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author | Frederick Muriuki Muriithi | 2021-09-15 12:42:38 +0300 |
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committer | Frederick Muriuki Muriithi | 2021-09-15 12:42:38 +0300 |
commit | 347301c1bc60ba5036625364ee48a5d72eeb1186 (patch) | |
tree | a32ba9a5671caa8b4d3f9da551f39564690b7a57 | |
parent | e9fb4e45cfc52c5d86ef534b0e7f42ba8f4c84d3 (diff) | |
download | genenetwork3-347301c1bc60ba5036625364ee48a5d72eeb1186.tar.gz |
Update entry-point function for heatmap generation
Issue:
https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/clustering.gmi
* Copy over code from the proof-of-concept implementation and clean it up a
little for the entry-point function for heatmap generation via the API
-rw-r--r-- | gn3/heatmaps.py | 70 |
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, |