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Reference flow: reducing reference bias using multiple population genomes

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 geneti...

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Detalles Bibliográficos
Autores principales: Chen, Nae-Chyun, Solomon, Brad, Mun, Taher, Iyer, Sheila, Langmead, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780692/
https://www.ncbi.nlm.nih.gov/pubmed/33397413
http://dx.doi.org/10.1186/s13059-020-02229-3
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-020-02229-3).