Sequencing era methods for identifying signatures of selection in the genome
| Autor: | Clare Horscroft, Andrew Collins, Reuben J. Pengelly, Sarah Ennis, Timothy J. Sluckin |
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| Rok vydání: | 2018 |
| Předmět: |
Computer science
0206 medical engineering 02 engineering and technology Computational biology Variation (game tree) Genome Linkage Disequilibrium DNA sequencing Machine Learning 03 medical and health sciences Animals Humans Selection Genetic Molecular Biology Selection (genetic algorithm) 030304 developmental biology Recombination Genetic Whole genome sequencing Likelihood Functions 0303 health sciences Natural selection Haplotypes Adaptation Selective sweep 020602 bioinformatics Information Systems |
| Zdroj: | Briefings in Bioinformatics. 20:1997-2008 |
| ISSN: | 1477-4054 1467-5463 |
| DOI: | 10.1093/bib/bby064 |
| Popis: | Insights into genetic loci which are under selection and their functional roles contribute to increased understanding of the patterns of phenotypic variation we observe today. The availability of whole-genome sequence data, for humans and other species, provides opportunities to investigate adaptation and evolution at unprecedented resolution. Many analytical methods have been developed to interrogate these large data sets and characterize signatures of selection in the genome. We review here recently developed methods and consider the impact of increased computing power and data availability on the detection of selection signatures. Consideration of demography, recombination and other confounding factors is important, and use of a range of methods in combination is a powerful route to resolving different forms of selection in genome sequence data. Overall, a substantial improvement in methods for application to whole-genome sequencing is evident, although further work is required to develop robust and computationally efficient approaches which may increase reproducibility across studies. |
| Databáze: | OpenAIRE |
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