Closed happyhamm closed 1 year ago
Hi @happyhamm , 1. Yes, it is the same, 2. You can ignore ABC_Road_I_GI where ABC_Road_GI_GI is present, it was corresponding to an older version, 3. For ALL, you use all rows of ABC and Roadmap files, corresponding to all tissues, see the code here: https://github.com/kkdey/GSSG/blob/master/code/GeneSet_toS2G/all_bedgraph_methods.R
Very helpful - Thanks so much, @kkdey!
Hi @kkdey, I tried running step2 and step3 starting from the posted gene scores linked below, and found that I was getting slightly different enrichment and tau-star values than what the publication found. The results were well correlated, but final values were slightly off.
gene score link we used: https://alkesgroup.broadinstitute.org/LDSCORE/Jagadeesh_Dey_sclinker/gene_scores/
sclinker results we compared against: https://alkesgroup.broadinstitute.org/LDSCORE/Jagadeesh_Dey_sclinker/sclinker_results/cell_type_programs/
Any suggestions on why this might be the case? Thanks!
Tracked this issue to differences in LDSC versions.
Hi @kkdey - Thanks so much for creating this great toolkit! We're excited to implement this for our studies.
Following the instructions for "STEP 2: Gene set/program to SNP annotation" using sc-linker, gives annotations with the expected/listed directory output containing "100kb" and "ABCRoad{enhancer_tissue}" (e.g. an output named "ABC_Road_GI"). How do I recreate the results posted in the publication?
Thank you so much!