Mercurial > repos > mheinzl > variant_analyzer2
changeset 84:e46d5e377760 draft
planemo upload for repository https://github.com/Single-Molecule-Genetics/VariantAnalyzerGalaxy/tree/master/tools/variant_analyzer commit ee4a8e6cf290e6c8a4d55f9cd2839d60ab3b11c8-dirty
| author | mheinzl |
|---|---|
| date | Fri, 19 Aug 2022 11:23:37 +0000 |
| parents | 8cec772c0bf1 |
| children | d1cd4cd9f18d |
| files | mut2read.py mut2read.xml mut2sscs.xml read2mut.py read2mut.xml |
| diffstat | 5 files changed, 95 insertions(+), 47 deletions(-) [+] |
line wrap: on
line diff
--- a/mut2read.py Fri Aug 05 08:23:34 2022 +0000 +++ b/mut2read.py Fri Aug 19 11:23:37 2022 +0000 @@ -40,6 +40,8 @@ help='Output FASTQ file of reads with mutations.') parser.add_argument('--outputJson', help='Output JSON file to store collected data.') + parser.add_argument('--refalttiers', action="store_true", + help='Store also information about the reference allele.') return parser @@ -52,6 +54,7 @@ file3 = args.familiesFile outfile = args.outputFastq json_file = args.outputJson + refalttiers = args.refalttiers if os.path.isfile(file1) is False: sys.exit("Error: Could not find '{}'".format(file1)) @@ -189,16 +192,26 @@ line = line.rstrip('\n') splits = line.split('\t') tag = splits[0] - - if tag in tag_dict or tag in tag_dict_ref: - str1 = splits[4] - curr_seq = str1.replace("-", "") - str2 = splits[5] - curr_qual = str2.replace(" ", "") - out.write("@" + splits[0] + "." + splits[1] + "." + splits[2] + "\n") - out.write(curr_seq + "\n") - out.write("+" + "\n") - out.write(curr_qual + "\n") + if refalttiers is True: + if tag in tag_dict or tag in tag_dict_ref: + str1 = splits[4] + curr_seq = str1.replace("-", "") + str2 = splits[5] + curr_qual = str2.replace(" ", "") + out.write("@" + splits[0] + "." + splits[1] + "." + splits[2] + "\n") + out.write(curr_seq + "\n") + out.write("+" + "\n") + out.write(curr_qual + "\n") + else: + if tag in tag_dict: + str1 = splits[4] + curr_seq = str1.replace("-", "") + str2 = splits[5] + curr_qual = str2.replace(" ", "") + out.write("@" + splits[0] + "." + splits[1] + "." + splits[2] + "\n") + out.write(curr_seq + "\n") + out.write("+" + "\n") + out.write(curr_qual + "\n") if __name__ == '__main__':
--- a/mut2read.xml Fri Aug 05 08:23:34 2022 +0000 +++ b/mut2read.xml Fri Aug 19 11:23:37 2022 +0000 @@ -1,5 +1,5 @@ <?xml version="1.0" encoding="UTF-8"?> -<tool id="mut2read" name="DCS mutations to tags/reads:" version="3.0.0" profile="19.01"> +<tool id="mut2read" name="DCS mutations to tags/reads:" version="3.1.0" profile="19.01"> <description>Extracts all tags that carry a mutation in the duplex consensus sequence (DCS)</description> <macros> <import>va_macros.xml</import> @@ -12,6 +12,7 @@ --mutFile '$file1' --bamFile bam_input.bam --familiesFile '$file3' + $refalttiers --outputFastq '$output_fastq' --outputJson '$output_json' ]]> @@ -20,6 +21,7 @@ <param name="file1" type="data" format="vcf" label="DCS Mutation File" optional="false" help="VCF file with DCS mutations. See the Help section below for a detailed explanation."/> <param name="file2" type="data" format="bam" label="DCS BAM File" optional="false" help="BAM file with aligned DCS reads."