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-rw-r--r--gn3/heatmaps.py70
1 files changed, 49 insertions, 21 deletions
diff --git a/gn3/heatmaps.py b/gn3/heatmaps.py
index f3d7d25..4349ee0 100644
--- a/gn3/heatmaps.py
+++ b/gn3/heatmaps.py
@@ -131,7 +131,7 @@ def cluster_traits(traits_data_list: Sequence[Dict]):
return tuple(__cluster(tdata_i) for tdata_i in enumerate(traits_data_list))
-def heatmap_data(traits_names, conn: Any):
+def build_heatmap(traits_names, conn: Any):
"""
heatmap function
@@ -148,27 +148,55 @@ def heatmap_data(traits_names, conn: Any):
TODO: Elaborate on the parameters here...
"""
threshold = 0 # webqtlConfig.PUBLICTHRESH
- def __retrieve_traitlist_and_datalist(threshold, fullname):
- trait = retrieve_trait_info(threshold, fullname, conn)
- return (trait, retrieve_trait_data(trait, conn))
-
- traits_details = [
- __retrieve_traitlist_and_datalist(threshold, fullname)
- for fullname in traits_names]
- traits_list = tuple(x[0] for x in traits_details)
- traits_data_list = [x[1] for x in traits_details]
- genotype_filename = build_genotype_file(traits_list[0]["riset"])
- strainlist = load_genotype_samples(genotype_filename)
- exported_traits_data_list = tuple(
- export_trait_data(td, strainlist) for td in traits_data_list)
- slink_data = slink(cluster_traits(exported_traits_data_list))
- ordering_data = compute_heatmap_order(slink_data)
+ traits = [
+ retrieve_trait_info(threshold, fullname, conn)
+ for fullname in trait_fullnames()]
+ traits_data_list = [retrieve_trait_data(t, conn) for t in traits]
+ genotype_filename = build_genotype_file(traits[0]["riset"])
+ genotype = parse_genotype_file(genotype_filename)
+ strains = load_genotype_samples(genotype_filename)
+ exported_traits_data_list = [
+ export_trait_data(td, strains) for td in traits_data_list]
+ slinked = slink(cluster_traits(exported_traits_data_list))
+ traits_order = compute_traits_order(slinked)
+ ordered_traits_names = [
+ traits[idx]["trait_fullname"] for idx in traits_order]
strains_and_values = retrieve_strains_and_values(
- ordering_data, strainlist, exported_traits_data_list)
- strains_values = strains_and_values[0][1]
- trait_values = [t[2] for t in strains_and_values]
- traits_filename = generate_traits_filename()
- generate_traits_file(strains_values, trait_values, traits_filename)
+ traits_order, strains, exported_traits_data_list)
+ traits_filename = "{}/traits_test_file_{}.txt".format(
+ TMPDIR, random_string(10))
+ generate_traits_file(
+ strains_and_values[0][1],
+ [t[2] for t in strains_and_values],
+ traits_filename)
+
+ main_output, permutations_output = run_reaper(
+ genotype_filename, traits_filename, separate_nperm_output=True)
+
+ qtlresults = parse_reaper_main_results(main_output)
+ permudata = parse_reaper_permutation_results(permutations_output)
+ organised = organise_reaper_main_results(qtlresults)
+
+ traits_ids = [# sort numerically, but retain the ids as strings
+ str(i) for i in sorted({int(row["ID"]) for row in qtlresults})]
+ chromosome_names = sorted(
+ {row["Chr"] for row in qtlresults}, key = chromosome_sorter_key_fn)
+ loci_names = sorted({row["Locus"] for row in qtlresults})
+ ordered_traits_names = {
+ res_id: trait for res_id, trait in
+ zip(traits_ids,
+ [traits[idx]["trait_fullname"] for idx in traits_order])}
+
+ return generate_clustered_heatmap(
+ process_traits_data_for_heatmap(
+ organised, traits_ids, chromosome_names),
+ "single_heatmap_{}".format(random_string(10)),
+ y_axis=tuple(
+ ordered_traits_names[traits_ids[order]]
+ for order in traits_order),
+ y_label="Traits",
+ x_axis=[chromo for chromo in chromosome_names],
+ x_label="Chromosomes")
return {
"slink_data": slink_data,