FinucaneLab / pathway_analysis_kt

Pathway analysis project using LDSC and Inrich

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Step 1:

Run make_genesets.py by inputting a unique list of genesets to both make the geneset files for LDSC and the submit.tsv file for dsub.

python make_genesets.py \
       --unique-genesets /broad/finucanelab/ktashman/inrich_genesets/kegg.unique.descrip \
       --full-genesets /broad/finucanelab/ktashman/inrich_genesets/kegg.set \
       --out-path /broad/finucanelab/ktashman/inrich_analyses/inrich_LDSC_genesets \

Copy the genesets from that folder to your local machine and upload them to the bucket and folder as specified in your make_genesets.py script

Step 2:

Run the Inrich analyses for your phenotype of interest with your gene sets of interest.

python run_inrich.py \
       --sumstats /broad/finucanelab/ktashman/inrich_analyses/sumstats/scz_summary_stats.sumstats \
       --assoc_snps /broad/finucanelab/ktashman/inrich_analyses/sumstats/scz_summary_stats.assoc_snps \
       --geneset-list /broad/finucanelab/ktashman/inrich_genesets/kegg.set

Step 3:

Copy the interval files to the cloud and create a submit.tsv file to run S-LDSC using dsub.

Step 5:

When your LDSC results are done, copy them to local machine and copy to server. Upload these to a folder that contains all of your genesets. Run munge_results.py to munge the inrich and the LDSC results and produce comined p-value results.

python munge_results.py \
       --geneset-list /broad/finucanelab/ktashman/inrich_genesets/kegg.unique.descrip \
       --in-path /broad/finucanelab/ktashman/inrich_analyses/inrich_results \
       --out-path /broad/finucanelab/ktashman/inrich_analyses/inrich_results \
       --inrich-path /broad/finucanelab/ktashman/inrich_analyses/sumstats/ \
       --phenotypes scz_summary_stats.sumstats

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Pathway analysis project using LDSC and Inrich


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