Merge remote-tracking branch 'origin/hotfix'

docs/conf.py

@@ -69,7 +69,7 @@
 # The short X.Y version.
 version = '3.0'
 # The full version, including alpha/beta/rc tags.
-release = '3.0.3'
+release = '3.0.4'
 
 
 # The language for content autogenerated by Sphinx. Refer to documentation

docs/index.rst

@@ -56,20 +56,12 @@ New in Release |release|
 
 This is a bugfix release. It fixes the following problem(s):
 
-- When using the ``--additional-report-columns`` parameter in
-  pVACview/pVACfuse, no contents were previously written to the additional columns.
-- MHCflurry may return no value for the percentile binding score. This would
-  previously result in an error which has been fixed in this release.
-- Variants in a VCF may contain an empty AF field, which was previsouly not
-  being handled correctly in all cases, resulting in an error.
-
-This release also includes some minor improvements:
-
-- When running the pVACseq pipeline there would be a lot of warning messages
-  about missing position column parameters. These would mostly be noise
-  because the underlying consequence type wasn't supported by pVACseq to begin
-  with. This release removes these warning messages for mutations with
-  consequences that are not supported by pVACseq.
+- This fixes an issue introduced in the previous release where VCF entries with no
+  VAF value would result in an error.
+- This release adds a new constraint to the vaf cutoff command line arguments
+  to ensure that they are a fraction between 0 and 1.
+- This release also fixes an issue where the wrong binding filter class was
+  being used when running pVACfuse with allele-specific binding cutoffs.
 
 
 New in Version |version|

docs/releases/3_0.rst

@@ -119,3 +119,15 @@ This release also includes some minor improvements:
   because the underlying consequence type wasn't supported by pVACseq to begin
   with. This release removes these warning messages for mutations with
   consequences that are not supported by pVACseq.
+
+Version 3.0.4
+-------------
+
+This is a bugfix release. It fixes the following problem(s):
+
+- This fixes an issue introduced in the previous release where VCF entries with no
+  VAF value would result in an error.
+- This release adds a new constraint to the vaf cutoff command line arguments
+  to ensure that they are a fraction between 0 and 1.
+- This release also fixes an issue where the wrong binding filter class was
+  being used when running pVACfuse with allele-specific binding cutoffs.

pvactools/lib/allele_specific_binding_filter.py

@@ -22,7 +22,7 @@ def execute(self):
             writer.writeheader()
 
             for entry in reader:
-                if self.file_type == 'pVACbind':
+                if self.file_type == 'pVACbind' or self.file_type == 'pVACfuse':
                     if self.top_score_metric == 'median':
                         score = float(entry['Median Score'])
                         percentile_column = 'Median Percentile'

pvactools/lib/input_file_converter.py

@@ -170,13 +170,16 @@ def get_vaf_from_vcf_genotype(self, genotype, alts, alt, af_tag, ad_tag, dp_tag)
             allele_frequencies = genotype.data[af_tag]
             if isinstance(allele_frequencies, list):
                 if len(allele_frequencies) == 0:
-                    vaf = 'NA'
+                    return 'NA'
                 else:
                     vaf = allele_frequencies[alts.index(alt)]
             else:
                 vaf = allele_frequencies
+                if vaf is None or vaf == "":
+                    return 'NA'
             if vaf > 1:
                 print("Warning: VAF is expected to be a fraction, but is larger than 1. If VAFs are encoded as percentages, please adjust the coverage cutoffs accordingly.")
+            return vaf
         else:
             if ad_tag in genotype.data and dp_tag in genotype.data:
                 allele_depths = genotype.data[ad_tag]
@@ -196,10 +199,10 @@ def get_vaf_from_vcf_genotype(self, genotype, alts, alt, af_tag, ad_tag, dp_tag)
                 depth = genotype.data[dp_tag]
                 if depth is None or depth == "":
                     return 'NA'
-                vaf = self.calculate_vaf(int(var_count), int(depth))
+                else:
+                    return self.calculate_vaf(int(var_count), int(depth))
             else:
-                vaf = 'NA'
-        return vaf
+                return 'NA'
 
     def calculate_coverage_for_entry(self, entry, reference, alt, genotype):
         coverage_for_entry = {}

pvactools/lib/run_argument_parser.py

@@ -3,6 +3,7 @@
 
 from pvactools.lib.prediction_class import PredictionClass
 import pvactools.lib.net_chop
+from pvactools.lib.run_utils import *
 
