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On optimal pooling designs to identify rare variants through massive resequencing
The advent of next-generation sequencing technologies has facilitated the detection of rare variants. Despite the significant cost reduction, sequencing cost is still high for large-scale studies. In this article, we examine DNA pooling as a cost-effective strategy for rare variant detection. We con...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wiley Subscription Services, Inc., A Wiley Company
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176340/ https://www.ncbi.nlm.nih.gov/pubmed/21254222 http://dx.doi.org/10.1002/gepi.20561 |
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author | Lee, Joon Sang Choi, Murim Yan, Xiting Lifton, Richard P Zhao, Hongyu |
author_facet | Lee, Joon Sang Choi, Murim Yan, Xiting Lifton, Richard P Zhao, Hongyu |
author_sort | Lee, Joon Sang |
collection | PubMed |
description | The advent of next-generation sequencing technologies has facilitated the detection of rare variants. Despite the significant cost reduction, sequencing cost is still high for large-scale studies. In this article, we examine DNA pooling as a cost-effective strategy for rare variant detection. We consider the optimal number of individuals in a DNA pool to detect an allele with a specific minor allele frequency (MAF) under a given coverage depth and detection threshold. We found that the optimal number of individuals in a pool is indifferent to the MAF at the same coverage depth and detection threshold. In addition, when the individual contributions to each pool are equal, the total number of individuals across different pools required in an optimal design to detect a variant with a desired power is similar at different coverage depths. When the contributions are more variable, more individuals tend to be needed for higher coverage depths. Our study provides general guidelines on using DNA pooling for more cost-effective identifications of rare variants. Genet. Epidemiol. 35:139-147, 2011. © 2011 Wiley-Liss, Inc. |
format | Online Article Text |
id | pubmed-3176340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Wiley Subscription Services, Inc., A Wiley Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-31763402011-09-19 On optimal pooling designs to identify rare variants through massive resequencing Lee, Joon Sang Choi, Murim Yan, Xiting Lifton, Richard P Zhao, Hongyu Genet Epidemiol Original Articles The advent of next-generation sequencing technologies has facilitated the detection of rare variants. Despite the significant cost reduction, sequencing cost is still high for large-scale studies. In this article, we examine DNA pooling as a cost-effective strategy for rare variant detection. We consider the optimal number of individuals in a DNA pool to detect an allele with a specific minor allele frequency (MAF) under a given coverage depth and detection threshold. We found that the optimal number of individuals in a pool is indifferent to the MAF at the same coverage depth and detection threshold. In addition, when the individual contributions to each pool are equal, the total number of individuals across different pools required in an optimal design to detect a variant with a desired power is similar at different coverage depths. When the contributions are more variable, more individuals tend to be needed for higher coverage depths. Our study provides general guidelines on using DNA pooling for more cost-effective identifications of rare variants. Genet. Epidemiol. 35:139-147, 2011. © 2011 Wiley-Liss, Inc. Wiley Subscription Services, Inc., A Wiley Company 2011-04 2011-01-19 /pmc/articles/PMC3176340/ /pubmed/21254222 http://dx.doi.org/10.1002/gepi.20561 Text en © 2011 Wiley-Liss, Inc. http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation. |
spellingShingle | Original Articles Lee, Joon Sang Choi, Murim Yan, Xiting Lifton, Richard P Zhao, Hongyu On optimal pooling designs to identify rare variants through massive resequencing |
title | On optimal pooling designs to identify rare variants through massive resequencing |
title_full | On optimal pooling designs to identify rare variants through massive resequencing |
title_fullStr | On optimal pooling designs to identify rare variants through massive resequencing |
title_full_unstemmed | On optimal pooling designs to identify rare variants through massive resequencing |
title_short | On optimal pooling designs to identify rare variants through massive resequencing |
title_sort | on optimal pooling designs to identify rare variants through massive resequencing |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176340/ https://www.ncbi.nlm.nih.gov/pubmed/21254222 http://dx.doi.org/10.1002/gepi.20561 |
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