Add VarNet somatic variant calling rule

bin/arch/daylily-analysis-samples-to-manifest.py

@@ -83,7 +83,7 @@ def generate_analysis_manifest(manifest_file, rows):
     header = [
         "samp", "sample", "sample_lane", "SQ", "RU", "EX", "LANE", "r1_path", "r2_path",
         "biological_sex", "iddna_uid", "concordance_control_path", "is_positive_control",
-        "is_negative_control", "sample_type", "merge_single", "external_sample_id",
+        "is_negative_control", "sample_type", "merge_single", "tum_nrm_sampleid_match", "external_sample_id",
         "instrument", "lib_prep", "bwa_kmer", "subsample_pct"
     ]
     with open(manifest_file, "w", newline="") as f:

bin/daylily-analysis-samples-to-manifest-new.py

@@ -66,7 +66,7 @@ def generate_analysis_manifest(manifest_file, rows):
     header = [
         "samp", "sample", "sample_lane", "SQ", "RU", "EX", "LANE", "r1_path", "r2_path",
         "biological_sex", "iddna_uid", "concordance_control_path", "is_positive_control",
-        "is_negative_control", "sample_type", "merge_single", "external_sample_id",
+        "is_negative_control", "sample_type", "merge_single", "tum_nrm_sampleid_match", "external_sample_id",
         "instrument", "lib_prep", "bwa_kmer", "subsample_pct"
     ]
     with open(manifest_file, "w", newline="") as f:

bin/util/downsample_paried_fastq.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python3
+"""
+Downsample paired-end FASTQ(.gz) by pair with a given fraction.
+
+Example:
+  python3 downsample_paired_fastq.py \
+    -1 HG001_30x_R1.fastq.gz -2 HG001_30x_R2.fastq.gz \
+    -f 0.1 -s 42 \
+    -o1 HG001_3x_R1.fastq.gz -o2 HG001_3x_R2.fastq.gz
+"""
+
+import argparse, gzip, io, os, random, sys
+from typing import TextIO
+
+def open_maybe_gzip(path: str, mode: str) -> TextIO:
+    # Large buffer for speed
+    if "r" in mode and "b" not in mode:
+        buffering = 1024 * 1024
+    else:
+        buffering = -1
+    if path.endswith(".gz"):
+        if "r" in mode:
+            return gzip.open(path, mode, encoding="utf-8", newline="")
+        else:
+            # compresslevel 5 is a good speed/size balance
+            return gzip.open(path, mode, compresslevel=5, encoding="utf-8", newline="")
+    else:
+        return open(path, mode, buffering=buffering, encoding="utf-8", newline="")
+
+def norm_name(h: str) -> str:
+    """
+    Normalize a FASTQ header to the read name used for pair matching.
+    Uses first whitespace-delimited token and strips leading '@' and any trailing '/1' or '/2'.
+    """
+    t = h.strip().split()[0]
+    if t.startswith("@"):
+        t = t[1:]
+    if t.endswith("/1") or t.endswith("/2"):
+        t = t[:-2]
+    return t
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("-1", "--r1", required=True, help="R1 FASTQ(.gz)")
+    ap.add_argument("-2", "--r2", required=True, help="R2 FASTQ(.gz)")
+    ap.add_argument("-f", "--fraction", required=True, type=float, help="Keep fraction (0..1)")
+    ap.add_argument("-s", "--seed", type=int, default=42, help="Random seed (default: 42)")
+    ap.add_argument("-o1", "--out1", required=True, help="Output R1 FASTQ(.gz)")
+    ap.add_argument("-o2", "--out2", required=True, help="Output R2 FASTQ(.gz)")
+    ap.add_argument("--no-check-names", action="store_true",
+                    help="Skip read name consistency check (faster, but riskier).")
+    args = ap.parse_args()
+
+    if not (0.0 <= args.fraction <= 1.0):
+        sys.exit("ERROR: --fraction must be in [0,1].")
+
+    rng = random.Random(args.seed)
+    total = 0
+    kept = 0
+
+    with open_maybe_gzip(args.r1, "rt") as f1, open_maybe_gzip(args.r2, "rt") as f2, \
+         open_maybe_gzip(args.out1, "wt") as o1, open_maybe_gzip(args.out2, "wt") as o2:
+        while True:
+            h1 = f1.readline()
+            if not h1:
+                break
+            s1 = f1.readline(); p1 = f1.readline(); q1 = f1.readline()
+            h2 = f2.readline(); s2 = f2.readline(); p2 = f2.readline(); q2 = f2.readline()
+
+            total += 1
+            if not args.no-check-names:
+                if norm_name(h1) != norm_name(h2):
+                    sys.stderr.write(
+                        f"ERROR: Read name mismatch at pair {total}:\nR1: {h1}R2: {h2}\n"
+                    )
+                    sys.exit(2)
+
+            if rng.random() < args.fraction:
+                o1.write(h1); o1.write(s1); o1.write(p1); o1.write(q1)
+                o2.write(h2); o2.write(s2); o2.write(p2); o2.write(q2)
+                kept += 1
+
+    ratio = (kept / total) if total else 0.0
+    sys.stderr.write(f"# pairs processed: {total}\n# pairs kept: {kept} (~{ratio:.6f})\n")
+
+if __name__ == "__main__":
+    main()