 class RunArgumentParser(metaclass=ABCMeta):
     def __init__(self, tool_name, input_file_help):
@@ -213,18 +214,18 @@ def __init__(self):
             default=10
         )
         self.parser.add_argument(
-            '--normal-vaf', type=float,
-            help="Normal VAF Cutoff. Only sites BELOW this cutoff in normal will be considered.",
+            '--normal-vaf', type=float_range(0.0,1.0),
+            help="Normal VAF Cutoff in decimal format. Only sites BELOW this cutoff in normal will be considered.",
             default=0.02
         )
         self.parser.add_argument(
-            '--tdna-vaf', type=float,
-            help="Tumor DNA VAF Cutoff. Only sites above this cutoff will be considered.",
+            '--tdna-vaf', type=float_range(0.0,1.0),
+            help="Tumor DNA VAF Cutoff in decimal format. Only sites above this cutoff will be considered.",
             default=0.25
         )
         self.parser.add_argument(
-            '--trna-vaf', type=float,
-            help="Tumor RNA VAF Cutoff. Only sites above this cutoff will be considered.",
+            '--trna-vaf', type=float_range(0.0,1.0),
+            help="Tumor RNA VAF Cutoff in decimal format. Only sites above this cutoff will be considered.",
             default=0.25
         )
         self.parser.add_argument(

pvactools/lib/run_utils.py

@@ -5,6 +5,7 @@
 from itertools import islice
 
 from pvactools.lib.prediction_class import *
+import argparse
 
 def split_algorithms(prediction_algorithms):
     if 'all' in prediction_algorithms:
@@ -89,3 +90,25 @@ def split_file(reader, lines):
 
 def construct_index(count, gene, transcript, variant_type, position):
     return '{}.{}.{}.{}.{}'.format(count, gene, transcript, variant_type, position)
+
+def float_range(minimum, maximum):
+    """Return function handle of an argument type function for
+       ArgumentParser checking a float range: minimum <= arg <= maximum
+         minimum - minimum acceptable argument
+         maximum - maximum acceptable argument"""
+
+    # Define the function with default arguments
+    def float_range_checker(arg):
+        """New Type function for argparse - a float within predefined range."""
+
+        try:
+            f = float(arg)
+        except ValueError:
+            raise argparse.ArgumentTypeError("must be a floating point number")
+        if f < minimum or f > maximum:
+            raise argparse.ArgumentTypeError("must be in range [" + str(minimum) + " .. " + str(maximum)+"]")
+        return f
+
+    # Return function handle to checking function
+    return float_range_checker
+

pvactools/tools/pvacseq/coverage_filter.py

@@ -5,6 +5,7 @@
 import csv
 
 from pvactools.lib.filter import Filter
+from pvactools.lib.run_utils import *
 
 def define_parser():
     parser = argparse.ArgumentParser(
@@ -36,18 +37,18 @@ def define_parser():
         default=10
     )
     parser.add_argument(
-        '--normal-vaf', type=float,
-        help="Normal VAF Cutoff. Sites BELOW this cutoff in normal will be considered.",
+        '--normal-vaf', type=float_range(0.0,1.0),
+        help="Normal VAF Cutoff in decimal format. Sites BELOW this cutoff in normal will be considered.",
         default=0.02
     )
     parser.add_argument(
-        '--tdna-vaf', type=float,
-        help="Tumor DNA VAF Cutoff. Sites above this cutoff will be considered.",
+        '--tdna-vaf', type=float_range(0.0,1.0),
+        help="Tumor DNA VAF Cutoff in decimal format. Sites above this cutoff will be considered.",
         default=0.25
     )
     parser.add_argument(
-        '--trna-vaf', type=float,
-        help="Tumor RNA VAF Cutoff. Sites above this cutoff will be considered.",
+        '--trna-vaf', type=float_range(0.0,1.0),
+        help="Tumor RNA VAF Cutoff in decimal format. Sites above this cutoff will be considered.",
         default=0.25
     )
     parser.add_argument(

setup.py

@@ -44,7 +44,7 @@
 
 setup(
     name="pvactools",
-    version="3.0.3",
+    version="3.0.4",
     packages=[
         "pvactools.tools",
         "pvactools.tools.pvacbind",

