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-rw-r--r--topics/data/precompute/steps.gmi15
1 files changed, 13 insertions, 2 deletions
diff --git a/topics/data/precompute/steps.gmi b/topics/data/precompute/steps.gmi
index a771e2c..d22778a 100644
--- a/topics/data/precompute/steps.gmi
+++ b/topics/data/precompute/steps.gmi
@@ -13,8 +13,18 @@ We will track precompute steps here. We will have:
Trait archives will have steps for
* [X] step p1: list-traits-to-compute
-* [+] step p2: gemma-lmm9-loco-output: Compute standard GEMMA lmm9 LOCO vector with gemma-wrapper
-* [ ] step p3: gemma-to-lmdb: create a clean vector
+* [X] step p2: gemma-lmm9-loco-output: Compute standard GEMMA lmm9 LOCO vector with gemma-wrapper
+* [X] step p3: gemma-to-lmdb: create a clean vector
+
+Start precompute
+
+* [ ] Fetch traits on tux04
+* [ ] Set up runner on tux04 and others
+* [ ] Run on Octopus
+
+Work on published data
+
+* [ ] Fetch traits
The DB itself can be updated from these
@@ -22,6 +32,7 @@ The DB itself can be updated from these
Later
+* [ ] Rqtl2: Compute Rqtl2 vector
* [ ] bulklmm: Compute bulklmm vector
Interestingly this work coincides with Arun's work on CWL. Rather than trying to write a workflow in bash, we'll use ccwl and accompanying tools to scale up the effort.