bin/util/downsample_paried_fastq_DRIVER.sh

@@ -0,0 +1,44 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+# Source directory with your 30x pairs
+BASEDIR="/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007"
+OUTROOT="${BASEDIR}/downsampled"
+SEED=42
+
+# Desired coverages and corresponding fractions from 30x
+# 3x=0.1, 1.5x=0.05, 1x≈0.0333333333, 0.4x≈0.0133333333, 0.1x≈0.0033333333
+declare -A FRAC=(
+  ["3x"]="0.1"
+  ["1.5x"]="0.05"
+  ["1x"]="0.0333333333"
+  ["0.4x"]="0.0133333333"
+  ["0.1x"]="0.0033333333"
+)
+
+mkdir -p "${OUTROOT}"
+
+for r1 in "${BASEDIR}"/HG*_30x_R1.fastq.gz; do
+  sample="$(basename "${r1}" | cut -d_ -f1)"
+  r2="${BASEDIR}/${sample}_30x_R2.fastq.gz"
+  if [[ ! -f "${r2}" ]]; then
+    echo "Missing R2 for ${sample}" >&2
+    exit 1
+  fi
+
+  for cov in 3x 1.5x 1x 0.4x 0.1x; do
+    frac="${FRAC[$cov]}"
+    outdir="${OUTROOT}/${sample}/${cov}"
+    mkdir -p "${outdir}"
+    o1="${outdir}/${sample}_${cov}_R1.fastq.gz"
+    o2="${outdir}/${sample}_${cov}_R2.fastq.gz"
+
+    echo "[$(date)] ${sample} -> ${cov} (fraction=${frac})"
+    ./downsample_paired_fastq.py \
+      -1 "${r1}" -2 "${r2}" \
+      -f "${frac}" -s "${SEED}" \
+      -o1 "${o1}" -o2 "${o2}"
+  done
+done
+
+echo "Done. Outputs under: ${OUTROOT}"

