Open jimhavrilla opened 3 years ago
Gives us an idea of what genes are more likely related to the trait. It's a bit sparse to have the Gene Section with just Phen2Gene, in honesty. May be good to add sources like this that use more data; no licensing information and code and data are online for free download so I'm guessing with citation we can use it. Results: https://www.dropbox.com/sh/dz4haeo48s34sex/AADT_nwA3HCl_VFEScGN-kWXa/results?dl=0&subfolder_nav_tracking=1 Paper https://www.medrxiv.org/content/10.1101/2020.09.08.20190561v1.full.pdf+html Data format is pretty straightforward, like this:
trait cohort ensgid gene chromosome start end tss pops_score Alzheimer PASS ENSG00000079974 RABL2B 22 51205929 51222091 51222091 0.2660925297737443 Anorexia PASS ENSG00000186092 OR4F5 1 69091 70008 69091 -0.006756145993567379
Easy Elasticsearch parse. Can be limited somewhat in results, but still something new using some powerful data.
Gives us an idea of what genes are more likely related to the trait. It's a bit sparse to have the Gene Section with just Phen2Gene, in honesty. May be good to add sources like this that use more data; no licensing information and code and data are online for free download so I'm guessing with citation we can use it. Results: https://www.dropbox.com/sh/dz4haeo48s34sex/AADT_nwA3HCl_VFEScGN-kWXa/results?dl=0&subfolder_nav_tracking=1 Paper https://www.medrxiv.org/content/10.1101/2020.09.08.20190561v1.full.pdf+html Data format is pretty straightforward, like this:
Easy Elasticsearch parse. Can be limited somewhat in results, but still something new using some powerful data.