ontr10doradosup5khz_ssrs is preset for ONT R10 Dorado 5 "Sup" basecaller

December 1, 2025 · View on GitHub

Input Preparation

Generate reference index

Index the reference genome with samtools.

samtools faidx reference.fasta

Generate alignment and index files

Produce read-to-reference alignment via minimap2 and sort/index the bam by samtools.

# generate alignment flie with minimap2 according to the sequencing platform e.g. map-pb/map-ont/map-hifi
# Note that the MD-tag is required by sniffles (–MD).
minimap2 --MD -ax map-ont -t 10 reference.fasta reads.fastq -o alignment.sam

# sort alignment file
samtools sort -@ 10 alignment.sam -o alignment.bam

# index alignment file
samtools index -@ 10 alignment.bam

Generate single nucleotide polymorphism (SNP) file

ClairS-TO Caller

INPUT_BAM_DIR="/path/to/bam"
INPUT_REF_DIR="/path/to/reference"
OUTPUT_DIR="/path/to/output"
BAM="alignment.bam"
REF="reference.fasta"
THREADS=64
MODEL="ont_r10_dorado_sup_5khz_ssrs"
# ont_r10_dorado_sup_5khz_ssrs is preset for ONT R10 Dorado 5 "Sup" basecaller
# ssrs is a model trained initially with synthetic samples and then real samples augmented
# if you do not want to use real data, use the ss model.
# for PacBio-HiFi reads: hifi_revio_ssrs

sudo docker run \
-v ${INPUT_BAM_DIR}:${INPUT_BAM_DIR} \
-v ${INPUT_REF_DIR}:${INPUT_REF_DIR} \
-v ${OUTPUT_DIR}:${OUTPUT_DIR} \
-u $(id -u):$(id -g) \
hkubal/clairs-to:v0.3.0 \
/opt/bin/run_clairs_to \
--tumor_bam_fn ${INPUT_BAM_DIR}/${BAM} \
--ref_fn ${INPUT_REF_DIR}/${REF} \
--threads ${THREADS} \
--platform ${MODEL} \
--output_dir ${OUTPUT_DIR}

DeepSomatic Caller

INPUT_BAM_DIR="/path/to/bam"
INPUT_REF_DIR="/path/to/reference"
OUTPUT_DIR="/path/to/output"
BAM="alignment.bam"
REF="reference.fasta"
THREADS=64
MODEL="ONT_TUMOR_ONLY"
# for PacBio-HiFi reads: PACBIO_TUMOR_ONLY

sudo docker run \
-v ${INPUT_BAM_DIR}:${INPUT_BAM_DIR} \
-v ${INPUT_REF_DIR}:${INPUT_REF_DIR} \
-u $(id -u):$(id -g) \
google/deepsomatic:1.8.0 \
run_deepsomatic \
--model_type ${MODEL} \
--ref ${INPUT_REF_DIR}/${REF} \
--reads_tumor  ${INPUT_BAM_DIR}/${BAM} \
--output_vcf  ${OUTPUT_DIR}/output.vcf.gz \
--sample_name_tumor "tumor" \
--num_shards ${THREADS} \
--logging_dir ${OUTPUT_DIR}/logs \
--intermediate_results_dir ${OUTPUT_DIR}/intermediate_results_dir \
--use_default_pon_filtering=true

If you're using GPUs.

INPUT_BAM_DIR="/path/to/bam"
INPUT_REF_DIR="/path/to/reference"
OUTPUT_DIR="/path/to/output"
BAM="alignment.bam"
REF="reference.fasta"
THREADS=64
MODEL="ONT_TUMOR_ONLY"
# for PacBio-HiFi reads: PACBIO_TUMOR_ONLY

sudo docker run --gpus all \
-v ${INPUT_BAM_DIR}:${INPUT_BAM_DIR} \
-v ${INPUT_REF_DIR}:${INPUT_REF_DIR} \
-u $(id -u):$(id -g) \
google/deepsomatic:1.8.0-gpu \
run_deepsomatic \
--model_type ${MODEL} \
--ref ${INPUT_REF_DIR}/${REF} \
--reads_tumor  ${INPUT_BAM_DIR}/${BAM} \
--output_vcf  ${OUTPUT_DIR}/output.vcf.gz \
--sample_name_tumor "tumor" \
--num_shards ${THREADS} \
--logging_dir ${OUTPUT_DIR}/logs \
--intermediate_results_dir ${OUTPUT_DIR}/intermediate_results_dir \
--use_default_pon_filtering=true

Generate panels of normals (PoNs) file

source: ClairS-TO

PATH="PoN"
mkdir $PATH
wget -P $PATH http://www.bio8.cs.hku.hk/clairs-to/databases/gnomad.r2.1.af-ge-0.001.sites.vcf.gz
wget -P $PATH http://www.bio8.cs.hku.hk/clairs-to/databases/dbsnp.b138.non-somatic.sites.vcf.gz
wget -P $PATH http://www.bio8.cs.hku.hk/clairs-to/databases/1000g-pon.sites.vcf.gz
wget -P $PATH http://www.bio8.cs.hku.hk/clairs-to/databases/CoLoRSdb.GRCh38.v1.1.0.deepvariant.glnexus.af-ge-0.001.vcf.gz

# longphase-to phase \
# --pon-file PoN/1000g-pon.sites.vcf.gz,\
#            PoN/CoLoRSdb.GRCh38.v1.1.0.deepvariant.glnexus.af-ge-0.001.vcf.gz,\
# --strict-pon-file PoN/dbsnp.b138.non-somatic.sites.vcf.gz,\
#                   PoN/gnomad.r2.1.af-ge-0.001.sites.vcf.gz