config/day_profiles/local/templates/rule_config.yaml

@@ -297,7 +297,19 @@ lofreq2:
     hg38_lofreq_chrms: "19~1-50000000,19~50000001-58617616,21~1-46709983"  # 1~1-50000000,1~50000001-100000000,1~100000001-150000000,1~150000001-200000000,1~200000001-248956422,2~1-50000000,2~50000001-100000000,2~100000001-150000000,2~150000001-200000000,2~200000001-242193529,3~1-50000000,3~50000001-100000000,3~100000001-150000000,3~150000001-198295559,4~1-50000000,4~50000001-100000000,4~100000001-150000000,4~150000001-190214555,5~1-50000000,5~50000001-100000000,5~100000001-150000000,5~150000001-181538259,6~1-50000000,6~50000001-100000000,6~100000001-150000000,6~150000001-170805979,7~1-50000000,7~50000001-100000000,7~100000001-150000000,7~150000001-159345973,8~1-50000000,8~50000001-100000000,8~100000001-145138636,9~1-50000000,9~50000001-100000000,9~100000001-138394717,10~1-50000000,10~50000001-100000000,10~100000001-133797422,11~1-50000000,11~50000001-100000000,11~100000001-135086622,12~1-50000000,12~50000001-100000000,12~100000001-133275309,13~1-50000000,13~50000001-100000000,13~100000001-114364328,14~1-50000000,14~50000001-100000000,14~100000001-107043718,15~1-50000000,15~50000001-100000000,15~100000001-101991189,16~1-50000000,16~50000001-90338345,17~1-50000000,17~50000001-83257441,18~1-50000000,18~50000001-80373285,19~1-50000000,19~50000001-58617616,20~1-50000000,20~50000001-64444167,21~1-46709983,22~1-50000000,22~50000001-50818468,23~1-50000000,23~50000001-100000000,23~100000001-150000000,23~150000001-156040895,24~1-50000000,24~50000001-57227415"
     hg38_broad_lofreq_chrms: "19~1-50000000,19~50000001-58617616,21~1-46709983"  # 1~1-50000000,1~50000001-100000000,1~100000001-150000000,1~150000001-200000000,1~200000001-248956422,2~1-50000000,2~50000001-100000000,2~100000001-150000000,2~150000001-200000000,2~200000001-242193529,3~1-50000000,3~50000001-100000000,3~100000001-150000000,3~150000001-198295559,4~1-50000000,4~50000001-100000000,4~100000001-150000000,4~150000001-190214555,5~1-50000000,5~50000001-100000000,5~100000001-150000000,5~150000001-181538259,6~1-50000000,6~50000001-100000000,6~100000001-150000000,6~150000001-170805979,7~1-50000000,7~50000001-100000000,7~100000001-150000000,7~150000001-159345973,8~1-50000000,8~50000001-100000000,8~100000001-145138636,9~1-50000000,9~50000001-100000000,9~100000001-138394717,10~1-50000000,10~50000001-100000000,10~100000001-133797422,11~1-50000000,11~50000001-100000000,11~100000001-135086622,12~1-50000000,12~50000001-100000000,12~100000001-133275309,13~1-50000000,13~50000001-100000000,13~100000001-114364328,14~1-50000000,14~50000001-100000000,14~100000001-107043718,15~1-50000000,15~50000001-100000000,15~100000001-101991189,16~1-50000000,16~50000001-90338345,17~1-50000000,17~50000001-83257441,18~1-50000000,18~50000001-80373285,19~1-50000000,19~50000001-58617616,20~1-50000000,20~50000001-64444167,21~1-46709983,22~1-50000000,22~50000001-50818468,23~1-50000000,23~50000001-100000000,23~100000001-150000000,23~150000001-156040895,24~1-50000000,24~50000001-57227415"  
