MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

Lee, Wan Ping; Strömberg, Michael; Ward, Alistair; Stewart, Chip; Garrison, Erik; Marth, Gábor

doi:10.1371/journal.pone.0090581

Cited by 243 publications

(192 citation statements)

References 67 publications

(92 reference statements)

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“…The captured DNA was sequenced with the Illumina HiSeq 2000 Sequencing System (Illumina, San Diego, CA, USA). Sequencing reads were split by barcode, filtered, and trimmed by quality and aligned to a hybrid P. trichocarpa / P. deltoides reference genome using MOSAIK 2.2 (Lee et al., 2014). …”

Section: Methodsmentioning

confidence: 99%

Population genomics of the eastern cottonwood (Populus deltoides)

Fahrenkrog

Neves

Resende

et al. 2017

Ecology and Evolution

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Despite its economic importance as a bioenergy crop and key role in riparian ecosystems, little is known about genetic diversity and adaptation of the eastern cottonwood (Populus deltoides). Here, we report the first population genomics study for this species, conducted on a sample of 425 unrelated individuals collected in 13 states of the southeastern United States. The trees were genotyped by targeted resequencing of 18,153 genes and 23,835 intergenic regions, followed by the identification of single nucleotide polymorphisms (SNPs). This natural P. deltoides population showed low levels of subpopulation differentiation (F ST = 0.022–0.106), high genetic diversity (θW = 0.00100, π = 0.00170), a large effective population size (N e ≈ 32,900), and low to moderate levels of linkage disequilibrium. Additionally, genomewide scans for selection (Tajima's D), subpopulation differentiation (XTX), and environmental association analyses with eleven climate variables carried out with two different methods (LFMM and BAYENV2) identified genes putatively involved in local adaptation. Interestingly, many of these genes were also identified as adaptation candidates in another poplar species, Populus trichocarpa, indicating possible convergent evolution. This study constitutes the first assessment of genetic diversity and local adaptation in P. deltoides throughout the southern part of its range, information we expect to be of use to guide management and breeding strategies for this species in future, especially in the face of climate change.

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Section: Methodsmentioning

confidence: 99%

Population genomics of the eastern cottonwood (Populus deltoides)

Fahrenkrog

Neves

Resende

et al. 2017

Ecology and Evolution

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“…Some tools, like MOSAIK, use k-mer-based indexing, in which short k-mer sequences from the reference are related to their locations using a hash table or other traditional keyvalue data structure (Lee et al 2014). Other tools, such as BWA-MEM, use Burrows-Wheeler Transform-based approaches, in which the reference is stored in a succinct self-indexed data structure optimized for substring search (Li 2013).…”

Section: Read Mapping In Genome Graphsmentioning

confidence: 99%

Genome graphs and the evolution of genome inference

et al. 2017

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The human reference genome is part of the foundation of modern human biology and a monumental scientific achievement. However, because it excludes a great deal of common human variation, it introduces a pervasive reference bias into the field of human genomics. To reduce this bias, it makes sense to draw on representative collections of human genomes, brought together into reference cohorts. There are a number of techniques to represent and organize data gleaned from these cohorts, many using ideas implicitly or explicitly borrowed from graph-based models. Here, we survey various projects underway to build and apply these graph-based structures—which we collectively refer to as genome graphs—and discuss the improvements in read mapping, variant calling, and haplotype determination that genome graphs are expected to produce.

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“…Basically Needleman Wunsch and Smith waterman algorithm [8] come under this approach. These are much more complex than the exact pattern matching.…”

Section: ) Dynamic Programming Algorithmsmentioning

confidence: 99%

“…smaller problems are solved in succession to solve the main problem. A)Smith-Waterman (local alignment) [8] • Accuracy: good with gapped pairs…”

Section: ) Dynamic Programming Algorithmsmentioning

confidence: 99%

Parallel Processing Approach for Pattern Matching using MPI

Rashmi¹,

Kumar²

2018

IJCA

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Bioinformatics is one of the field where high performance computation widely used. Pattern matching is essential task in Bio-informatics. A powerful technique for searching sequence patterns in the biological sequence databases is the pattern recognition. Significant increase in the number of protein sequences and DNA expanded the need for the enhancement of performance of pattern matching. Hence fast and high performance algorithms are highly demanded in many applications of computational molecular biology and bioinformatics. In this paper we present a parallel processing approach for pattern matching algorithm using distributed parallel programming paradigm Message Passing Interface (MPI). The focus of the research is the implementation of basic algorithm naïve for pattern matching by utilizing compute nodes of high performance computing server optimally. The parallel algorithm finds correct matches and experimental results show very high performance gain over sequential approach.

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MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

Cited by 243 publications

References 67 publications

Population genomics of the eastern cottonwood (Populus deltoides)

Population genomics of the eastern cottonwood (Populus deltoides)

Genome graphs and the evolution of genome inference

Parallel Processing Approach for Pattern Matching using MPI

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