cwSDTWnano

cwSDTWnano performs subsequence search and mapping directly on nanopore raw electrical current signals to enable accurate SNP detection and haplotype classification while avoiding information loss from base-calling.

Key Features:

• Algorithmic Innovation: Implements continuous wavelet Subsequence Dynamic Time Warping (cwSDTW) for efficient and accurate subsequence inquiry on raw nanopore signals.
• Signal-Based Processing: Processes electrical current signals directly from nanopore sequencing, bypassing base-calling to preserve signal-level information.
• Quality Analysis and Data Classification: Implements two novel criteria for signal quality analysis and data classification to improve performance under low sequencing coverage or low sequencing accuracy.
• Targeted Sequencing Applications: Applicable to targeted sequencing in human healthcare, including single nucleotide polymorphism (SNP) detection and haplotype classification within specific genomic regions.

Scientific Applications:

• Targeted sequencing in human healthcare: Enables direct signal-level mapping of genomic regions for targeted sequencing analyses.
• SNP Detection: Supports detection of single nucleotide polymorphisms (SNPs), including under low sequencing coverage conditions.
• Haplotype Classification: Facilitates haplotype classification under conditions of low sequencing accuracy by leveraging signal-level alignment.

Methodology:

Applies continuous wavelet Subsequence Dynamic Time Warping (cwSDTW), a subsequence dynamic time warping approach, to raw nanopore electrical current signals and incorporates two novel signal-quality and classification criteria.