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* Add inheritance information to the result vcf

* Fix typo

* Fix a problem with the multiprocessing

* Fix some problems with multiprocessing in standalone mode. Introduce small changes to the result file creation to prevent possible problems if some data is missing.
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@dboceck
dboceck authored Mar 12, 2021
1 parent 20bdf35 commit 13ca753
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Showing 4 changed files with 92 additions and 21 deletions.
101 changes: 85 additions & 16 deletions aidiva/helper_modules/create_result_vcf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,11 @@
def write_header(out_file, single):
out_file.write("##fileformat=VCFv4.1\n")
if not single:
out_file.write("##INFO=<ID=AIDIVA,Number=4,Type=String,Description=\"AIdiva scores: AIdiva-score,AIdiva-final-score,AIdiva-hpo-relatedness,AIdiva-hpo-relatedness-interacting,AIdiva-filter. (AIdiva-score is the pathogenicity prediction from the random forest; AIdiva-final-score is the predction finalized with the given HPO terms; AIdiva-hpo-relatedness indicates how strong the currrent variant is associated with the given HPO terms; AIdiva-filter 0 or 1 wether all internal filters were passed or not)\">\n")
out_file.write("##INFO=<ID=AIDIVA,Number=5,Type=String,Description=\"AIdiva scores: AIdiva-score,AIdiva-final-score,AIdiva-hpo-relatedness,AIdiva-hpo-relatedness-interacting,AIdiva-filter. (AIdiva-score is the pathogenicity prediction from the random forest; AIdiva-final-score is the predction finalized with the given HPO terms; AIdiva-hpo-relatedness indicates how strong the currrent variant is associated with the given HPO terms; AIdiva-filter 0 or 1 wether all internal filters were passed or not)\">\n")
out_file.write("##INFO=<ID=AIDIVA_INHERITANCE,Number=4,Type=String,Description=\"AIdiva inheritance flags: dominant,denovo,recessive,xlinked,compound. (Each value can be 0 or 1)\">\n")
out_file.write("##INFO=<ID=AIDIVA_INHERITANCE_COMMENT,Number=1,Type=String,Description=\"AIdiva inheritance flags (dominant,denovo,recessive,xlinked,compound) in written form\">\n")
else:
out_file.write("##INFO=<ID=AIDIVA,Number=4,Type=String,Description=\"AIdiva scores: AIdiva-score,AIdiva-final-score,AIdiva-hpo-relatedness,AIdiva-hpo-relatedness-interacting,AIdiva-filter. (AIdiva-score is the pathogenicity prediction from the random forest; AIdiva-final-score is the predction finalized with the given HPO terms; AIdiva-hpo-relatedness indicates how strong the currrent variant is associated with the given HPO terms; AIdiva-filter 0 or 1 wether all internal filters were passed or not)\">\n")
out_file.write("##INFO=<ID=AIDIVA,Number=5,Type=String,Description=\"AIdiva scores: AIdiva-score,AIdiva-final-score,AIdiva-hpo-relatedness,AIdiva-hpo-relatedness-interacting,AIdiva-filter. (AIdiva-score is the pathogenicity prediction from the random forest; AIdiva-final-score is the predction finalized with the given HPO terms; AIdiva-hpo-relatedness indicates how strong the currrent variant is associated with the given HPO terms; AIdiva-filter 0 or 1 wether all internal filters were passed or not)\">\n")
out_file.write("##INFO=<ID=AIDIVA_INHERITANCE,Number=2,Type=String,Description=\"AIdiva inheritance flags: recessive,compound. (Each value can be 0 or 1)\">\n")
out_file.write("##INFO=<ID=AIDIVA_INHERITANCE_COMMENT,Number=1,Type=String,Description=\"AIdiva inheritance flags (recessive,compound) in written form\">\n")

Expand Down Expand Up @@ -43,35 +43,104 @@ def write_header(out_file, single):
def write_result_vcf(input_data, vcf_file, single):
input_data = input_data.sort_values(["CHROM", "POS"], ascending=[True, True])
input_data = input_data.reset_index(drop=True)
colnames = input_data.columns

with open(vcf_file, "w") as out:
write_header(out, single)

for row in input_data.itertuples():
if str(row.AIDIVA_SCORE) == "nan":
aidiva_score = ""
if ("AIDIVA_SCORE" in colnames):
if (str(row.AIDIVA_SCORE) == "nan"):
aidiva_score = "."
else:
aidiva_score = str(row.AIDIVA_SCORE)
else:
aidiva_score = str(row.AIDIVA_SCORE)
aidiva_score = "."