/> <param name="file3" type="data" format="tabular" label="Aligned Families File" optional="false" help="TABULAR file with aligned families."/> + <param name="refalttiers" type="boolean" label="Extract tiers also for reference allele" truevalue="--refalttiers" falsevalue="" checked="False" help="Extracts tier information for the alternate and reference allele. Note that this will increase the running time of the tool. Otherwise only the tier information for the alternate allele is extracted."/> </inputs> <outputs> <data name="output_fastq" format="fastq" label="${tool.name} on ${on_string}: FASTQ"/> @@ -40,7 +42,7 @@ Takes a VCF file with mutations, a BAM file of aligned DCS reads, and a tabular file with aligned families as input and prints all tags of reads that carry a mutation or have the reference allele to a user-specified output file and creates a fastq file of -reads of tags with a mutation and the reference allele. +reads of tags with a mutation (and optional the reference allele). **Input**
--- a/mut2sscs.xml Fri Aug 05 08:23:34 2022 +0000 +++ b/mut2sscs.xml Fri Aug 19 11:23:37 2022 +0000 @@ -1,5 +1,5 @@ <?xml version="1.0" encoding="UTF-8"?> -<tool id="mut2sscs" name="DCS mutations to SSCS stats:" version="3.0.0" profile="19.01"> +<tool id="mut2sscs" name="DCS mutations to SSCS stats:" version="3.1.0" profile="19.01"> <description>Extracts all tags from the single-stranded consensus sequence (SSCS) bam file that carries a mutation at the same position a mutation is called in the duplex consensus sequence (DCS) and calculates their frequencies</description> <macros> <import>va_macros.xml</import>
--- a/read2mut.py Fri Aug 05 08:23:34 2022 +0000 +++ b/read2mut.py Fri Aug 19 11:23:37 2022 +0000 @@ -67,6 +67,9 @@ help='Count mutation as an artifact if mutation lies within this parameter away from the softclipping part of the read.') parser.add_argument('--reads_threshold', type=float, default=1.0, help='Float number which specifies the minimum percentage of softclipped reads in a family to be considered in the softclipping tiers. Default: 1.0, means all reads of a family have to be softclipped.') + parser.add_argument('--refalttiers', action="store_true", + help='Store also information about the reference allele.') + return parser @@ -87,6 +90,7 @@ outfile2 = args.outputFile2 outfile3 = args.outputFile3 outputFile_csv = args.outputFile_csv + refalttiers = args.refalttiers thresh = args.thresh phred_score = args.phred @@ -425,8 +429,8 @@ counts_mut = 0 chimeric_tag_list = [] chimeric_tag = {} + if (key1 in pure_tags_dict_short.keys()) or (key1 in pure_tags_dict_ref.keys()): # ref or alt - # if key1 not in np.array(['#'.join(str(i) for i in z) # for z in zip(mut_array[:, 0], mut_array[:, 1], mut_array[:, 2], mut_array[:, 3])]): # continue @@ -478,6 +482,9 @@ elif key2[:-5] in tag_dict_ref.keys(): variant_type = "ref" + if refalttiers is False and variant_type == "ref": # if we only want information about alt tiers, skip all refs + continue + if key2[:-5] + '.ab.1' in mut_dict[key1].keys(): total1 = sum(mut_dict[key1][key2[:-5] + '.ab.1'].values()) if 'na' in mut_dict[key1][key2[:-5] + '.ab.1'].keys(): @@ -682,8 +689,6 @@ # used_keys_ref.append(key2[:-5]) counts_mut += 1 - if key2[:-5] == "CTTGAACACGTCAGCATGCATGGAGA": - print(key1, variant_type, (alt1f + alt2f + alt3f + alt4f) > 0.5, (ref1f + ref2f + ref3f + ref4f) > 0.5) if (variant_type == "alt" and ((alt1f + alt2f + alt3f + alt4f) > 0.5)) or (variant_type == "ref" and ((ref1f + ref2f + ref3f + ref4f) > 0.5)): if variant_type == "alt": tier1ff, tier2ff, tier3ff, tier4ff = alt1f, alt2f, alt3f, alt4f @@ -1345,10 +1350,9 @@ ws1.conditional_format('M{}:N{}'.format(row + 1, row + 2), {'type': 'formula', 'criteria': '=OR($B${}="1.1", $B${}="1.2")'.format(row + 1, row + 1), 'format': format1, 'multi_range': 'M{}:N{} S{}:T{} B{}'.format(row + 1, row + 2, row + 1, row + 2, row + 1, row + 2)}) ws1.conditional_format('M{}:N{}'.format(row + 1, row + 2), {'type': 'formula', 'criteria': '=OR($B${}="2.1", $B${}="2.2", $B${}="2.3", $B${}="2.4", $B${}="2.5")'.format(row + 1, row + 1, row + 1, row + 1, row + 1), 'format': format3, 'multi_range': 'M{}:N{} S{}:T{} B{}'.format(row + 1, row + 2, row + 1, row + 2, row + 1, row + 2)}) ws1.conditional_format('M{}:N{}'.format(row + 1, row + 2), {'type': 'formula', 'criteria': '=$B${}>="3"'.format(row + 1), 'format': format2, 'multi_range': 'M{}:N{} S{}:T{} B{}'.format(row + 1, row + 2, row + 1, row + 2, row + 1, row + 2)}) + row += 3 else: - change_tier_after_print.append((line, line2, trimmed_actual_high_tier)) - - row += 3 + change_tier_after_print.append((line, line2, trimmed_actual_high_tier)) if chimera_correction: chimeric_dcs_high_tiers = 0 @@ -1416,20 +1420,32 @@ row += 3 # sheet 2 - if chimera_correction: - header_line2 = ('variant ID', 'cvrg', 'AC alt (all tiers)', 'AF (all tiers)', 'cvrg (tiers 1.1-2.5)', 'AC ref (tiers 1.1-2.5)', 'AC alt (tiers 1.1-2.5)', 'AF (tiers 1.1-2.5)', 'chimera-corrected cvrg (tiers 1.1-2.5)', 'chimeras in AC alt (tiers 1.1-2.5)', 'chimera-corrected AF (tiers 1.1-2.5)', 'AC alt (orginal DCS)', 'AF (original DCS)', - 'tier 1.1 (alt)', 'tier 1.2 (alt)', 'tier 2.1 (alt)', 'tier 2.2 (alt)', 'tier 2.3 (alt)', 'tier 2.4 (alt)', 'tier 2.5 (alt)', - 'tier 3.1 (alt)', 'tier 3.2 (alt)', 'tier 4 (alt)', 'tier 5.1 (alt)', 'tier 5.2 (alt)', 'tier 5.3 (alt)', 'tier 5.4 (alt)', 'tier 5.5 (alt)', 'tier 6 (alt)', 'tier 7 (alt)', - 'tier 1.1 (ref)', 'tier 1.2 (ref)', 'tier 2.1 (ref)', 'tier 2.2 (ref)', 'tier 2.3 (ref)', 'tier 2.4 (ref)', 'tier 2.5 (ref)', - 'tier 3.1 (ref)', 'tier 3.2 (ref)', 'tier 4 (ref)', 'tier 5.1 (ref)', 'tier 5.2 (ref)', 'tier 5.3 (ref)', 'tier 5.4 (ref)', 'tier 5.5 (ref)', 'tier 6 (ref)', 'tier 7 (ref)' - ) + if refalttiers: + if chimera_correction: + header_line2 = ('variant ID', 'cvrg', 'AC alt (all tiers)', 'AF (all tiers)', 'cvrg (tiers 1.1-2.5)', 'AC ref (tiers 1.1-2.5)', 'AC alt (tiers 1.1-2.5)', 'AF (tiers 1.1-2.5)', 'chimera-corrected cvrg (tiers 1.1-2.5)', 'chimeras in AC alt (tiers 1.1-2.5)', 'chimera-corrected AF (tiers 1.1-2.5)', 'AC alt (orginal DCS)', 'AF (original DCS)', + 'tier 1.1 (alt)', 'tier 1.2 (alt)', 'tier 2.1 (alt)', 'tier 2.2 (alt)', 'tier 2.3 (alt)', 'tier 2.4 (alt)', 'tier 2.5 (alt)', + 'tier 3.1 (alt)', 'tier 3.2 (alt)', 'tier 4 (alt)', 'tier 5.1 (alt)', 'tier 5.2 (alt)', 'tier 5.3 (alt)', 'tier 5.4 (alt)', 'tier 5.5 (alt)', 'tier 6 (alt)', 