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authorDanny Arends2020-05-04 05:05:25 -0500
committerDanny Arends2020-05-04 05:05:25 -0500
commit3b1bcd0ff7dc199e6ea83a766cb1d9e6081776a7 (patch)
tree26dc50325357040bea4d209628f29e359f8a2921 /wqflask
parentcd05cb4782c22abdf299f033a39ccfa82be38596 (diff)
downloadgenenetwork2-3b1bcd0ff7dc199e6ea83a766cb1d9e6081776a7.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.py13
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):