download the test data through the interface, using wget or git lfs
and place it in the ./test_data/hg38_EAS folder.
[!NOTE]
The pipeline has been upgraded to nextflow DSL2 syntax recently. If you wish to use the previous version in DSL1, you find it in ./old_versions and run it with previous version of nextflow ("NXF_VER=22.10.5 nextflow run jass_pipeline.nf ....")
Test data are located in the ${PATH_TO_PIPELINE_FOLDER}/test_data/hg38_EAS/ folder
These are extracts of summary statistics from a trans ancestry GWAS on blood traits ([Chen et al](https://www.sciencedirect.com/science/article/pii/S0092867420308229?via%3Dihub)): WBC, White blood cell count; RBC, Red blood cell count; PLT, platelet count.
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@@ -53,7 +38,7 @@ They correspond to the chromosome 21 and 22 for the East asian ancestry.
/* Parameter to set if optional pipeline steps are performed */
params.compute_project=true// Compute JASS runs
params.compute_LDSC_matrix=true// Infer the genetic covariance and residual covariance using the LDscore regression (Bulik-Sullivan, et al, 2015). The residual covariance is necessary to perform multi-trait GWAS (see julienne, et al 2021) If set to false, the residual covariance will be infered from Zscores
params.compute_imputation=true
params.compute_LDSC_matrix=false// Infer the genetic covariance and residual covariance using the LDscore regression (Bulik-Sullivan, et al, 2015). The residual covariance is necessary to perform multi-trait GWAS (see julienne, et al 2021) If set to false, the residual covariance will be infered from Zscores
params.compute_imputation=false
/* Path of input data */
params.meta_data="${projectDir}"+"/input_files/Meta_data_preliminary_analysis.csv"// file describing gwas summary statistic format
