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authorPjotr Prins2025-08-22 13:10:05 +0200
committerPjotr Prins2025-08-22 13:10:09 +0200
commit96c7bfc3477b95d3f2f36f548d5dbbb90e88fb62 (patch)
treeeaf124e79ced7398dd5930ae5229c09f3c8a4417
parent35a73129d2f98f8f02fbc94d24433dcda783f72a (diff)
downloadgn-ai-96c7bfc3477b95d3f2f36f548d5dbbb90e88fb62.tar.gz
Precompute
-rw-r--r--topics/systems/mariadb/precompute-publishdata.gmi8
1 files changed, 6 insertions, 2 deletions
diff --git a/topics/systems/mariadb/precompute-publishdata.gmi b/topics/systems/mariadb/precompute-publishdata.gmi
index 71fc0f2c..2db425d0 100644
--- a/topics/systems/mariadb/precompute-publishdata.gmi
+++ b/topics/systems/mariadb/precompute-publishdata.gmi
@@ -2009,11 +2009,15 @@ Another trait 14905 shows a whopper on Chr4 with gemma and and one on Chr8 with
 
 So, rerunning GEMMA and reaper are on the books. While we are at it we can adapt reruns for
 
-* qnormalized data
+* qnormalized data*
 * auto winsorizing
 * sex covariate
 * run gemma without LOCO
-* cis covariate, using the current hit and recompute with that as a covariate
+* cis covariate, using the current hit and recompute with that as a covariate*
 * epistatic covariates
 
 and that should all be reasonably easy for the 13K traits.
+
+## More metadata
+
+But first we set up a new run with more metadata. In the lmdb files we should add the trait values, the mean, SE, skew, kurtosis, any DOIs.