     b37_lofreq_chrms: "19~1-50000000,19~50000001-59128983,21~1-48129895"  # 1~1-50000000,1~50000001-100000000,1~100000001-150000000,1~150000001-200000000,1~200000001-249250621,2~1-50000000,2~50000001-100000000,2~100000001-150000000,2~150000001-200000000,2~200000001-243199373,3~1-50000000,3~50000001-100000000,3~100000001-150000000,3~150000001-198022430,4~1-50000000,4~50000001-100000000,4~100000001-150000000,4~150000001-191154276,5~1-50000000,5~50000001-100000000,5~100000001-150000000,5~150000001-180915260,6~1-50000000,6~50000001-100000000,6~100000001-150000000,6~150000001-171115067,7~1-50000000,7~50000001-100000000,7~100000001-150000000,7~150000001-159138663,8~1-50000000,8~50000001-100000000,8~100000001-146364022,9~1-50000000,9~50000001-100000000,9~100000001-141213431,10~1-50000000,10~50000001-100000000,10~100000001-135534747,11~1-50000000,11~50000001-100000000,11~100000001-135006516,12~1-50000000,12~50000001-100000000,12~100000001-133851895,13~1-50000000,13~50000001-100000000,13~100000001-115169878,14~1-50000000,14~50000001-100000000,14~100000001-107349540,15~1-50000000,15~50000001-100000000,15~100000001-102531392,16~1-50000000,16~50000001-90354753,17~1-50000000,17~50000001-81195210,18~1-50000000,18~50000001-78077248,19~1-50000000,19~50000001-59128983,20~1-50000000,20~50000001-63025520,21~1-48129895,22~1-50000000,22~50000001-51304566,23~1-50000000,23~50000001-100000000,23~100000001-150000000,23~150000001-155270560,24~1-50000000,24~50000001-59373566"
-    numa: " OMP_THREADS=64 OMP_PROC_BIND=close OMP_PLACES=threads OMP_PROC_BIND=TRUE OMP_DYNAMIC=TRUE OMP_MAX_ACTIVE_LEVELS=1 OMP_SCHEDULE=dynamic OMP_WAIT_POLICY=ACTIVE " 
+    numa: " OMP_THREADS=64 OMP_PROC_BIND=close OMP_PLACES=threads OMP_PROC_BIND=TRUE OMP_DYNAMIC=TRUE OMP_MAX_ACTIVE_LEVELS=1 OMP_SCHEDULE=dynamic OMP_WAIT_POLICY=ACTIVE "
+
+varn:
+    threads: 4
+    partition: "i8"
+    partition_other: "i8"
+    mem_mb: 8000
+    hg38_varn_chrms: "1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24"
+    hg38_broad_varn_chrms: "1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24"
+    b37_varn_chrms: "1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24"
+    numa: ""
+    conda: "../envs/vanilla_v0.1.yaml"
+    varn_container: "docker://skandlab/varnet:latest"
 
