Acceleration of short and long DNA read mapping without loss of accuracy using suffix array

Tárraga, Joaquín; Arnau, Vicente; Martínez, Héctor; Moreno, R. García; Cazorla, Diego; Salavert-Torres, José; Blanquer-Espert, I.; Dopazo, Joaquín; Medina, Ignacio

doi:10.1093/bioinformatics/btu553

Cited by 22 publications

(22 citation statements)

References 14 publications

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“…However, in order to take advantage of the parallel architectures available in current computers, it follows a very similar parallel pipeline to the one used by HPG-Aligner ( Martínez et al. , 2013 ; Tárraga et al. , 2014 ), but adapted to the specific features of methylation analysis.…”

Section: Methodsmentioning

confidence: 99%

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A parallel and sensitive software tool for methylation analysis on multicore platforms

et al. 2015

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Motivation: DNA methylation analysis suffers from very long processing time, as the advent of Next-Generation Sequencers has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. As it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed.Results: We present a new software tool, called HPG-Methyl, which efficiently maps bisulphite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows–Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith–Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPG-Methyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulphite reads.Availability and implementation: Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to anonymous@clariano.uv.es (password ‘anonymous’).Contact: juan.orduna@uv.es or jdopazo@cipf.es

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Section: Methodsmentioning

confidence: 99%

“…HPG-Methyl uses a parallel pipeline similar to HPG-Aligner ( Martínez et al. , 2013 ; Tárraga et al. , 2014 ).…”

Section: Introductionmentioning

confidence: 99%

A parallel and sensitive software tool for methylation analysis on multicore platforms

et al. 2015

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“…To find maximal exact matching seeds with hash table index, first find the start position of a substring of the read with a hash table and then enlarge it on both sides by a direct comparison between the read and the reference genome. A similar approach has been adopted by the HPG DNA read aligner [17].…”

Section: B Seed Computationmentioning

confidence: 99%

A comparison of seed-and-extend techniques in modern DNA read alignment algorithms

Ahmed

Bertels

Al-Ars

2016

2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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Abstract-DNA read alignment is a major step in genome analysis. However, as DNA reads continue to become longer, new approaches need to be developed to effectively use these longer reads in the alignment process. Modern aligners commonly use a two-step approach for read alignment: 1. seeding, 2. extension. In this paper, we have investigated various seeding and extension techniques used in modern DNA read alignment algorithms to find the best seeding and extension combinations. We developed an open source generic DNA read aligner that can be used to compare the alignment accuracy and total execution time of different combinations of seeding and extension algorithms. For extension, our results show that local alignment is the best extension approach, achieving up to 3.6x more accuracy than other extension techniques, for longer reads. For seeding, if BLAST-like seed extension is used, the best seeding approach is identifying all SMEMs in the DNA read (e.g., approach used by BWA-MEM). This combination is up to 6x more accurate than other seeding techniques, for longer reads. With local alignment, we observed that the seeding technique does not impact the alignment accuracy. Furthermore, we showed that an optimized implementation of local alignment using vector instructions, enabling 4.5x speedup, makes it the fastest of all extension techniques. Overall, we show that using local alignment with non-overlapping maximal exact matching seeds is the best seeding-extension combination due to its high accuracy and higher potential for optimization/acceleration for future DNA reads.

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“…For species without a good-quality reference genome, it is necessary to perform de novo transcriptome assembly to get a rough reference transcriptome first. Then the RNA-seq reads are aligned to the de novo transcriptome using an aligner for DNA alignment, such as Bowtie2 [94] and HPG aligner [95]. Abundance per transcript is estimated by using expectation-maximization (EM) algorithm-based methods, such as RSEM [96], eXpress [97] and Mix 2 [98].…”

Section: Different Library Construction Methods Can Bring Different Bmentioning

confidence: 99%

Swine blood transcriptomics: Application and advancement

Li¹

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Acceleration of short and long DNA read mapping without loss of accuracy using suffix array

Cited by 22 publications

References 14 publications

A parallel and sensitive software tool for methylation analysis on multicore platforms

A parallel and sensitive software tool for methylation analysis on multicore platforms

A comparison of seed-and-extend techniques in modern DNA read alignment algorithms

Swine blood transcriptomics: Application and advancement

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