if str(row.FINAL_AIDIVA_SCORE) == "nan":
final_aidiva_score = ""
if ("FINAL_AIDIVA_SCORE" in colnames):
if (str(row.FINAL_AIDIVA_SCORE) == "nan"):
final_aidiva_score = "."
else:
final_aidiva_score = str(row.FINAL_AIDIVA_SCORE)
else:
final_aidiva_score = str(row.FINAL_AIDIVA_SCORE)
final_aidiva_score = "."

if str(row.HPO_RELATEDNESS) == "nan":
hpo_relatedness = ""
if ("HPO_RELATEDNESS" in colnames):
if (str(row.HPO_RELATEDNESS) == "nan"):
hpo_relatedness = "."
else:
hpo_relatedness = str(row.HPO_RELATEDNESS)
else:
hpo_relatedness = str(row.HPO_RELATEDNESS)
hpo_relatedness = "."

if str(row.HPO_RELATEDNESS_INTERACTING) == "nan":
hpo_relatedness_interacting = ""
if ("HPO_RELATEDNESS_INTERACTING" in colnames):
if (str(row.HPO_RELATEDNESS_INTERACTING) == "nan"):
hpo_relatedness_interacting = "."
else:
hpo_relatedness_interacting = str(row.HPO_RELATEDNESS_INTERACTING)
else:
hpo_relatedness_interacting = str(row.HPO_RELATEDNESS_INTERACTING)
hpo_relatedness_interacting = "."

if ("FILTER_PASSED" in colnames):
if (str(row.FILTER_PASSED) == "nan"):
filter_passed = "."
else:
filter_passed = str(row.FILTER_PASSED)
else:
filter_passed = "."

if ("DOMINANT" in colnames):
if (str(row.DOMINANT) == "nan"):
dominant = "."
else:
dominant = str(row.DOMINANT)
else:
dominant = "."

if ("DOMINANT_DENOVO" in colnames):
if (str(row.DOMINANT_DENOVO) == "nan"):
dominant_denovo = "."
else:
dominant_denovo = str(row.DOMINANT_DENOVO)
else:
dominant_denovo = "."

if ("RECESSIVE" in colnames):
if (str(row.RECESSIVE) == "nan"):
recessive = "."
else:
recessive = str(row.RECESSIVE)
else:
recessive = "."

if ("XLINKED" in colnames):
if (str(row.XLINKED) == "nan"):
xlinked = "."
else:
xlinked = str(row.XLINKED)
else:
xlinked = "."

if ("COMPOUND" in colnames):
if (str(row.COMPOUND) == "nan"):
compound = "."
else:
compound = str(row.COMPOUND)
else:
compound = "."

if ("INHERITANCE" in colnames):
if (str(row.INHERITANCE) == "nan") or (str(row.INHERITANCE) == ""):
inheritance_comment = "."
else:
inheritance_comment = str(row.INHERITANCE)
else:
inheritance_comment = "."

if not single:
info_entry = "AIDIVA=" + aidiva_score + "," + final_aidiva_score + "," + hpo_relatedness + "," + hpo_relatedness_interacting + "," + str(row.FILTER_PASSED) + ";AIDIVA_INHERITANCE=" + str(row.DOMINANT) + "," + str(row.DOMINANT_DENOVO) + "," + str(row.RECESSIVE) + "," + str(row.XLINKED) + "," + str(row.COMPOUND) + ";AIDIVA_INHERITANCE_COMMENT=" + str(row.INHERITANCE)
info_entry = "AIDIVA=" + aidiva_score + "," + final_aidiva_score + "," + hpo_relatedness + "," + hpo_relatedness_interacting + "," + filter_passed + ";AIDIVA_INHERITANCE=" + dominant + "," + dominant_denovo + "," + recessive + "," + xlinked + "," + compound + ";AIDIVA_INHERITANCE_COMMENT=" + inheritance_comment
else:
info_entry = "AIDIVA=" + aidiva_score + "," + final_aidiva_score + "," + hpo_relatedness + "," + hpo_relatedness_interacting + "," + str(row.FILTER_PASSED) + ";AIDIVA_INHERITANCE=" + str(row.RECESSIVE) + "," + str(row.COMPOUND) + ";AIDIVA_INHERITANCE_COMMENT=" + str(row.INHERITANCE)
info_entry = "AIDIVA=" + aidiva_score + "," + final_aidiva_score + "," + hpo_relatedness + "," + hpo_relatedness_interacting + "," + filter_passed + ";AIDIVA_INHERITANCE=" + recessive + "," + compound + ";AIDIVA_INHERITANCE_COMMENT=" + inheritance_comment

out.write(str(row.CHROM).strip() + "\t" + str(row.POS) + "\t" + "." + "\t" + str(row.REF) + "\t" + str(row.ALT) + "\t" + "." + "\t" + "." + "\t" + info_entry + "\n")