 
 multiqc:

config/day_profiles/slurm/templates/rule_config.yaml

@@ -262,7 +262,19 @@ lofreq2:
     hg38_lofreq_chrms: "1~1-50000000,1~50000001-100000000,1~100000001-150000000,1~150000001-200000000,1~200000001-248956422,2~1-50000000,2~50000001-100000000,2~100000001-150000000,2~150000001-200000000,2~200000001-242193529,3~1-50000000,3~50000001-100000000,3~100000001-150000000,3~150000001-198295559,4~1-50000000,4~50000001-100000000,4~100000001-150000000,4~150000001-190214555,5~1-50000000,5~50000001-100000000,5~100000001-150000000,5~150000001-181538259,6~1-50000000,6~50000001-100000000,6~100000001-150000000,6~150000001-170805979,7~1-50000000,7~50000001-100000000,7~100000001-150000000,7~150000001-159345973,8~1-50000000,8~50000001-100000000,8~100000001-145138636,9~1-50000000,9~50000001-100000000,9~100000001-138394717,10~1-50000000,10~50000001-100000000,10~100000001-133797422,11~1-50000000,11~50000001-100000000,11~100000001-135086622,12~1-50000000,12~50000001-100000000,12~100000001-133275309,13~1-50000000,13~50000001-100000000,13~100000001-114364328,14~1-50000000,14~50000001-100000000,14~100000001-107043718,15~1-50000000,15~50000001-100000000,15~100000001-101991189,16~1-50000000,16~50000001-90338345,17~1-50000000,17~50000001-83257441,18~1-50000000,18~50000001-80373285,19~1-50000000,19~50000001-58617616,20~1-50000000,20~50000001-64444167,21~1-46709983,22~1-50000000,22~50000001-50818468,23~1-50000000,23~50000001-100000000,23~100000001-150000000,23~150000001-156040895,24~1-50000000,24~50000001-57227415"
     hg38_broad_lofreq_chrms: "1~1-50000000,1~50000001-100000000,1~100000001-150000000,1~150000001-200000000,1~200000001-248956422,2~1-50000000,2~50000001-100000000,2~100000001-150000000,2~150000001-200000000,2~200000001-242193529,3~1-50000000,3~50000001-100000000,3~100000001-150000000,3~150000001-198295559,4~1-50000000,4~50000001-100000000,4~100000001-150000000,4~150000001-190214555,5~1-50000000,5~50000001-100000000,5~100000001-150000000,5~150000001-181538259,6~1-50000000,6~50000001-100000000,6~100000001-150000000,6~150000001-170805979,7~1-50000000,7~50000001-100000000,7~100000001-150000000,7~150000001-159345973,8~1-50000000,8~50000001-100000000,8~100000001-145138636,9~1-50000000,9~50000001-100000000,9~100000001-138394717,10~1-50000000,10~50000001-100000000,10~100000001-133797422,11~1-50000000,11~50000001-100000000,11~100000001-135086622,12~1-50000000,12~50000001-100000000,12~100000001-133275309,13~1-50000000,13~50000001-100000000,13~100000001-114364328,14~1-50000000,14~50000001-100000000,14~100000001-107043718,15~1-50000000,15~50000001-100000000,15~100000001-101991189,16~1-50000000,16~50000001-90338345,17~1-50000000,17~50000001-83257441,18~1-50000000,18~50000001-80373285,19~1-50000000,19~50000001-58617616,20~1-50000000,20~50000001-64444167,21~1-46709983,22~1-50000000,22~50000001-50818468,23~1-50000000,23~50000001-100000000,23~100000001-150000000,23~150000001-156040895,24~1-50000000,24~50000001-57227415"
     b37_lofreq_chrms: "1~1-50000000,1~50000001-100000000,1~100000001-150000000,1~150000001-200000000,1~200000001-249250621,2~1-50000000,2~50000001-100000000,2~100000001-150000000,2~150000001-200000000,2~200000001-243199373,3~1-50000000,3~50000001-100000000,3~100000001-150000000,3~150000001-198022430,4~1-50000000,4~50000001-100000000,4~100000001-150000000,4~150000001-191154276,5~1-50000000,5~50000001-100000000,5~100000001-150000000,5~150000001-180915260,6~1-50000000,6~50000001-100000000,6~100000001-150000000,6~150000001-171115067,7~1-50000000,7~50000001-100000000,7~100000001-150000000,7~150000001-159138663,8~1-50000000,8~50000001-100000000,8~100000001-146364022,9~1-50000000,9~50000001-100000000,9~100000001-141213431,10~1-50000000,10~50000001-100000000,10~100000001-135534747,11~1-50000000,11~50000001-100000000,11~100000001-135006516,12~1-50000000,12~50000001-100000000,12~100000001-133851895,13~1-50000000,13~50000001-100000000,13~100000001-115169878,14~1-50000000,14~50000001-100000000,14~100000001-107349540,15~1-50000000,15~50000001-100000000,15~100000001-102531392,16~1-50000000,16~50000001-90354753,17~1-50000000,17~50000001-81195210,18~1-50000000,18~50000001-78077248,19~1-50000000,19~50000001-59128983,20~1-50000000,20~50000001-63025520,21~1-48129895,22~1-50000000,22~50000001-51304566,23~1-50000000,23~50000001-100000000,23~100000001-150000000,23~150000001-155270560,24~1-50000000,24~50000001-59373566"
-    numa: " OMP_THREADS=1 OMP_PROC_BIND=close OMP_PLACES=threads OMP_DYNAMIC=true OMP_MAX_ACTIVE_LEVELS=1 OMP_SCHEDULE=dynamic OMP_WAIT_POLICY=ACTIVE " 
+    numa: " OMP_THREADS=1 OMP_PROC_BIND=close OMP_PLACES=threads OMP_DYNAMIC=true OMP_MAX_ACTIVE_LEVELS=1 OMP_SCHEDULE=dynamic OMP_WAIT_POLICY=ACTIVE "
+
+varn:
+    threads: 32
+    partition: "i192,i128,i192mem"
+    partition_other: "i192,i128,i192mem"
+    mem_mb: 64000
+    hg38_varn_chrms: "1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24"
+    hg38_broad_varn_chrms: "1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24"
+    b37_varn_chrms: "1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24"
+    numa: ""
+    conda: "../envs/vanilla_v0.1.yaml"
+    varn_container: "docker://skandlab/varnet:latest"
 
