Introduction
Mako is a bioinformatics pipeline designed for the differential analysis of RNA modifications between two groups using Oxford Nanopore Technologies (ONT) direct RNA sequencing data (RNA002 or RNA004). It takes a samplesheet and POD5 files as input, performs basecalling and alignment, and then applies various statistical methods to identify differentially modified sites between experimental conditions.
If you already have pre-basecalled data or m6Anet results, you can skip the basecalling step and directly analyze the modification data as well.
The software is written in Nextflow and utilises Docker/Singularity containerisation for reproducibility and ease of installation.
See Getting Started for instructions on how to install and run the pipeline.
mako is in active development and not all features are supported. See Configuration for a list of what features are in-progress.
Steps of the pipeline
- Sample and read QC
- Site-level aggregation, filtering, and selection
- Choice of differential analysis methods:
- Either binomial or beta-binomial, depending on the dispersion (default)
- Binomial
- Beta-binomial
- Homoscedastic normal
- Heteroscedastic normal
- Visualization of results via makoview