Seed design framework for mapping SOLiD reads

TL;DR

This paper introduces a novel seed design framework for mapping SOLiD color-space reads to reference genomes, improving accuracy by modeling read matches and distinguishing SNPs from errors.

Contribution

It presents a flexible, probabilistic seed design algorithm tailored for SOLiD read mapping, incorporating a new seeding principle and handling both lossy and lossless frameworks.

Findings

Demonstrates efficiency of proposed seed designs

Handles SNPs and reading errors effectively

Provides a rigorous probabilistic modeling approach

Abstract

The advent of high-throughput sequencing technologies constituted a major advance in genomic studies, offering new prospects in a wide range of applications. We propose a rigorous and flexible algorithmic solution to mapping SOLiD color-space reads to a reference genome. The solution relies on an advanced method of seed design that uses a faithful probabilistic model of read matches and, on the other hand, a novel seeding principle especially adapted to read mapping. Our method can handle both lossy and lossless frameworks and is able to distinguish, at the level of seed design, between SNPs and reading errors. We illustrate our approach by several seed designs and demonstrate their efficiency.