rHAT: fast alignment of noisy long reads with regional hashing

MOTIVATION Single Molecule Real-Time (SMRT) sequencing has been widely applied in cutting-edge genomic studies. However, it is still an expensive task to align the noisy long SMRT reads to reference genome by state-of-the-art aligners, which is becoming a bottleneck in applications with SMRT sequencing. Novel approach is on demand for improving the efficiency and effectiveness of SMRT read alignment. RESULTS We propose Regional Hashing-based Alignment Tool (rHAT), a seed-and-extension-based read alignment approach specifically designed for noisy long reads. rHAT indexes reference genome by regional hash table (RHT), a hash table-based index which describes the short tokens within local windows of reference genome. In the seeding phase, rHAT utilizes RHT for efficiently calculating the occurrences of short token matches between partial read and local genomic windows to find highly possible candidate sites. In the extension phase, a sparse dynamic programming-based heuristic approach is used for reducing the cost of aligning read to the candidate sites. By benchmarking on the real and simulated datasets from various prokaryote and eukaryote genomes, we demonstrated that rHAT can effectively align SMRT reads with outstanding throughput. AVAILABILITY AND IMPLEMENTATION rHAT is implemented in C++; the source code is available at https://github.com/HIT-Bioinformatics/rHAT CONTACT: ydwang@hit.edu.cn SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

[1]  Heng Li.  Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM , 2013, 1303.3997.

[2]  Aaron A. Klammer,et al.  Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data , 2013, Nature Methods.

[3]  Nuno A. Fonseca,et al.  Tools for mapping high-throughput sequencing data , 2012, Bioinform..

[4]  Knut Reinert,et al.  RazerS 3: Faster, fully sensitive read mapping , 2012, Bioinform..

[5]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[6]  Lucian Ilie,et al.  SHRiMP2: Sensitive yet Practical Short Read Mapping , 2011, Bioinform..

[7]  Timothy P. L. Smith,et al.  Reducing assembly complexity of microbial genomes with single-molecule sequencing , 2013, Genome Biology.

[8]  Steven L Salzberg,et al.  Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.

[9]  W. J. Kent,et al.  BLAT--the BLAST-like alignment tool. , 2002, Genome research.

[10]  Giovanni Manzini,et al.  Opportunistic data structures with applications , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[11]  Cole Trapnell,et al.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome , 2009, Genome Biology.

[12]  Mark J. P. Chaisson,et al.  Resolving the complexity of the human genome using single-molecule sequencing , 2014, Nature.

[13]  Mauricio O. Carneiro,et al.  The advantages of SMRT sequencing , 2013, Genome Biology.

[14]  M. Schatz,et al.  Hybrid error correction and de novo assembly of single-molecule sequencing reads , 2012, Nature Biotechnology.

[15]  Glenn Tesler,et al.  Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory , 2012, BMC Bioinformatics.

[16]  Eugene W. Myers,et al.  Efficient q-Gram Filters for Finding All epsilon-Matches over a Given Length , 2006, J. Comput. Biol..

[17]  Adam C. English,et al.  PBHoney: identifying genomic variants via long-read discordance and interrupted mapping , 2014, BMC Bioinformatics.

[18]  Mark J. P. Chaisson,et al.  Reconstructing complex regions of genomes using long-read sequencing technology , 2014, Genome research.

[19]  S. Salzberg,et al.  Repetitive DNA and next-generation sequencing: computational challenges and solutions , 2011, Nature Reviews Genetics.

[20]  S. Turner,et al.  Real-Time DNA Sequencing from Single Polymerase Molecules , 2009, Science.

[21]  Mauricio O. Carneiro,et al.  Pacific biosciences sequencing technology for genotyping and variation discovery in human data , 2012, BMC Genomics.

[22]  Vladimir Yanovsky,et al.  Various Algorithms for High Throughput Sequencing , 2014 .

[23]  Nagesh V. Honnalli,et al.  Hobbes: optimized gram-based methods for efficient read alignment , 2011, Nucleic acids research.

[24]  M. Frith,et al.  Adaptive seeds tame genomic sequence comparison. , 2011, Genome research.

[25]  David Eppstein,et al.  Sparse dynamic programming I: linear cost functions , 1992, JACM.

[26]  Kiyoshi Asai,et al.  PBSIM: PacBio reads simulator - toward accurate genome assembly , 2013, Bioinform..