'tier 7 (alt)', + 'tier 1.1 (ref)', 'tier 1.2 (ref)', 'tier 2.1 (ref)', 'tier 2.2 (ref)', 'tier 2.3 (ref)', 'tier 2.4 (ref)', 'tier 2.5 (ref)', + 'tier 3.1 (ref)', 'tier 3.2 (ref)', 'tier 4 (ref)', 'tier 5.1 (ref)', 'tier 5.2 (ref)', 'tier 5.3 (ref)', 'tier 5.4 (ref)', 'tier 5.5 (ref)', 'tier 6 (ref)', 'tier 7 (ref)' + ) + else: + header_line2 = ('variant ID', 'cvrg', 'AC alt (all tiers)', 'AF (all tiers)', 'cvrg (tiers 1.1-2.5)', 'AC ref (tiers 1.1-2.5)', 'AC alt (tiers 1.1-2.5)', 'AF (tiers 1.1-2.5)', 'AC alt (orginal DCS)', 'AF (original DCS)', + 'tier 1.1 (alt)', 'tier 1.2 (alt)', 'tier 2.1 (alt)', 'tier 2.2 (alt)', 'tier 2.3 (alt)', 'tier 2.4 (alt)', 'tier 2.5 (alt)', + 'tier 3.1 (alt)', 'tier 3.2 (alt)', 'tier 4 (alt)', 'tier 5.1 (alt)', 'tier 5.2 (alt)', 'tier 5.3 (alt)', 'tier 5.4 (alt)', 'tier 5.5 (alt)', 'tier 6 (alt)', 'tier 7 (alt)', + 'tier 1.1 (ref)', 'tier 1.2 (ref)', 'tier 2.1 (ref)', 'tier 2.2 (ref)', 'tier 2.3 (ref)', 'tier 2.4 (ref)', 'tier 2.5 (ref)', + 'tier 3.1 (ref)', 'tier 3.2 (ref)', 'tier 4 (ref)', 'tier 5.1 (ref)', 'tier 5.2 (ref)', 'tier 5.3 (ref)', 'tier 5.4 (ref)', 'tier 5.5 (ref)', 'tier 6 (ref)', 'tier 7 (ref)' + ) else: - header_line2 = ('variant ID', 'cvrg', 'AC alt (all tiers)', 'AF (all tiers)', 'cvrg (tiers 1.1-2.5)', 'AC ref (tiers 1.1-2.5)', 'AC alt (tiers 1.1-2.5)', 'AF (tiers 1.1-2.5)', 'AC alt (orginal DCS)', 'AF (original DCS)', - 'tier 1.1 (alt)', 'tier 1.2 (alt)', 'tier 2.1 (alt)', 'tier 2.2 (alt)', 'tier 2.3 (alt)', 'tier 2.4 (alt)', 'tier 2.5 (alt)', - 'tier 3.1 (alt)', 'tier 3.2 (alt)', 'tier 4 (alt)', 'tier 5.1 (alt)', 'tier 5.2 (alt)', 'tier 5.3 (alt)', 'tier 5.4 (alt)', 'tier 5.5 (alt)', 'tier 6 (alt)', 'tier 7 (alt)', - 'tier 1.1 (ref)', 'tier 1.2 (ref)', 'tier 2.1 (ref)', 'tier 2.2 (ref)', 'tier 2.3 (ref)', 'tier 2.4 (ref)', 'tier 2.5 (ref)', - 'tier 3.1 (ref)', 'tier 3.2 (ref)', 'tier 4 (ref)', 'tier 5.1 (ref)', 'tier 5.2 (ref)', 'tier 5.3 (ref)', 'tier 5.4 (ref)', 'tier 5.5 (ref)', 'tier 6 (ref)', 'tier 7 (ref)' - ) + if chimera_correction: + header_line2 = ('variant ID', 'cvrg', 'AC alt (all tiers)', 'AF (all tiers)', 'cvrg (tiers 1.1-2.5)', 'AC alt (tiers 1.1-2.5)', 'AF (tiers 1.1-2.5)', 'chimera-corrected cvrg (tiers 1.1-2.5)', 'chimeras in AC alt (tiers 1.1-2.5)', 'chimera-corrected AF (tiers 1.1-2.5)', 'AC alt (orginal DCS)', 'AF (original DCS)', + 'tier 1.1 (alt)', 'tier 1.2 (alt)', 'tier 2.1 (alt)', 'tier 2.2 (alt)', 'tier 2.3 (alt)', 'tier 2.4 (alt)', 'tier 2.5 (alt)', + 'tier 3.1 (alt)', 'tier 3.2 (alt)', 'tier 4 (alt)', 'tier 5.1 (alt)', 'tier 5.2 (alt)', 'tier 5.3 (alt)', 'tier 5.4 (alt)', 'tier 5.5 (alt)', 'tier 6 (alt)', 'tier 7 (alt)' + ) + else: + header_line2 = ('variant ID', 'cvrg', 'AC alt (all tiers)', 'AF (all tiers)', 'cvrg (tiers 1.1-2.5)', 'AC alt (tiers 1.1-2.5)', 'AF (tiers 1.1-2.5)', 'AC alt (orginal DCS)', 'AF (original DCS)', + 'tier 1.1 (alt)', 'tier 1.2 (alt)', 'tier 2.1 (alt)', 'tier 2.2 (alt)', 'tier 2.3 (alt)', 'tier 2.4 (alt)', 'tier 2.5 (alt)', + 'tier 3.1 (alt)', 'tier 3.2 (alt)', 'tier 4 (alt)', 'tier 5.1 (alt)', 'tier 5.2 (alt)', 'tier 5.3 (alt)', 'tier 5.4 (alt)', 'tier 5.5 (alt)', 'tier 6 (alt)', 'tier 7 (alt)' + ) ws2.write_row(0, 0, header_line2) row = 0 @@ -1458,7 +1474,10 @@ if sum(used_tiers) == 0: # skip mutations that are filtered by the VA in the first place continue lst.extend([sum(used_tiers), safe_div(sum(used_tiers), cvrg)]) - lst.extend([(sum(used_tiers_ref[0:7]) + sum(used_tiers[0:7])), sum(used_tiers_ref[0:7]), sum(used_tiers[0:7]), safe_div(sum(used_tiers[0:7]), (sum(used_tiers_ref[0:7]) + sum(used_tiers[0:7])))]) + if refalttiers: + lst.extend([(sum(used_tiers_ref[0:7]) + sum(used_tiers[0:7])), sum(used_tiers_ref[0:7]), sum(used_tiers[0:7]), safe_div(sum(used_tiers[0:7]), (sum(used_tiers_ref[0:7]) + sum(used_tiers[0:7])))]) + else: + lst.extend([(cvrg - sum(used_tiers[-10:])), sum(used_tiers[0:7]), safe_div(sum(used_tiers[0:7]), (cvrg - sum(used_tiers[-10:])))]) if chimera_correction: chimeras_all = chimera_dict[key1][1] new_alt = sum(used_tiers[0:7]) - chimeras_all @@ -1469,18 +1488,29 @@ lst.extend([new_cvrg, chimeras_all, safe_div(new_alt, new_cvrg)]) lst.extend([alt_count, safe_div(alt_count, cvrg)]) lst.extend(used_tiers) - lst.extend(used_tiers_ref) + if refalttiers: + lst.extend(used_tiers_ref) # lst.extend(cum_af) lst = tuple(lst) ws2.write_row(row + 1, 0, lst) - if chimera_correction: - ws2.conditional_format('N{}:O{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$N$1="tier 1.1 (alt)"', 'format': format12, 'multi_range': 'N{}:O{} N1:O1 AE{}:AF{} AE1:AF1'.format(row + 2, row + 2, row + 2, row + 2)}) - ws2.conditional_format('P{}:T{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$P$1="tier 2.1 (alt)"', 'format': format32, 'multi_range': 'P{}:T{} P1:T1 AG{}:AK{} AG1:AK1'.format(row + 2, row + 2, row + 2, row + 2)}) - ws2.conditional_format('U{}:AD{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$U$1="tier 3.1 (alt)"', 'format': format22, 'multi_range': 'U{}:AD{} U1:AD1 AL{}:AU{} AL1:AU1'.format(row + 2, row + 2, row + 2, row + 2)}) + if refalttiers: + if chimera_correction: + ws2.conditional_format('N{}:O{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$N$1="tier 1.1 (alt)"', 'format': format12, 'multi_range': 'N{}:O{} N1:O1 AE{}:AF{} AE1:AF1'.format(row + 2, row + 2, row + 2, row + 2)}) + ws2.conditional_format('P{}:T{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$P$1="tier 2.1 (alt)"', 'format': format32, 'multi_range': 'P{}:T{} P1:T1 AG{}:AK{} AG1:AK1'.format(row + 2, row + 2, row + 2, row + 2)}) + ws2.conditional_format('U{}:AD{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$U$1="tier 3.1 (alt)"', 'format': format22, 'multi_range': 'U{}:AD{} U1:AD1 AL{}:AU{} AL1:AU1'.format(row + 2, row + 2, row + 2, row + 2)}) + else: + ws2.conditional_format('K{}:L{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$K$1="tier 1.1 (alt)"', 'format': format12, 'multi_range': 'K{}:L{} K1:L1 AB{}:AC{} AB1:AC1'.format(row + 2, row + 2, row + 2, row + 2)}) + ws2.conditional_format('M{}:Q{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$M$1="tier 2.1 (alt)"', 'format': format32, 'multi_range': 'M{}:Q{} M1:Q1 AD{}:AH{} AD1:AH1'.format(row + 2, row + 2, row + 2, row + 2)}) + ws2.conditional_format('R{}:AA{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$R$1="tier 3.1 (alt)"', 'format': format22, 'multi_range': 'R{}:AA{} R1:AA1 