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| author | Danny Arends | 2020-05-04 05:05:25 -0500 |
|---|---|---|
| committer | Danny Arends | 2020-05-04 05:05:25 -0500 |
| commit | 3b1bcd0ff7dc199e6ea83a766cb1d9e6081776a7 (patch) | |
| tree | 26dc50325357040bea4d209628f29e359f8a2921 /wqflask | |
| parent | cd05cb4782c22abdf299f033a39ccfa82be38596 (diff) | |
| download | genenetwork2-3b1bcd0ff7dc199e6ea83a766cb1d9e6081776a7.tar.gz | |
Working on covariate mapping, making sure the addcovars are numeric
Diffstat (limited to 'wqflask')
| -rw-r--r-- | wqflask/wqflask/marker_regression/rqtl_mapping.py | 13 |
1 files changed, 10 insertions, 3 deletions
diff --git a/wqflask/wqflask/marker_regression/rqtl_mapping.py b/wqflask/wqflask/marker_regression/rqtl_mapping.py index c1a56787..46b54f36 100644 --- a/wqflask/wqflask/marker_regression/rqtl_mapping.py +++ b/wqflask/wqflask/marker_regression/rqtl_mapping.py @@ -45,7 +45,7 @@ def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, pe if manhattan_plot: cross_object = calc_genoprob(cross_object) else: - cross_object = calc_genoprob(cross_object, step=1, stepwidth="max") + cross_object = calc_genoprob(cross_object, step=5, stepwidth="max") pheno_string = sanitize_rqtl_phenotype(vals) @@ -59,9 +59,15 @@ def run_rqtl_geno(vals, samples, dataset, method, model, permCheck, num_perm, pe ro.r('all_covars <- cbind(marker_covars, trait_covars)') else: ro.r('all_covars <- marker_covars') + + # Force all covaraites to be numeric (which is wrong for ITP year, season, etc... But required for R/qtl) + ro.r('covarnames <- colnames(all_covars)') + ro.r('all_covars <- apply(all_covars, 2, as.numeric)') + ro.r('colnames(all_covars) <- covarnames') 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) @@ -187,7 +193,8 @@ def sanitize_rqtl_phenotype(vals): def add_phenotype(cross, pheno_as_string, col_name): ro.globalenv["the_cross"] = cross - ro.r('the_cross$pheno <- cbind(pull.pheno(the_cross), ' + col_name + ' = '+ pheno_as_string +')') + ro.r('pheno <- data.frame(pull.pheno(the_cross))') + ro.r('the_cross$pheno <- cbind(pheno, ' + col_name + ' = as.numeric('+ pheno_as_string +'))') return ro.r["the_cross"] def pull_var(var_name, cross, var_string): |