diploS/HIC: An Updated Approach to Classifying Selective Sweeps
Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective sweeps in genomes on the basis of patterns of genet...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Oxford University Press
2018-06-01
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| Series: | G3: Genes, Genomes, Genetics |
| Subjects: | |
| Online Access: | http://g3journal.org/lookup/doi/10.1534/g3.118.200262 |
| _version_ | 1818622967081336832 |
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| author | Andrew D. Kern Daniel R. Schrider |
| author_facet | Andrew D. Kern Daniel R. Schrider |
| author_sort | Andrew D. Kern |
| collection | DOAJ |
| description | Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective sweeps in genomes on the basis of patterns of genetic variation surrounding a window of the genome. While S/HIC was shown to be both powerful and precise, the utility of S/HIC was limited by the use of phased genomic data as input. In this report we describe a deep learning variant of our method, diploS/HIC, that uses unphased genotypes to accurately classify genomic windows. diploS/HIC is shown to be quite powerful even at moderate to small sample sizes. |
| first_indexed | 2024-12-16T18:33:34Z |
| format | Article |
| id | doaj.art-c4f0b7986c554061a2314c81d69aa5c7 |
| institution | Directory Open Access Journal |
| issn | 2160-1836 |
| language | English |
| last_indexed | 2024-12-16T18:33:34Z |
| publishDate | 2018-06-01 |
| publisher | Oxford University Press |
| record_format | Article |
| series | G3: Genes, Genomes, Genetics |
| spelling | doaj.art-c4f0b7986c554061a2314c81d69aa5c72022-12-21T22:21:14ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362018-06-01861959197010.1534/g3.118.20026210diploS/HIC: An Updated Approach to Classifying Selective SweepsAndrew D. KernDaniel R. SchriderIdentifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective sweeps in genomes on the basis of patterns of genetic variation surrounding a window of the genome. While S/HIC was shown to be both powerful and precise, the utility of S/HIC was limited by the use of phased genomic data as input. In this report we describe a deep learning variant of our method, diploS/HIC, that uses unphased genotypes to accurately classify genomic windows. diploS/HIC is shown to be quite powerful even at moderate to small sample sizes.http://g3journal.org/lookup/doi/10.1534/g3.118.200262Machine LearningDeep learningSelective SweepsAdaptationand Population genetics |
| spellingShingle | Andrew D. Kern Daniel R. Schrider diploS/HIC: An Updated Approach to Classifying Selective Sweeps G3: Genes, Genomes, Genetics Machine Learning Deep learning Selective Sweeps Adaptation and Population genetics |
| title | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| title_full | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| title_fullStr | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| title_full_unstemmed | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| title_short | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| title_sort | diplos hic an updated approach to classifying selective sweeps |
| topic | Machine Learning Deep learning Selective Sweeps Adaptation and Population genetics |
| url | http://g3journal.org/lookup/doi/10.1534/g3.118.200262 |
| work_keys_str_mv | AT andrewdkern diploshicanupdatedapproachtoclassifyingselectivesweeps AT danielrschrider diploshicanupdatedapproachtoclassifyingselectivesweeps |