ArticlePloS one2014
MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 160 papers.
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Who cites it
160 citing papers in PubMed.
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- DNA and Histone Modifications Identify a Putative Controlling Element (CE) on the X Chromosome ofCells · 2025Article
- Genomic prediction and association analyses for breeding parthenocarpic blueberries.Horticulture research · 2025Article
- Genetic control of prickles in tetraploid blackberry.G3 (Bethesda, Md.) · 2025Article
- HPV-KITE: sequence analysis software for rapid HPV genotype detection.Briefings in bioinformatics · 2025Article
- Genetic control of sweetness and acidity in blackberry.Frontiers in plant science · 2025Article
- Inference of the genetic basis of fruit texture in highbush blueberries using genome-wide association analyses.Horticulture research · 2024Article
- Identification of osteoporosis genes using family studies.Frontiers in endocrinology · 2024Review
- Whole genome sequencing of increased number of azithromycin-resistant Shigella flexneri 1b isolates in Ontario.Scientific reports · 2023Article
- Tropical forest loss and geographic location drive the functional genomic diversity of an endangered palm tree.Evolutionary applications · 2023Article
- Adaptive responses of yeast strains tolerant to acidic pH, acetate, and supraoptimal temperature.Applied microbiology and biotechnology · 2023Article
- Article
100 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.