tests/test_data/input_file_converter/output_empty_vaf.tsv

@@ -0,0 +1,2 @@
+chromosome_name	start	stop	reference	variant	gene_name	transcript_name	transcript_support_level	amino_acid_change	codon_change	ensembl_gene_id	hgvsc	hgvsp	wildtype_amino_acid_sequence	frameshift_amino_acid_sequence	fusion_amino_acid_sequence	variant_type	protein_position	transcript_expression	gene_expression	normal_depth	normal_vaf	tdna_depth	tdna_vaf	trna_depth	trna_vaf	index	protein_length_change
+chr5	109378379	109378382	TCC	AAA	PJA2	ENST00000361189.7	1	G/F	GGA/TTT	ENSG00000198961	ENST00000361189.7:c.1105_1107delinsTTT	ENSP00000354775.2:p.Gly369Phe	MSQYTEKEPAAMDQESGKAVWPKPAGGYQTITGRRYGRRHAYVSFKPCMTRHERSLGRAGDDYEVLELDDVPKENSSGSSPLDQVDSSLPSEPIFEKSETEIPTCGSALNQTTESSQSFVAVHHSEEGRDTLGSSTNLHNHSEGEYIPGACSASSVQNGIALVHTDSYDPDGKHGEDNDHLQLSAEVVEGSRYQESLGNTVFELENREAEAYTGLSPPVPSFNCEVRDEFEELDSVPLVKSSAGDTEFVHQNSQEIQRSSQDEMVSTKQQNNTSQERQTEHSPEDAACGPGHICSEQNTNDREKNHGSSPEQVVRPKVRKLISSSQVDQETGFNRHEAKQRSVQRWREALEVEESGSDDLLIKCEEYDGEHDCMFLDPPYSRVITQRETENNQMTSESGATAGRQEVDNTFWNGCGDYYQLYDKDEDSSECSDGEWSASLPHRFSGTEKDQSSSDESWETLPGKDENEPELQSDSSGPEEENQELSLQEGEQTSLEEGEIPWLQYNEVNESSSDEGNEPANEFAQPAFMLDGNNNLEDDSSVSEDLDVDWSLFDGFADGLGVAEAISYVDPQFLTYMALEERLAQAMETALAHLESLAVDVEVANPPASKESIDGLPETLVLEDHTAIGQEQCCPICCSEYIKDDIATELPCHHFFHKPCVSIWLQKSGTCPVCRRHFPPAVIEASAAPSSEPDPDAPPSNDSIAEAP			missense	369	NA	36.746376	NA	NA	225	0.283	NA	NA	1.PJA2.ENST00000361189.7.missense.369G/F	

tests/test_input_file_converter.py

@@ -78,6 +78,37 @@ def test_input_vcf_generates_expected_tsv(self):
         expected_output_file = os.path.join(self.test_data_dir, 'output.tsv')
         self.assertTrue(cmp(convert_vcf_output_file.name, expected_output_file))
 
+    def test_input_vcf_with_empty_vaf_generates_expected_tsv(self):
+        convert_vcf_input_file  = os.path.join(self.test_data_dir, 'input_empty_vaf_list.vcf.gz')
+        convert_vcf_output_file = tempfile.NamedTemporaryFile()
+
+        convert_vcf_params = {
+            'input_file'  : convert_vcf_input_file,
+            'output_file' : convert_vcf_output_file.name,
+            'sample_name' : 'TUMOR',
+            'normal_sample_name': 'NORMAL',
+        }
+        converter = VcfConverter(**convert_vcf_params)
+
+        self.assertFalse(converter.execute())
+        expected_output_file = os.path.join(self.test_data_dir, 'output_empty_vaf.tsv')
+        self.assertTrue(cmp(convert_vcf_output_file.name, expected_output_file))
+
+        convert_vcf_input_file  = os.path.join(self.test_data_dir, 'input_empty_vaf_single.vcf.gz')
+        convert_vcf_output_file = tempfile.NamedTemporaryFile()
+
+        convert_vcf_params = {
+            'input_file'  : convert_vcf_input_file,
+            'output_file' : convert_vcf_output_file.name,
+            'sample_name' : 'TUMOR',
+            'normal_sample_name': 'NORMAL',
+        }
+        converter = VcfConverter(**convert_vcf_params)
+
+        self.assertFalse(converter.execute())
+        expected_output_file = os.path.join(self.test_data_dir, 'output_empty_vaf.tsv')
+        self.assertTrue(cmp(convert_vcf_output_file.name, expected_output_file))
+
     def test_input_vcf_with_tx_annotation_generates_expected_tsv(self):
         convert_vcf_input_file              = os.path.join(self.test_data_dir, 'input.tx.vcf')
         convert_vcf_output_file             = tempfile.NamedTemporaryFile()

tests/test_pvacseq.py

@@ -263,7 +263,7 @@ def test_pvacseq_pipeline(self):
                 '--keep-tmp-files',
                 '--net-chop-method', 'cterm',
                 '--netmhc-stab',
-                '--tdna-vaf', '20',
+                '--tdna-vaf', '0.2',
                 '-d', 'full',
                 '--pass-only',
                 '--run-reference-proteome-similarity',