Recent advances in sequence assembly: principles and applications

Abstract

The application of advanced sequencing technologies and the rapid growth of various sequence data have led to increasing interest in DNA sequence assembly. However, repeats and polymorphism occur frequently in genomes, and each of these has different impacts on assembly. Further, many new applications for sequencing, such as metagenomics regarding multiple species, have emerged in recent years. These not only give rise to higher complexity but also prevent short-read assembly in an efficient way. This article reviews the theoretical foundations that underlie current mapping-based assembly and de novo-based assembly, and highlights the key issues and feasible solutions that need to be considered. It focuses on how individual processes, such as optimal k-mer determination and error correction in assembly, rely on intelligent strategies or high-performance computation. We also survey primary algorithms/software and offer a discussion on the emerging challenges in assembly.

A Framework Approach for Quality Feature Analysis of Genome Assemblies

“…Figure from (Commins et al 2009) Figure 1.2 Biases from repeat regions. Figure taken from (Chen et al 2017). (A) The sequencing machine detects six reads, namely, n1, n2, n3, n4, n5 and n6 derived from the DNA sequence 'TACCCGTCCCAACCCTT'.…”

“…Finding this path is computationally difficult, an NP-hard problem, known as the Hamiltonian Path. The overlap strategy has time complexity O(n ) (Chen et al 2017).…”

“…There are several efficient algorithms for finding the Eulerian path, perhaps it can generate an exponential number of Eulerian paths (Pop 2009). In addition, finding a Hamiltonian path may be reduced to finding a Eulerian path in a (k-1)-mer DBG (Chen et al 2017).…”

“…But also, it can generate too many nodes, unfailing genome assembly. K-mers shorter than some repeat regions (we discuss repeats in the next section) can cause graph disorder and break up the contigs (Chen et al 2017). Thereby, a longer k might be desired but limited by read length -"if the overlapping region of two reads is less than k characters, they do not have any common vertex in the graph" (Chen et al 2017).…”

“…Basically, it is difficult for an assembler to differentiate a sequencing error from a polymorphism between almost identical repeat copies, and to detect the correct positions of identical repeats (Phillippy et al 2008 (Chen et al 2017). (A) The sequencing machine detects six reads, namely, n1, n2, n3, n4, n5 and n6 derived from the DNA sequence 'TACCCGTCCCAACCCTT'.…”