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author | zsloan | 2021-05-21 19:43:23 +0000 |
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committer | zsloan | 2021-05-21 19:43:23 +0000 |
commit | efbe47b58f6e0b9a4b509a28ec8788a1c6dae343 (patch) | |
tree | d09eea867e29a6f1333b2bf0c8625762719babb0 /wqflask | |
parent | c2fac869f5ac1a398677d5646d34a1a0704e29e4 (diff) | |
download | genenetwork2-efbe47b58f6e0b9a4b509a28ec8788a1c6dae343.tar.gz |
run_rqtl now reads in permutation output
Diffstat (limited to 'wqflask')
-rw-r--r-- | wqflask/wqflask/marker_regression/rqtl_mapping.py | 34 |
1 files changed, 32 insertions, 2 deletions
diff --git a/wqflask/wqflask/marker_regression/rqtl_mapping.py b/wqflask/wqflask/marker_regression/rqtl_mapping.py index 3f4899b0..c3f047fc 100644 --- a/wqflask/wqflask/marker_regression/rqtl_mapping.py +++ b/wqflask/wqflask/marker_regression/rqtl_mapping.py @@ -8,6 +8,8 @@ from typing import List from typing import Optional from typing import TextIO +import numpy as np + from base.webqtlConfig import TMPDIR from base.trait import create_trait from utility.tools import locate @@ -46,7 +48,11 @@ def run_rqtl(trait_name, vals, samples, dataset, mapping_scale, method, model, p out_file = requests.post(GN3_RQTL_URL, data=post_data).json()['output_file'] - return process_rqtl_results(out_file) + if num_perm > 0: + perm_results, suggestive, significant = process_perm_results(out_file) + return perm_results, suggestive, significant, process_rqtl_results(out_file) + else: + return process_rqtl_results(out_file) def process_rqtl_results(out_file: str) -> List: @@ -63,6 +69,7 @@ def process_rqtl_results(out_file: str) -> List: for line in the_file: line_items = line.split(",") if line_items[1][1:-1] == "chr" or not line_items: + # Skip header line continue else: # Convert chr to int if possible @@ -81,6 +88,30 @@ def process_rqtl_results(out_file: str) -> List: return marker_obs + +def process_perm_results(out_file: str): + """Given base filename, read in R/qtl permutation output and calculate + suggestive and significant thresholds + + """ + perm_results = [] + with open(GN3_TMP_PATH + "/output/PERM_" + out_file, "r") as the_file: + for i, line in enumerate(the_file): + if i == 0: + # Skip header line + continue + else: + line_items = line.split(",") + perm_results.append(float(line_items[1])) + + logger.debug("PERM RESULTS:", perm_results) + + suggestive = np.percentile(np.array(perm_results), 67) + significant = np.percentile(np.array(perm_results), 95) + + return perm_results, suggestive, significant + + def get_hash_of_textio(the_file: TextIO) -> str: """Given a StringIO, return the hash of its contents""" @@ -146,7 +177,6 @@ def cofactors_to_dict(cofactors: str, dataset_ob, samples) -> Dict: name=cofactor_name) sample_data = trait_ob.data for index, sample in enumerate(samples): - #if (sample in sample_list) and (sample in sample_data): if sample in sample_data: sample_value = sample_data[sample].value cofactors[cofactor_name].append(sample_value) |