diploS/HIC: An Updated Approach to Classifying Selective Sweeps
| Publication Date: |
2018-06-01
|
|---|---|
| Publisher: |
Genetics Society of America (GSA)
|
| Electronic ISSN: |
2160-1836
|
| Topics: |
Biology
|
| Published by: |
| _version_ | 1836398952418639874 |
|---|---|
| autor | Kern, A. D., Schrider, D. R. |
| beschreibung | 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. |
| citation_standardnr | 6272844 |
| datenlieferant | ipn_articles |
| feed_id | 169615 |
| feed_publisher | Genetics Society of America (GSA) |
| feed_publisher_url | http://www.genetics-gsa.org/ |
| insertion_date | 2018-06-01 |
| journaleissn | 2160-1836 |
| publikationsjahr_anzeige | 2018 |
| publikationsjahr_facette | 2018 |
| publikationsjahr_intervall | 7984:2015-2019 |
| publikationsjahr_sort | 2018 |
| publisher | Genetics Society of America (GSA) |
| quelle | G3: Genes, Genomes, Genetics |
| relation | http://www.g3journal.org/cgi/content/short/8/6/1959?rss=1 |
| search_space | articles |
| shingle_author_1 | Kern, A. D., Schrider, D. R. |
| shingle_author_2 | Kern, A. D., Schrider, D. R. |
| shingle_author_3 | Kern, A. D., Schrider, D. R. |
| shingle_author_4 | Kern, A. D., Schrider, D. R. |
| shingle_catch_all_1 | 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 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. Kern, A. D., Schrider, D. R. Genetics Society of America (GSA) 2160-1836 21601836 |
| shingle_catch_all_2 | 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 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. Kern, A. D., Schrider, D. R. Genetics Society of America (GSA) 2160-1836 21601836 |
| shingle_catch_all_3 | 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 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. Kern, A. D., Schrider, D. R. Genetics Society of America (GSA) 2160-1836 21601836 |
| shingle_catch_all_4 | 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 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. Kern, A. D., Schrider, D. R. Genetics Society of America (GSA) 2160-1836 21601836 |
| shingle_title_1 | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| shingle_title_2 | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| shingle_title_3 | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| shingle_title_4 | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| timestamp | 2025-06-30T23:35:15.539Z |
| titel | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| titel_suche | diploS/HIC: An Updated Approach to Classifying Selective Sweeps |
| topic | W |
| uid | ipn_articles_6272844 |