Mercurial > repos > iuc > vsnp_add_zero_coverage
comparison vsnp_add_zero_coverage.py @ 9:40b97055bb99 draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/vsnp commit c38fd63f7980c70390d104a73ba4c72b266444c3
author | iuc |
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date | Fri, 10 Jun 2022 06:08:02 +0000 |
parents | 2e863710a2f0 |
children |
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8:18b59c38017e | 9:40b97055bb99 |
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31 | 31 |
32 | 32 |
33 def get_zero_df(reference): | 33 def get_zero_df(reference): |
34 # Create a zero coverage dictionary. | 34 # Create a zero coverage dictionary. |
35 zero_dict = {} | 35 zero_dict = {} |
36 reference_length = 0 | |
36 for record in SeqIO.parse(reference, "fasta"): | 37 for record in SeqIO.parse(reference, "fasta"): |
37 chrom = record.id | 38 chrom = record.id |
38 total_len = len(record.seq) | 39 total_len = len(record.seq) |
40 reference_length = reference_length + len(record.seq) | |
39 for pos in list(range(1, total_len + 1)): | 41 for pos in list(range(1, total_len + 1)): |
40 zero_dict["%s-%s" % (str(chrom), str(pos))] = 0 | 42 zero_dict["%s-%s" % (str(chrom), str(pos))] = 0 |
41 # Convert it to a data frame with depth_x | 43 # Convert it to a data frame with depth_x |
42 # and depth_y columns - index is NaN. | 44 # and depth_y columns - index is NaN. |
43 zero_df = pandas.DataFrame.from_dict(zero_dict, orient='index', columns=["depth"]) | 45 zero_df = pandas.DataFrame.from_dict(zero_dict, orient='index', columns=["depth"]) |
44 return zero_df | 46 return zero_df, reference_length |
45 | 47 |
46 | 48 |
47 def output_zc_vcf_file(base_file_name, vcf_file, zero_df, total_zero_coverage, output_vcf): | 49 def output_zc_vcf_file(base_file_name, vcf_file, zero_df, total_zero_coverage, output_vcf): |
48 column_names = ["CHROM", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO", "FORMAT", "Sample"] | 50 column_names = ["CHROM", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO", "FORMAT", "Sample"] |
49 vcf_df = pandas.read_csv(vcf_file, sep='\t', header=None, names=column_names, comment='#') | 51 vcf_df = pandas.read_csv(vcf_file, sep='\t', header=None, names=column_names, comment='#') |
80 else: | 82 else: |
81 shutil.move(vcf_file, output_vcf) | 83 shutil.move(vcf_file, output_vcf) |
82 return good_snp_count | 84 return good_snp_count |
83 | 85 |
84 | 86 |
85 def output_metrics_file(base_file_name, average_coverage, genome_coverage, good_snp_count, output_metrics): | 87 def output_metrics_file(base_file_name, average_coverage, genome_coverage, good_snp_count, dbkey, reference, |
86 bam_metrics = [base_file_name, "", "%4f" % average_coverage, genome_coverage] | 88 reference_length, total_zero_coverage, percent_ref_with_zero_coverage, output_metrics): |
87 vcf_metrics = [base_file_name, str(good_snp_count), "", ""] | 89 columns = ["BAM File", "Reference", "reference Length", "Genome with Coverage", "Average Depth", |
88 metrics_columns = ["File", "Number of Good SNPs", "Average Coverage", "Genome Coverage"] | 90 "No Coverage Bases", "Percent Ref with Zero Coverage", "Quality SNPs"] |
91 values = [base_file_name, dbkey, str(reference_length), genome_coverage, average_coverage, | |
92 str(total_zero_coverage), percent_ref_with_zero_coverage, str(good_snp_count)] | |
89 with open(output_metrics, "w") as fh: | 93 with open(output_metrics, "w") as fh: |
90 fh.write("# %s\n" % "\t".join(metrics_columns)) | 94 fh.write("# %s\n" % "\t".join(columns)) |
91 fh.write("%s\n" % "\t".join(bam_metrics)) | 95 fh.write("%s\n" % "\t".join(values)) |
92 fh.write("%s\n" % "\t".join(vcf_metrics)) | |
93 | 96 |
94 | 97 |
95 def output_files(vcf_file, total_zero_coverage, zero_df, output_vcf, average_coverage, genome_coverage, output_metrics): | 98 def output_files(vcf_file, total_zero_coverage, percent_ref_with_zero_coverage, zero_df, output_vcf, |
99 average_coverage, genome_coverage, output_metrics, reference, reference_length, dbkey): | |
96 base_file_name = get_sample_name(vcf_file) | 100 base_file_name = get_sample_name(vcf_file) |
97 good_snp_count = output_zc_vcf_file(base_file_name, vcf_file, zero_df, total_zero_coverage, output_vcf) | 101 good_snp_count = output_zc_vcf_file(base_file_name, vcf_file, zero_df, total_zero_coverage, output_vcf) |
