Summary Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when processing raw Nanopore data before alignment. Guppy is deprecated; use Dorado for all new analyses.
Version Compatibility
Reference examples tested with: samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
CLI: <tool> --version then <tool> --help to confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.
Nanopore Basecalling
"Basecall my Nanopore data" → Convert raw electrical signal (FAST5/POD5) into nucleotide sequences with quality scores, optionally detecting modified bases.
CLI: dorado basecaller sup pod5/ > calls.bam (recommended), dorado basecaller sup,5mCG_5hmCG pod5/ (with modifications)
Convert raw electrical signal from Nanopore sequencing into nucleotide sequences.
Dorado (Recommended)
Dorado is ONT's current production basecaller, replacing Guppy. It offers better accuracy and speed.
Basic Basecalling
dorado basecaller sup pod5_dir/ > calls.bam
Choose Model
dorado basecaller fast pod5_dir/ > calls.bam
dorado basecaller hac pod5_dir/ > calls.bam
dorado basecaller sup pod5_dir/ > calls.bam
Model Speed vs Accuracy
Model Speed Accuracy Use Case fast Fastest Lower Quick preview hac Medium High General use sup Slowest
Specific Model Version
List Available Models
Output FASTQ Instead of BAM dorado basecaller sup pod5_dir/ --emit-fastq > calls.fastq
Modified Base Detection dorado basecaller sup,5mCG_5hmCG pod5_dir/ > calls_mods.bam
dorado basecaller sup,5mCG pod5_dir/ > calls_5mc.bam
dorado basecaller sup,6mA pod5_dir/ > calls_6ma.bam
GPU Selection dorado basecaller sup pod5_dir/ --device cuda:0 > calls.bam
dorado basecaller sup pod5_dir/ --device cuda:0,1 > calls.bam
dorado basecaller sup pod5_dir/ --device cpu > calls.bam
Batch Size for Memory dorado basecaller sup pod5_dir/ --batchsize 64 > calls.bam
Duplex Calling dorado duplex sup pod5_dir/ > duplex.bam
Demultiplexing During Basecalling dorado basecaller sup pod5_dir/ --kit-name SQK-NBD114-24 > calls.bam
dorado demux calls.bam --output-dir demuxed/ --kit-name SQK-NBD114-24
Trim Adapters dorado basecaller sup pod5_dir/ --trim adapters > calls.bam
dorado basecaller sup pod5_dir/ --no-trim > calls_untrimmed.bam
Resume Interrupted Run dorado basecaller sup pod5_dir/ --resume-from calls.bam > calls_complete.bam
Guppy (Deprecated - Legacy Only) Guppy is deprecated and no longer receiving updates. Use Dorado for all new analyses. Guppy examples below are only for maintaining legacy pipelines.
Basic Basecalling guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_sup.cfg \
--device cuda:0
CPU Mode guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_fast.cfg \
--num_callers 8 \
--cpu_threads_per_caller 4
High Accuracy Model guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_hac.cfg \
--device cuda:0
Super Accuracy Model guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_sup.cfg \
--device cuda:0
List Available Configs guppy_basecaller --print_workflows
ls /opt/ont/guppy/data/*.cfg
Modified Base Calling guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_modbases_5mc_cg_sup.cfg \
--device cuda:0
Barcoding During Basecalling guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_sup.cfg \
--device cuda:0 \
--barcode_kits SQK-NBD114-24
Output BAM guppy_basecaller \
-i fast5_dir/ \
-s output_dir/ \
-c dna_r10.4.1_e8.2_400bps_sup.cfg \
--device cuda:0 \
--bam_out \
--index
POD5 File Handling POD5 is the new format replacing FAST5.
Convert FAST5 to POD5 pod5 convert fast5 fast5_dir/*.fast5 --output pod5_dir/
Merge POD5 Files pod5 merge pod5_dir/*.pod5 --output merged.pod5
Inspect POD5 pod5 inspect reads input.pod5
pod5 inspect summary input.pod5
Subset POD5 pod5 subset input.pod5 --output subset.pod5 --read-id-file read_ids.txt
Quality Filtering
Filter with Chopper (After Basecalling) gunzip -c calls.fastq.gz | chopper -q 10 -l 500 | gzip > filtered.fastq.gz
Filter by Quality Score gunzip -c calls.fastq.gz | \
awk 'BEGIN{OFS="\n"} {h=$0; getline seq; getline plus; getline qual;
split(h, a, " "); split(a[4], q, "=");
if(q[2] >= 10) print h, seq, plus, qual}' | \
gzip > q10_filtered.fastq.gz
NanoFilt (Alternative) gunzip -c calls.fastq.gz | NanoFilt -q 10 -l 500 | gzip > filtered.fastq.gz
Basecalling QC
NanoPlot NanoPlot --fastq calls.fastq.gz -o qc_report/ --plots hex dot
NanoPlot --bam calls.bam -o qc_report/
pycoQC (From Sequencing Summary) pycoQC -f sequencing_summary.txt -o pycoqc_report.html
Basic Stats seqkit stats calls.fastq.gz
awk 'NR%4==2 {sum+=length($0); count++} END {print "Reads:", count, "Mean length:", sum/count}' calls.fastq
Model Selection Guide
R10.4.1 Chemistry (Current) Model Use dna_r10.4.1_e8.2_400bps_fast Quick analysis dna_r10.4.1_e8.2_400bps_hac Routine work dna_r10.4.1_e8.2_400bps_sup High accuracy
R9.4.1 Chemistry (Legacy) Model Use dna_r9.4.1_450bps_fast Quick analysis dna_r9.4.1_450bps_hac Routine work dna_r9.4.1_450bps_sup High accuracy
Complete Pipeline Goal: Run the full Nanopore basecalling pipeline from raw signal data through quality-filtered reads with a QC report.
Approach: Convert FAST5 to POD5 if needed, basecall with Dorado, convert to FASTQ, filter with chopper, and generate NanoPlot QC.
#!/bin/bash
INPUT=$1
OUTPUT=$2
MODEL=${3:-sup}
mkdir -p $OUTPUT
if [ -d "$INPUT/fast5" ]; then
echo "Converting FAST5 to POD5..."
pod5 convert fast5 $INPUT/fast5/*.fast5 --output $OUTPUT/pod5/
INPUT_DIR="$OUTPUT/pod5"
else
INPUT_DIR="$INPUT"
fi
echo "Basecalling with $MODEL model..."
dorado basecaller $MODEL $INPUT_DIR > $OUTPUT/calls.bam
echo "Converting to FASTQ..."
samtools fastq $OUTPUT/calls.bam | gzip > $OUTPUT/calls.fastq.gz
echo "Filtering..."
gunzip -c $OUTPUT/calls.fastq.gz | chopper -q 10 -l 500 | gzip > $OUTPUT/filtered.fastq.gz
echo "QC report..."
NanoPlot --fastq $OUTPUT/filtered.fastq.gz -o $OUTPUT/qc/
echo "Done!"
GPU Requirements Model VRAM Required Speed (R10.4.1) fast 4 GB ~450 bases/s hac 8 GB ~200 bases/s sup 12 GB ~50 bases/s
Troubleshooting
Out of Memory dorado basecaller sup pod5_dir/ --batchsize 32 > calls.bam
Slow CPU Basecalling dorado basecaller fast pod5_dir/ --device cpu > calls.bam
Check GPU Usage nvidia-smi -l 1
watch -n 1 nvidia-smi
Related Skills
long-read-alignment - Align basecalled reads
long-read-qc - QC after basecalling
medaka-polishing - Polish using basecalled reads
structural-variants - SV detection from long reads
