Smalt

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 (36bp, 50bp, 72bp, 100bp, 125bp,
150bp, 200bp, 250bp and 300bp) 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 (>100bp) mapping. On the other hand NovoAlign showed higher sensitivity
towards both short reads (36bp, 50bp, 72bp) and long reads (>100bp) 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.

Evaluation and assessment of read-mapping by multiple next-generation sequencing aligners based on genome-wide characteristics.

Smalt is a tool to align DNA sequencing reads to a reference genome using Next-generation sequencing data. However, it does not support SOLID sequencing data.

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