AI{}:AR{} AI1:AR1'.format(row + 2, row + 2, row + 2, row + 2)}) else: - ws2.conditional_format('K{}:L{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$K$1="tier 1.1 (alt)"', 'format': format12, 'multi_range': 'K{}:L{} K1:L1 AB{}:AC{} AB1:AC1'.format(row + 2, row + 2, row + 2, row + 2)}) - ws2.conditional_format('M{}:Q{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$M$1="tier 2.1 (alt)"', 'format': format32, 'multi_range': 'M{}:Q{} M1:Q1 AD{}:AH{} AD1:AH1'.format(row + 2, row + 2, row + 2, row + 2)}) - ws2.conditional_format('R{}:AA{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$R$1="tier 3.1 (alt)"', 'format': format22, 'multi_range': 'R{}:AA{} R1:AA1 AI{}:AR{} AI1:AR1'.format(row + 2, row + 2, row + 2, row + 2)}) + if chimera_correction: + ws2.conditional_format('M{}:N{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$M$1="tier 1.1 (alt)"', 'format': format12, 'multi_range': 'M{}:N{} M1:N1'.format(row + 2, row + 2)}) + ws2.conditional_format('O{}:S{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$O$1="tier 2.1 (alt)"', 'format': format32, 'multi_range': 'O{}:S{} O1:S1'.format(row + 2, row + 2)}) + ws2.conditional_format('T{}:AC{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$T$1="tier 3.1 (alt)"', 'format': format22, 'multi_range': 'T{}:AC{} T1:AC1'.format(row + 2, row + 2)}) + else: + ws2.conditional_format('J{}:K{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$J$1="tier 1.1 (alt)"', 'format': format12, 'multi_range': 'J{}:K{} J1:K1'.format(row + 2, row + 2)}) + ws2.conditional_format('L{}:P{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$L$1="tier 2.1 (alt)"', 'format': format32, 'multi_range': 'L{}:P{} L1:P1'.format(row + 2, row + 2)}) + ws2.conditional_format('Q{}:Z{}'.format(row + 2, row + 2), {'type': 'formula', 'criteria': '=$Q$1="tier 3.1 (alt)"', 'format': format22, 'multi_range': 'Q{}:Z{} Q1:Z1'.format(row + 2, row + 2)}) row += 1 # sheet 3 @@ -1612,9 +1642,9 @@ ex = examples_tiers[i] for k in range(len(ex)): ws3.write_row(start_row + 2 + row + i + k + 2, 0, ex[k]) - ws3.conditional_format('M{}:N{}'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 3), - {'type': 'formula', 'criteria': '=OR($B${}="1.1", $B${}="1.2")'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 2), - 'format': format13, + ws3.conditional_format('M{}:N{}'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 3), + {'type': 'formula', 'criteria': '=OR($B${}="1.1", $B${}="1.2")'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 2), + 'format': format13, 'multi_range': 'M{}:N{} U{}:V{} B{}'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 3, start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 3, start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 3)}) ws3.conditional_format('M{}:N{}'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 3), {'type': 'formula', 'criteria': '=OR($B${}="2.1",$B${}="2.2", $B${}="2.3", $B${}="2.4", $B${}="2.5")'.format(start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 2, start_row + 2 + row + i + k + 2),
