NanoSNP: a progressive and haplotype-aware SNP caller on low-coverage nanopore sequencing data.

ABSTRACT:

Motivation

Oxford Nanopore sequencing has great potential and advantages in population-scale studies. Due to the cost of sequencing, the depth of whole-genome sequencing for per individual sample must be small. However, the existing single nucleotide polymorphism (SNP) callers are aimed at high-coverage Nanopore sequencing reads. Detecting the SNP variants on low-coverage Nanopore sequencing data is still a challenging problem.

Results

We developed a novel deep learning-based SNP calling method, NanoSNP, to identify the SNP sites (excluding short indels) based on low-coverage Nanopore sequencing reads. In this method, we design a multi-step, multi-scale and haplotype-aware SNP detection pipeline. First, the pileup model in NanoSNP utilizes the naive pileup feature to predict

SUBMITTER: Huang N 

PROVIDER: S-EPMC9822538 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature