Evaluation and assessment of read-mapping by multiple next-generation sequencing aligners based on genome-wide characteristics
Artikel i vetenskaplig tidskrift, 2017

Massive data produced due to the advent of next-generation sequencing (NGS) technology is widely used for biological researches and medical diagnosis. The crucial step in NGS analysis is read alignment or mapping which is computationally intensive and complex. The mapping bias tends to affect the downstream analysis, including detection of polymorphisms. In order to provide guidelines to the biologist for suitable selection of aligners; we have evaluated and benchmarked 5 different aligners (BWA, Bowtie2, NovoAlign, Smalt and Stampy) and their mapping bias based on characteristics of 5 microbial genomes. Two million simulated read pairs of various sizes (36 bp, 50 bp, 72 bp, 100 bp, 125 bp, 150 bp, 200 bp, 250 bp and 300 bp) were aligned. Specific alignment features such as sensitivity of mapping, percentage of properly paired reads, alignment time and effect of tandem repeats on incorrectly mapped reads were evaluated. BWA showed faster alignment followed by Bowtie2 and Smalt. NovoAlign and Stampy were comparatively slower. Most of the aligners showed high sensitivity towards long reads (> 100 bp) mapping. On the other hand NovoAlign showed higher sensitivity towards both short reads (36 bp, 50 bp, 72 bp) and long reads (> 100 bp) mappings; It also showed higher sensitivity towards mapping a complex genome like Plasmodium falciparum. The percentage of properly paired reads aligned by NovoAlign, BWA and Stampy were markedly higher. None of the aligners outperforms the others in the benchmark, however the aligners perform differently with genome characteristics. We expect that the results from this study will be useful for the end user to choose aligner, thus enhance the accuracy of read mapping. (C) 2017 Elsevier Inc. All rights reserved.

Alignments

Aligners

Genome

Mapping

Algorithm

NGS

Next-generation sequencing

Reads

Författare

Subazini Thankaswamy

Chalmers, Biologi och bioteknik

Partho Sen

Chalmers, Biologi och bioteknik, Systembiologi

Intawat Nookaew

Chalmers, Biologi och bioteknik, Systembiologi

Genomics

0888-7543 (ISSN) 1089-8646 (eISSN)

Vol. 109 186-191

Ämneskategorier

Genetik

DOI

10.1016/j.ygeno.2017.03.001