Moore Notes 12 18 13
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Group Call
- Participants: Katie, Tom, Stephen, Dongying, Patrick, Josh
- PICRUSTs update: http://edhar.genomecenter.ucdavis.edu/~gjospin/picrust_test/picrust_test/Dec_3_2013/
- Does collapsing KOs to pathways (via EC identifiers) improve agreement between PICRUSTs and Shotmap?
- Small improvement in correlation, but similar to KO results
- Correlation is statistically significant but not high
- Katie: Check that ECs are all pathways and not individual enzymes
- Discussed results to Jack Gilbert
- Stephen: What about presence-absence? Tom: slightly better. Stephen: could check families that are above an abundance threshold in metagenomes.
- Does collapsing KOs to pathways (via EC identifiers) improve agreement between PICRUSTs and Shotmap?
- Stephen: Looks like the Tara Oceans data is available?
- Josh will check release dates
- Tom: Check rules about using data pre-publication (Ft. Lauderdale, permissions etc)
- Where to put data and do compute?
- Single repository, with mirrors
- Distribute compute jobs across systems and users
- IHG cluster
- Other pay-as-you-go options: EC2 just got cheaper
- Josh: Tibetan soils
- Can we predict current bacterial distributions from historical climate data?
- About 80% of taxa (plus community composition: NMDS1) are better predicted by climate data from 50 years ago than current climate data
- Similar results were found in North American soils, e.g., Deltaproteobacteria
- Josh: plants and other dispersal limited taxa in communities could be driving this
- Stephen: how closely do bacteria really associate with plants?
- Tom: check what lag is in plant data
- Josh: Will also look at deserts vs. other regions with more plants
- Stephen: What was happening in 1970s when prediction falls? Is it real or an artifact of data collection?
- Check what climate variable(s) change then
- Tom: did soil disturbance patterns change?
- Tom: Fluctuations are also interesting
- Can we predict current bacterial distributions from historical climate data?