98 output_metrics_file(base_file_name, average_coverage, genome_coverage, good_snp_count, output_metrics) | 102 output_metrics_file(base_file_name, average_coverage, genome_coverage, good_snp_count, dbkey, reference, |
103 reference_length, total_zero_coverage, percent_ref_with_zero_coverage, output_metrics) | |
99 | 104 |
100 | 105 |
101 def get_coverage_and_snp_count(bam_file, vcf_file, reference, output_metrics, output_vcf): | 106 def get_coverage_and_snp_count(bam_file, vcf_file, dbkey, reference, output_metrics, output_vcf): |
102 coverage_df = get_coverage_df(bam_file) | 107 coverage_df = get_coverage_df(bam_file) |
103 zero_df = get_zero_df(reference) | 108 zero_df, reference_length = get_zero_df(reference) |
104 coverage_df = zero_df.merge(coverage_df, left_index=True, right_index=True, how='outer') | 109 coverage_df = zero_df.merge(coverage_df, left_index=True, right_index=True, how='outer') |
105 # depth_x "0" column no longer needed. | 110 # depth_x "0" column no longer needed. |
106 coverage_df = coverage_df.drop(columns=['depth_x']) | 111 coverage_df = coverage_df.drop(columns=['depth_x']) |
107 coverage_df = coverage_df.rename(columns={'depth_y': 'depth'}) | 112 coverage_df = coverage_df.rename(columns={'depth_y': 'depth'}) |
108 # Covert the NaN to 0 coverage and get some metrics. | 113 # Covert the NaN to 0 coverage and get some metrics. |
109 coverage_df = coverage_df.fillna(0) | 114 coverage_df = coverage_df.fillna(0) |
110 coverage_df['depth'] = coverage_df['depth'].apply(int) | 115 coverage_df['depth'] = coverage_df['depth'].apply(int) |
111 total_length = len(coverage_df) | 116 total_length = len(coverage_df) |
112 average_coverage = coverage_df['depth'].mean() | 117 average_coverage = "{:.2f}".format(coverage_df['depth'].mean()) |
113 zero_df = coverage_df[coverage_df['depth'] == 0] | 118 zero_df = coverage_df[coverage_df['depth'] == 0] |
114 total_zero_coverage = len(zero_df) | 119 total_zero_coverage = len(zero_df) |
120 percent_ref_with_zero_coverage = "{:.6%}".format(total_zero_coverage / reference_length * 100) | |
115 total_coverage = total_length - total_zero_coverage | 121 total_coverage = total_length - total_zero_coverage |
116 genome_coverage = "{:.2%}".format(total_coverage / total_length) | 122 genome_coverage = "{:.2%}".format(total_coverage / total_length) |
117 # Output a zero-coverage vcf fil and the metrics file. | 123 # Output a zero-coverage vcf fil and the metrics file. |
118 output_files(vcf_file, total_zero_coverage, zero_df, output_vcf, average_coverage, genome_coverage, output_metrics) | 124 output_files(vcf_file, total_zero_coverage, percent_ref_with_zero_coverage, zero_df, output_vcf, |
125 average_coverage, genome_coverage, output_metrics, reference, reference_length, dbkey) | |
119 | 126 |
120 | 127 |
121 if __name__ == '__main__': | 128 if __name__ == '__main__': |
122 parser = argparse.ArgumentParser() | 129 parser = argparse.ArgumentParser() |
123 | 130 |
124 parser.add_argument('--bam_input', action='store', dest='bam_input', help='bam input file') | 131 parser.add_argument('--bam_input', action='store', dest='bam_input', help='bam input file') |
132 parser.add_argument('--dbkey', action='store', dest='dbkey', help='bam input dbkey') | |
125 parser.add_argument('--output_metrics', action='store', dest='output_metrics', required=False, default=None, help='Output metrics text file') | 133 parser.add_argument('--output_metrics', action='store', dest='output_metrics', required=False, default=None, help='Output metrics text file') |
126 parser.add_argument('--output_vcf', action='store', dest='output_vcf', required=False, default=None, help='Output VCF file') | 134 parser.add_argument('--output_vcf', action='store', dest='output_vcf', required=False, default=None, help='Output VCF file') |
127 parser.add_argument('--reference', action='store', dest='reference', help='Reference dataset') | 135 parser.add_argument('--reference', action='store', dest='reference', help='Reference dataset') |
128 parser.add_argument('--vcf_input', action='store', dest='vcf_input', help='vcf input file') | 136 parser.add_argument('--vcf_input', action='store', dest='vcf_input', help='vcf input file') |
129 | 137 |
130 args = parser.parse_args() | 138 args = parser.parse_args() |
131 | 139 |
132 get_coverage_and_snp_count(args.bam_input, args.vcf_input, args.reference, args.output_metrics, args.output_vcf) | 140 get_coverage_and_snp_count(args.bam_input, args.vcf_input, args.dbkey, args.reference, args.output_metrics, args.output_vcf) |