 
 manta_sort_and_index:

giab_30x_hg38_analysis_manifest.csv

@@ -1,5 +1,5 @@
-samp,sample,sample_lane,SQ,RU,EX,LANE,r1_path,r2_path,biological_sex,iddna_uid,concordance_control_path,is_positive_control,is_negative_control,sample_type,merge_single,external_sample_id,instrument,lib_prep,bwa_kmer
-R0_HG001_D0_0,R0_HG001_D0_0,R0_HG001_D0_0,D0,R0,HG001,0,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG001_30x_R1.fastq.gz,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG001_30x_R2.fastq.gz,female,na,/fsx/data/genomic_data/organism_annotations/H_sapiens/hg38/controls/giab/snv/v4.2.1/HG001/,true,false,blood,merge,HG001,NOVASEQ,PCR-FREE,19
+samp,sample,sample_lane,SQ,RU,EX,LANE,r1_path,r2_path,biological_sex,iddna_uid,concordance_control_path,is_positive_control,is_negative_control,sample_type,merge_single,tum_nrm_sampleid_match,external_sample_id,instrument,lib_prep,bwa_kmer
+R0_HG001_D0_0,R0_HG001_D0_0,R0_HG001_D0_0,D0,R0,HG001,0,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG001_30x_R1.fastq.gz,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG001_30x_R2.fastq.gz,female,na,/fsx/data/genomic_data/organism_annotations/H_sapiens/hg38/controls/giab/snv/v4.2.1/HG001/,true,false,blood,merge,HG001,HG001,NOVASEQ,PCR-FREE,19
 R0_HG002_D0_0,R0_HG002_D0_0,R0_HG002_D0_0,D0,R0,HG002,0,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG002_30x_R1.fastq.gz,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG002_30x_R2.fastq.gz,male,na,/fsx/data/genomic_data/organism_annotations/H_sapiens/hg38/controls/giab/snv/v4.2.1/HG002/,true,false,blood,merge,HG002,NOVASEQ,PCR-FREE,19
 R0_HG003_D0_0,R0_HG003_D0_0,R0_HG003_D0_0,D0,R0,HG003,0,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG003_30x_R1.fastq.gz,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG003_30x_R2.fastq.gz,male,na,/fsx/data/genomic_data/organism_annotations/H_sapiens/hg38/controls/giab/snv/v4.2.1/HG003/,true,false,blood,merge,HG003,NOVASEQ,PCR-FREE,19
 R0_HG004_D0_0,R0_HG004_D0_0,R0_HG004_D0_0,D0,R0,HG004,0,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG004_30x_R1.fastq.gz,/fsx/data/genomic_data/organism_reads/H_sapiens/giab/NovaSeqX_WHGS_TruSeqPF_HG002-007/HG004_30x_R2.fastq.gz,female,na,/fsx/data/genomic_data/organism_annotations/H_sapiens/hg38/controls/giab/snv/v4.2.1/HG004/,true,false,blood,merge,HG004,NOVASEQ,PCR-FREE,19

workflow/Snakefile

@@ -273,6 +273,7 @@ include: "rules/go_left.smk"
 # include: "rules/hisat2.smk"
 include: "rules/kat.smk"
 include: "rules/lofreq2.smk"
+include: "rules/varnet.smk"
 include: "rules/manta.smk"
 include: "rules/merge_all_bams.smk"
 include: "rules/mosdepth.smk"