diff options
| -rw-r--r-- | wqflask/wqflask/marker_regression/rqtl_mapping.py | 39 |
1 files changed, 21 insertions, 18 deletions
diff --git a/wqflask/wqflask/marker_regression/rqtl_mapping.py b/wqflask/wqflask/marker_regression/rqtl_mapping.py index 4117a0e5..f593ae91 100644 --- a/wqflask/wqflask/marker_regression/rqtl_mapping.py +++ b/wqflask/wqflask/marker_regression/rqtl_mapping.py @@ -78,6 +78,7 @@ def run_rqtl_geno(vals, samples, dataset, mapping_scale, method, model, permChec cross_object = calc_genoprob(cross_object) else: cross_object = calc_genoprob(cross_object, step=5, stepwidth="max") + logger.info("after calc_genoprob"); pheno_string = sanitize_rqtl_phenotype(vals) logger.info("phenostring done"); @@ -110,11 +111,13 @@ def run_rqtl_geno(vals, samples, dataset, mapping_scale, method, model, permChec return process_pair_scan_results(result_data_frame) else: if do_control == "true" or cofactors != "": - logger.info("Using covariate"); result_data_frame = scanone(cross_object, pheno = "the_pheno", addcovar = covars, model=model, method=method) - ro.r('save.image(file = "/home/zas1024/gn2-zach/itp_cofactor_test.RData")') + ro.r(f"qtl_results = scanone(the_cross, pheno='the_pheno', addcovar=all_covars, model='{model}', method='{method}')") + result_data_frame = ro.r("qtl_results") else: - logger.info("No covariates"); result_data_frame = scanone(cross_object, pheno = "the_pheno", model=model, method=method) + ro.r(f"qtl_results = scanone(the_cross, pheno='the_pheno', model='{model}', method='{method}')") + result_data_frame = ro.r("qtl_results") + marker_names = np.asarray(ro.r("row.names(qtl_results)")) if num_perm > 0 and permCheck == "ON": # Do permutation (if requested by user) if len(perm_strata_list) > 0: #ZS: The strata list would only be populated if "Stratified" was checked on before mapping cross_object, strata_ob = add_perm_strata(cross_object, perm_strata_list) @@ -129,9 +132,10 @@ def run_rqtl_geno(vals, samples, dataset, mapping_scale, method, model, permChec perm_data_frame = scanone(cross_object, pheno_col = "the_pheno", n_perm = num_perm, model=model, method=method) perm_output, suggestive, significant = process_rqtl_perm_results(num_perm, perm_data_frame) # Functions that sets the thresholds for the webinterface - return perm_output, suggestive, significant, process_rqtl_results(result_data_frame, dataset.group.species) + + return perm_output, suggestive, significant, process_rqtl_results(marker_names, result_data_frame, dataset.group.species) else: - return process_rqtl_results(result_data_frame, dataset.group.species) + return process_rqtl_results(marker_names, result_data_frame, dataset.group.species) def generate_cross_from_rdata(dataset): rdata_location = locate(dataset.group.name + ".RData", "genotype/rdata") @@ -144,7 +148,6 @@ def generate_cross_from_rdata(dataset): """ % (rdata_location)) def generate_cross_from_geno(dataset, scale_units): # TODO: Need to figure out why some genofiles have the wrong format and don't convert properly - ro.r(""" trim <- function( x ) { gsub("(^[[:space:]]+|[[:space:]]+$)", "", x) } getGenoCode <- function(header, name = 'unk'){ @@ -376,9 +379,8 @@ def process_pair_scan_results(result): def process_rqtl_perm_results(num_perm, results): perm_vals = [] - for line in str(results).split("\n")[1:(num_perm+1)]: - #print("R/qtl permutation line:", line.split()) - perm_vals.append(float(line.split()[1])) + for item in results: + perm_vals.append(item) perm_output = perm_vals suggestive = np.percentile(np.array(perm_vals), 67) @@ -386,20 +388,21 @@ def process_rqtl_perm_results(num_perm, results): return perm_output, suggestive, significant -def process_rqtl_results(result, species_name): # TODO: how to make this a one liner and not copy the stuff in a loop +def process_rqtl_results(marker_names, results, species_name): # TODO: how to make this a one liner and not copy the stuff in a loop qtl_results = [] - output = [tuple([result[j][i] for j in range(result.ncol)]) for i in range(result.nrow)] - for i, line in enumerate(result.iter_row()): + for i, line in enumerate(results): marker = {} - marker['name'] = result.rownames[i] - if species_name == "mouse" and output[i][0] == 20: #ZS: This is awkward, but I'm not sure how to change the 20s to Xs in the RData file + marker['name'] = marker_names[i] + if species_name == "mouse" and line[0] == 20: marker['chr'] = "X" else: - marker['chr'] = output[i][0] - marker['cM'] = output[i][1] - marker['Mb'] = output[i][1] - marker['lod_score'] = output[i][2] + try: + marker['chr'] = int(line[0]) + except: + marker['chr'] = line[0] + marker['cM'] = marker['Mb'] = line[1] + marker['lod_score'] = line[2] qtl_results.append(marker) return qtl_results
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