Fast numerical optimization for genome sequencing data in population biobanks

Abstract Motivation Large-scale and high-dimensional genome sequencing data poses computational challenges. General-purpose optimization tools are usually not optimal in terms of computational and memory performance for genetic data. Results We develop two efficient solvers for optimization problems...

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Bibliographic Details
Published in:	Bioinformatics (Oxford, England) Vol. 37; no. 22; pp. 4148 - 4155
Main Authors:	Li, Ruilin, Chang, Christopher, Tanigawa, Yosuke, Narasimhan, Balasubramanian, Hastie, Trevor, Tibshirani, Robert, Rivas, Manuel A
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 18.11.2021 Oxford Publishing Limited (England)
Subjects:	Algorithms Biological Specimen Banks Chromosome Mapping Cognitive ability Computer applications Floating point arithmetic Gene sequencing Genetic diversity Genetic variance Genome Genomes Humans Least-Squares Analysis Optimization Original Papers Representations Software Solvers Sparse matrices Sparsity Whole genome sequencing
ISSN:	1367-4803, 1367-4811, 1367-4811
Online Access:	Get full text
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