/06/16-hcls2-minutes.html mscottm2
17:30:51 <mscottm2>   RRSAgent, please make log world-visible
18:08:45 <Zakim> Zakim has left #hcls2
19:34:59 <mscottm> mscottm has joined #hcls2