diff options
| -rw-r--r-- | wqflask/wqflask/marker_regression/rqtl_mapping.py | 7 |
1 files changed, 4 insertions, 3 deletions
diff --git a/wqflask/wqflask/marker_regression/rqtl_mapping.py b/wqflask/wqflask/marker_regression/rqtl_mapping.py index 152bb5be..4070e9f5 100644 --- a/wqflask/wqflask/marker_regression/rqtl_mapping.py +++ b/wqflask/wqflask/marker_regression/rqtl_mapping.py @@ -62,6 +62,7 @@ def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, pe marker_covars = create_marker_covariates(control_marker, cross_object) # Create the additive covariate markers logger.info("Marker covars done"); if cofactors != "": + logger.info("Cofactors: " + cofactors); cross_object, trait_covars = add_cofactors(cross_object, dataset, cofactors, samples) # Create the covariates from selected traits ro.r('all_covars <- cbind(marker_covars, trait_covars)') else: @@ -71,7 +72,6 @@ def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, pe #logger.info("Saving Done"); covars = ro.r['all_covars'] #DEBUG to save the session object to file - #ro.r('save.image(file = "/home/dannya/gn2-danny/all.RData")') if pair_scan: if do_control == "true": logger.info("Using covariate"); result_data_frame = scantwo(cross_object, pheno = "the_pheno", addcovar = covars, model=model, method=method, n_cluster = 16) @@ -274,7 +274,8 @@ def add_cofactors(cross, this_dataset, covariates, samples): covar_name_string += ")" covars_ob = pull_var("trait_covars", cross, covar_name_string) - + # TODO: Pull in the types of the covars from MariaDB + # TODO: Iterate through the covar types and create a design matrix based on it return cross, covars_ob def create_marker_covariates(control_marker, cross): @@ -287,7 +288,7 @@ def create_marker_covariates(control_marker, cross): ro.r('covnames <- covnames[covInGeno]') ro.r("cat('covnames (purged): ', covnames,'\n')") ro.r('marker_covars <- genotypes[,covnames]') # Get the covariate matrix by using the marker name as index to the genotype file - + # TODO: Create a design matrix from the marker covars for the markers in case of an F2, 4way, etc return ro.r["marker_covars"] def process_pair_scan_results(result): |