| Literature DB >> 33397413 |
Nae-Chyun Chen1, Brad Solomon1, Taher Mun1, Sheila Iyer1, Ben Langmead2.
Abstract
Most sequencing data analyses start by aligning sequencing reads to a linear reference genome, but failure to account for genetic variation leads to reference bias and confounding of results downstream. Other approaches replace the linear reference with structures like graphs that can include genetic variation, incurring major computational overhead. We propose the reference flow alignment method that uses multiple population reference genomes to improve alignment accuracy and reduce reference bias. Compared to the graph aligner vg, reference flow achieves a similar level of accuracy and bias avoidance but with 14% of the memory footprint and 5.5 times the speed.Entities:
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Year: 2021 PMID: 33397413 PMCID: PMC7780692 DOI: 10.1186/s13059-020-02229-3
Source DB: PubMed Journal: Genome Biol ISSN: 1474-7596 Impact factor: 13.583