Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory

By Mark J. P. Chaisson, Glenn Tesler. BMC Bioinformatics, 2012

1,122 citations recorded by the source corpus.

Recent methods have been developed to perform high-throughput sequencing of DNA by Single Molecule Sequencing (SMS). While Next-Generation sequencing methods may produce reads up to several hundred bases long, SMS sequencing produces reads up to tens of kilobases long. Existing alignment methods are either too inefficient for high-throughput datasets, or not sensitive enough to align SMS reads, which have a higher error rate than Next-Generation sequencing. We describe the method BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands of bases long, with divergence between the read and genome dominated by insertion and deletion error. The method is benchmarked using both simulated reads and reads from a bacterial sequencing project. We also present a combinatorial model of sequencing error that motivates why our approach is effective. The results indicate that it is possible to map SMS reads with high accuracy and speed. Furthermore, the inferences made on the mapability of SMS reads using our combinatorial model of sequencing error are in agreement with the mapping accuracy demonstrated on simulated reads.

Subfields: Ecology, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/61d5bfc2207410659e47dcf29a61331be7fd8397

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Citations in the corpus

SVIM: structural variant identification using mapped long reads (2018, background): “reads can be mapped with greater accuracy which enables the sequencing of repetitive and low-complexity regions (Chaisson and Tesler, 2012; Loomis et al., 2013).”
One chromosome, one contig: complete microbial genomes from long-read sequencing and assembly. (2015, methodology): “As SMRT sequencing improved to longer and more accurate sequences, this became a highly effective strategy for assembly [18 ,57].”
TGS-GapCloser: A fast and accurate gap closer for large genomes with low coverage of error-prone long reads (2020, neutral): “GMcloser and FGAP (based on BLAST [26]) and PBJelly (based on BLASR [45]) were the most time-consuming.”
Piercing the dark matter: bioinformatics of long-range sequencing and mapping (2018, methodology): “…technology-specific algorithms have been introduced to address the specific error models and characteristics of the data, including BLASR (PacBio) 75 , BWA-MEM (PacBio and Oxford Nanopore) 76 , Minimap2 (PacBio and Oxford Nanopore) 77 , NGMLR (PacBio and Oxford Nanopore) 73 or Lariat (10X…”
Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage (2015, positive): “We used DBG2OLC to align our PacBio reads to the De Bruijn graph assembly to produce a ‘backbone’, then, according to the DBG2OLC standard pipeline, used the backbone to generate the consensus using the programs BLASR (29) and PBDagCon (https://github.”
Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing (2019, methodology): “PacBio long reads were aligned with blasr [83] for PBHoney and using NGM-LR [55] for PBHoney-NGM, Sniffles, and pbsv.”
PacBio Sequencing and Its Applications (2015, background): “Compared to BLASR, another aligner that is capable of overlapping PacBio reads [37], MHAP efﬁciently constructed comparable or improved de novo assemblies of the human genome and the genomes of four model organisms ( Escherichia coli , Saccharomyces cerevisiae , Arabidopsis thaliana , and…”
Fast and accurate de novo genome assembly from long uncorrected reads (2016, neutral): “We evaluated Sparc in a similar manner to Racon, with the only difference being in the mapping step (step 3 in the miniasm+Racon pipline) where Sparc uses BLASR (Chaisson and Tesler 2012).”
Oxford Nanopore MinION Sequencing and Genome Assembly (2016, methodology): “…when raw sequencing data are converted into FASTQ/FASTA ﬁles, alignment tools such as the basic local alignment with successive reﬁnement (BLASR) [42], DALIGNER (https://github.com/thegenemyers/ DALIGNER) or Celera Assembler could be used to compute multiple alignments for base error correction…”
Accurate detection of complex structural variations using single molecule sequencing (2017, neutral): “A few aligners are available, including LAST 24 , BlasR 25 , BWA-MEM 26 , GraphMap 27 , MECAT 28 and minimap2 29 .”