fix: add decompress to manta vcf and annotation for normal ratio head…

…er to Tonly samples

workflow/Snakefile

@@ -23,6 +23,7 @@ ruleorder: filtering_bcftools_filter_include_region_snv_tn > bgzip_mutect
 ruleorder: filtering_bcftools_filter_include_region_snv_t > bgzip_mutect
 ruleorder: cnv_sv_manta_run_workflow_t > tabix_cnv
 ruleorder: cnv_sv_manta_run_workflow_tn > tabix_cnv
+ruleorder: filtering_bcftools_filter_include_region_sv > bgzip_cnv
 
 
 aligner = config.get("aligner", None)
@@ -738,6 +739,21 @@ use rule tabix from misc as tabix_cnv with:
         file="cnv_sv/[A-Za-z0-9-_./]+.vcf",
 
 
+use rule bgzip from misc as decompress_manta with:
+    input:
+        "cnv_sv/manta_run_workflow_{analysis}/{sample}.ssa.include.{bed}.vcf.gz",
+    output:
+        "cnv_sv/manta_run_workflow_{analysis}/{sample}.ssa.include.{bed}.vcf",
+    params:
+         extra="-d"
+    log:
+        "cnv_sv/manta_run_workflow_{analysis}/{sample}.ssa.include.{bed}.vcf.log",
+    benchmark:
+        repeat("cnv_sv/manta_run_workflow_{analysis}/{sample}.ssa.include.{bed}.vcf.benchmark.tsv", config.get("bgzip", {}).get("benchmark_repeats", 1))
+    message:
+        "{rule}: decompress {input}"
+
+
 use rule samtools_index from misc as misc_samtools_index with:
     input:
         cram="{file}.crumble.cram",

workflow/scripts/annotate_normal_ratio.py

@@ -19,33 +19,39 @@
 logging.debug("Creating header for " + snakemake.output.vcf)
 vcf_out = VariantFile(snakemake.output.vcf, "w", header=new_header)
 
-sample_tumor = [x for x in list(vcf_in.header.samples) if x.endswith("_T")][0]
-sample_normal = [x for x in list(vcf_in.header.samples) if x.endswith("_N")][0]
-logging.debug(f"{sample_tumor=}, {sample_normal=}")
-
-logging.info("Starting to iterate through input.")
-for record in vcf_in.fetch():
-    try:
-        n_freq = float(record.samples[sample_normal].get("AF")[0])
-    except TypeError:
-        n_freq = 0
-
-    try:
-        t_freq = float(record.samples[sample_tumor].get("AF")[0])
-    except TypeError:
-        t_freq = 0
-
-    if n_freq == 0:
-        logging.warning("Normal freq 0 or missing, setting ratio to 0")
-        ratio = 0
-    elif t_freq == 0:
-        logging.warning("Tumor freq 0 or missing, setting ratio to 100")
-        ratio = 100
-    else:
-        ratio = float(record.samples[sample_normal].get("AF")[0]) / float(record.samples[sample_tumor].get("AF")[0])
-
-    logging.debug(f"{record.samples[sample_normal].get('AF')[0]=}, {record.samples[sample_tumor].get('AF')[0]=}")
-    logging.debug(f"{ratio=}")
-    record.info["N_ratio"] = ratio
-
-    vcf_out.write(record)
+if len(list(vcf_in.header.samples)) > 1:
+    logging.info("Two or more samples identified, proccessing as a TN vcf")
+    sample_tumor = [x for x in list(vcf_in.header.samples) if x.endswith("_T")][0]
+    sample_normal = [x for x in list(vcf_in.header.samples) if x.endswith("_N")][0]
+    logging.debug(f"{sample_tumor=}, {sample_normal=}")
+
+    logging.info("Starting to iterate through input.")
+    for record in vcf_in.fetch():
+        try:
+            n_freq = float(record.samples[sample_normal].get("AF")[0])
+        except TypeError:
+            n_freq = 0
+
+        try:
+            t_freq = float(record.samples[sample_tumor].get("AF")[0])
+        except TypeError:
+            t_freq = 0
+
+        if n_freq == 0:
+            logging.warning("Normal freq 0 or missing, setting ratio to 0")
+            ratio = 0
+        elif t_freq == 0:
+            logging.warning("Tumor freq 0 or missing, setting ratio to 100")
+            ratio = 100
+        else:
+            ratio = float(record.samples[sample_normal].get("AF")[0]) / float(record.samples[sample_tumor].get("AF")[0])
+
+        logging.debug(f"{record.samples[sample_normal].get('AF')[0]=}, {record.samples[sample_tumor].get('AF')[0]=}")
+        logging.debug(f"{ratio=}")
+        record.info["N_ratio"] = ratio
+
+        vcf_out.write(record)
+else:
+    logging.info("Only one sample found in header processing as a T only vcf.")
+    for record in vcf_in.fetch():
+        vcf_out.write(record)