Expand Down
4 changes: 3 additions & 1 deletion aidiva/run_AIdiva.py
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Original file line number Diff line number Diff line change
Expand Up @@ -107,7 +107,9 @@
write_result.write_result_vcf(prioritized_data, str(working_directory + output_filename + ".vcf"), bool(family_type == "SINGLE"))
write_result.write_result_vcf(prioritized_data[prioritized_data["FILTER_PASSED"] == 1], str(working_directory + output_filename + "_filtered.vcf"), bool(family_type == "SINGLE"))
prioritized_data.to_csv(str(working_directory + output_filename + ".csv"), sep="\t", index=False)
prioritized_data[prioritized_data["FILTER_PASSED"] == 1].to_csv(str(working_directory + output_filename + "_passed_filters.csv"), sep="\t", index=False)
prioritized_data[prioritized_data["FILTER_PASSED"] == 1].to_csv(str(working_directory + output_filename + "_filtered.csv"), sep="\t", index=False)
print("Pipeline successfully finsished!")
else:
write_result.write_result_vcf(input_data_snp, str(working_directory + output_filename + ".vcf"), bool(family_type == "SINGLE"))
write_result.write_result_vcf(input_data_snp, str(working_directory + output_filename + "_filtered.vcf"), bool(family_type == "SINGLE"))
print("ERROR: The given input files were empty!")
6 changes: 3 additions & 3 deletions aidiva/run_annotation_and_AIdiva.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@
scoring_model_indel = os.path.dirname(os.path.abspath(__file__)) + "/../data/" + configuration["Analysis-Input"]["scoring-model-indel"]

# obtain number of threads to use during computation
num_cores = configuration["VEP-Annotation"]["num-threads"]
num_cores = int(configuration["VEP-Annotation"]["num-threads"])

# parse disease and inheritance information
if args.hpo_list is not None:
Expand Down Expand Up @@ -133,11 +133,11 @@

# prioritize and filter variants
print("Filter variants and finalize score...")
prioritized_data = prio.prioritize_variants(predicted_data, hpo_resources_folder, family_file, family_type, hpo_file, gene_exclusion_file, num_cores)
prioritized_data = prio.prioritize_variants(predicted_data, hpo_resources_folder, num_cores, family_file, family_type, hpo_file, gene_exclusion_file)

## TODO: create additional output files according to the inheritance information (only filtered data)
write_result.write_result_vcf(prioritized_data, str(working_directory + input_filename + "_aidiva_result.vcf"), bool(family_type == "SINGLE"))
write_result.write_result_vcf(prioritized_data[prioritized_data["FILTER_PASSED"] == 1], str(working_directory + input_filename + "_aidiva_result_filtered.vcf"), bool(family_type == "SINGLE"))
prioritized_data.to_csv(str(working_directory + input_filename + "_aidiva_result.csv"), sep="\t", index=False)
prioritized_data[prioritized_data["FILTER_PASSED"] == 1].to_csv(str(working_directory + input_filename + "_aidiva_result_filt.csv"), sep="\t", index=False)
prioritized_data[prioritized_data["FILTER_PASSED"] == 1].to_csv(str(working_directory + input_filename + "_aidiva_result_filtered.csv"), sep="\t", index=False)
print("Pipeline successfully finsished!")
2 changes: 1 addition & 1 deletion aidiva/variant_prioritization/prioritize_variants.py
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Original file line number Diff line number Diff line change
Expand Up @@ -325,7 +325,7 @@ def add_inheritance_mode(variant, variant_columns):
if variant["XLINKED"] == 1:
inheritance_list.append("XLINKED")

inheritance_mode = ";".join(inheritance_list)
inheritance_mode = "&".join(inheritance_list)

return inheritance_mode

Expand Down

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