signalAlign
SignalAlign maps cytosine and adenosine DNA methylation by analyzing ionic current signals produced by Oxford Nanopore Technologies MinION nanopore sequencing to localize methylation sites across genomes.
Key Features:
- Methylation detection: Identifies DNA chemical modifications focusing on cytosine and adenosine methylation from nanopore signal data.
- Nanopore sequencing integration: Operates on ionic current signals generated by Oxford Nanopore Technologies MinION sequencers.
- Variant mapping: Maps three cytosine variants and two adenine variants to provide variant-specific methylation calls.
- Signal-level analysis: Interprets raw ionic current traces to associate signal deviations with nucleotide modifications.
- Quantitative sensitivity: Detects variations in methylation levels enabling comparative analysis across conditions such as growth phases.
Scientific Applications:
- Genomic function regulation: Maps methylation patterns to study how DNA chemical modifications regulate genomic functions.
- Microbial studies: Applied to Escherichia coli to detect changes in methylation levels across different growth phases, supporting microbial genomics and epigenetics research.
Methodology:
Interprets ionic current signals produced by the MinION sequencer to map methylation sites and distinguish three cytosine variants and two adenine variants, detecting variation in methylation levels.
Topics
Details
- License:
- MIT
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- Python
- Added:
- 6/11/2018
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Mapping
Publications
Rand AC, Jain M, Eizenga JM, Musselman-Brown A, Olsen HE, Akeson M, Paten B. Mapping DNA methylation with high-throughput nanopore sequencing. Nature Methods. 2017;14(4):411-413. doi:10.1038/nmeth.4189. PMID:28218897. PMCID:PMC5704956.
Documentation
Downloads
- Source codehttps://github.com/ArtRand/signalAlign