--- a/read2mut.xml Fri Aug 05 08:23:34 2022 +0000 +++ b/read2mut.xml Fri Aug 19 11:23:37 2022 +0000 @@ -1,5 +1,5 @@ <?xml version="1.0" encoding="UTF-8"?> -<tool id="read2mut" name="Call specific mutations in reads:" version="3.0.0" profile="19.01"> +<tool id="read2mut" name="Call specific mutations in reads:" version="3.1.0" profile="19.01"> <description>Looks for reads with a mutation at known positions and calculates frequencies and stats.</description> <macros> <import>va_macros.xml</import> @@ -19,6 +19,7 @@ --phred '$phred' --trim '$trim' $chimera_correction + $refalttiers --softclipping_dist '$softclipping_dist' --reads_threshold '$reads_threshold' --outputFile '$output_xlsx' @@ -37,7 +38,8 @@ <param name="trim" type="integer" label="Trimming threshold" value="10" help="Integer threshold for assigning mutations at start and end of reads to lower tier. Default 10."/> <param name="chimera_correction" type="boolean" label="Apply chimera correction?" truevalue="--chimera_correction" falsevalue="" checked="False" help="Count chimeric variants (not for the reference allele) and correct the variant frequencies."/> <param name="softclipping_dist" type="integer" label="Distance between artifact and softclipping of the reads" min="1" value="15" help="Count mutation as an artifact if mutation lies within this parameter away from the softclipping part of the reads. Default = 20"/> -<param name="reads_threshold" type="float" label="Minimum percentage of softclipped reads in a family" min="0.0" max="1.0" value="1.0" help="Float number which specifies the minimum percentage of softclipped reads in a family to be considered in the softclipping tiers. Default: 1.0, means all reads of a family have to be softclipped."/> + <param name="reads_threshold" type="float" label="Minimum percentage of softclipped reads in a family" min="0.0" max="1.0" value="1.0" help="Float number which specifies the minimum percentage of softclipped reads in a family to be considered in the softclipping tiers. Default: 1.0, means all reads of a family have to be softclipped."/> + <param name="refalttiers" type="boolean" label="Extract tiers also for reference allele" truevalue="--refalttiers" falsevalue="" checked="False" help="Extracts tier information for the alternate and reference allele. Note that this will increase the running time of the tool. Otherwise only the tier information for the alternate allele is extracted."/> </inputs> <outputs> <data name="output_xlsx" format="xlsx" label="${tool.name} on ${on_string}: XLSX summary"/> @@ -57,6 +59,7 @@ <param name="chimera_correction"/> <param name="softclipping_dist" value="15"/> <param name="reads_threshold" value="1.0"/> + <param name="refalttiers"/> <output name="output_xlsx" file="Variant_Analyzer_summary_test.xlsx" decompress="true"/> <output name="outputFile_csv" file="Variant_Analyzer_summary_test.csv" decompress="true"/> <output name="output_xlsx2" file="Variant_Analyzer_allele_frequencies_test.xlsx" decompress="true"/> @@ -84,7 +87,7 @@ in the DCS. **Dataset 4:** JSON file generated by the **DCS mutations to SSCS stats** tool -stats of tags that carry a mutation and the reference allele in the SSCS at the same position a mutation +stats of tags that carry a mutation (and optional the reference allele) in the SSCS at the same position a mutation is called in the DCS. **Output**