RICO

RICO (Ribosomal DNA Copy number) is a long-read sequencing–based pipeline for estimating ribosomal DNA (rDNA) copy number (CN) using coverage normalization against single-copy genes (SCGs), with DNA methylation analysis.

The pipeline is designed for Oxford Nanopore Technologies (ONT) whole-genome sequencing data and supports both rDNA CN estimation and CpG methylation profiling.

Table of contents

• Overview
• Installation
• How to Use

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Overview

RICO performs the following major steps:

1. Alignment of unaligned ONT BAMs to a custom reference genome containing rDNA repeats
2. Coverage quantification over rDNA loci and curated SCG panel
3. Estimation of rDNA CN by normalizing rDNA coverage against SCG coverage
4. Extraction of CpG methylation calls within rDNA regions

The workflow is implemented in Nextflow (DSL2) and is optimised for HPC environments.

Execution environment

RICO is implemented in Nextflow (DSL2). It is developed and tested on a PBSPro-based HPC system (NCI Australia).

UPDATE (April 2026):

• RICO now supports execution using Singularity containers
• This means all required software dependencies are provided

The pipeline currently assumes:

• A PBSPro scheduler (executor = 'pbspro')
• HPC-style job submission
• Singularity available on the system (module load singularity on Gadi)

Other PBSPro-based HPC systems may work with minimal configuration changes. Support for Slurm or other schedulers has not yet been tested.

Tools used in the pipeline

RICO was developed and tested with the following versions (bundled in the container image):

• Nextflow (25.04.6)
• Minimap2 (2.30)
• Samtools (1.23)
• Bedtools (2.31.1)
• Modkit (0.6.1)

When using the Singularity container, manual installation of these tools is no longer required.

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Installation

1. Clone the repository on Gadi:

git clone https://github.com/comprna/RICO.git
cd RICO

2. Load Nextflow and singularity on Gadi

module load nextflow/25.04.6
module load singularity
nextflow -version #check

3. Pull the Singularity container

mkdir -p /path/to/containers
singularity pull /path/to/containers/rico_2026.03.sif docker://zakayuen/rico:2026.03

Replace /path/to/containers with your preferred location (e.g. /g/data/.../containers)

4. Download reference files

Human and mouse reference genomes and annotation files are available on Zenodo:

DOI: https://doi.org/10.5281/zenodo.18500657

Download the archive and extract:

tar -xzf RICO_ref_v1.tar.gz

Place the extracted ref/ directory inside the cloned RICO repository

RICO currently supports

• Human (GRCh38 + rDNAx5)
• Mouse (GRCm39 + rDNAx5)

5. Configure NCI project, storage, and mirror path

Edit nextflow.config and update the following fields:

params {
  project   = 'jd21'
  storage   = 'gdata/jd21+scratch/jd21+gdata/xc17+gdata/qq78'
  container = '/g/data/xc17/zaka/containers/rico_2026.03.sif'
...

• project: your NCI project code
• storage: file systems used by the pipeline (where input data and results are stored)
• container: /path/to/containers/rico_2026.03.sif

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How to use

Input - unaligned BAM

Path to your input BAM needs to be provided in samples.tsv:

file_path
/path/to/your.bam 

Minimum command (default: human, SCG-2)

From the RICO directory:

nextflow run rico.nf \
 --samplesheet samples.tsv

The results are written to the results folder by default.

But you can specify the results directory using --out_dir:

nextflow run rico.nf \
 --samplesheet samples.tsv \
 --out_dir /path/to/output

Other SCGs for human samples

For human samples, three curated SCG panels are provided: SCG-1, SCG-2 (default), SCG-3 Specify using --scg, for example:

nextflow run rico.nf \
 --samplesheet samples.tsv \
 --scg 3

If not specified, SCG-2 is used.

Mouse samples

nextflow run rico.nf \
 --samplesheet samples.tsv \
 --species mouse

For mouse samples, it uses a single curated SCG panel only. The --scg parameter is ignored when --species mouse is selected.

Outputs

For each input BAM, RICO produces:

1. Alignment outputs

• <sample>_<reference>.bam
• <sample>_<reference>.bam.bai

2. Copy number estimation

• Coverage outputs for rDNA and SCGs
• rDNA CN estimates

3. Methylation outputs

• BedMethyl file
• Per-read base modification output table for rDNA

Citation

Yuen, Leeder, Hannan, Eyras & Hein. Accurate estimation of ribosomal DNA copy number using nanopore long-read sequencing. (Manuscript in preparation)