Cargando…
Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data
BACKGROUND: A number of different statistics are used for detecting natural selection using DNA sequencing data, including statistics that are summaries of the frequency spectrum, such as Tajima’s D. These statistics are now often being applied in the analysis of Next Generation Sequencing (NGS) dat...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015034/ https://www.ncbi.nlm.nih.gov/pubmed/24088262 http://dx.doi.org/10.1186/1471-2105-14-289 |
_version_ | 1782315276046434304 |
---|---|
author | Korneliussen, Thorfinn Sand Moltke, Ida Albrechtsen, Anders Nielsen, Rasmus |
author_facet | Korneliussen, Thorfinn Sand Moltke, Ida Albrechtsen, Anders Nielsen, Rasmus |
author_sort | Korneliussen, Thorfinn Sand |
collection | PubMed |
description | BACKGROUND: A number of different statistics are used for detecting natural selection using DNA sequencing data, including statistics that are summaries of the frequency spectrum, such as Tajima’s D. These statistics are now often being applied in the analysis of Next Generation Sequencing (NGS) data. However, estimates of frequency spectra from NGS data are strongly affected by low sequencing coverage; the inherent technology dependent variation in sequencing depth causes systematic differences in the value of the statistic among genomic regions. RESULTS: We have developed an approach that accommodates the uncertainty of the data when calculating site frequency based neutrality test statistics. A salient feature of this approach is that it implicitly solves the problems of varying sequencing depth, missing data and avoids the need to infer variable sites for the analysis and thereby avoids ascertainment problems introduced by a SNP discovery process. CONCLUSION: Using an empirical Bayes approach for fast computations, we show that this method produces results for low-coverage NGS data comparable to those achieved when the genotypes are known without uncertainty. We also validate the method in an analysis of data from the 1000 genomes project. The method is implemented in a fast framework which enables researchers to perform these neutrality tests on a genome-wide scale. |
format | Online Article Text |
id | pubmed-4015034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40150342014-05-23 Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data Korneliussen, Thorfinn Sand Moltke, Ida Albrechtsen, Anders Nielsen, Rasmus BMC Bioinformatics Methodology Article BACKGROUND: A number of different statistics are used for detecting natural selection using DNA sequencing data, including statistics that are summaries of the frequency spectrum, such as Tajima’s D. These statistics are now often being applied in the analysis of Next Generation Sequencing (NGS) data. However, estimates of frequency spectra from NGS data are strongly affected by low sequencing coverage; the inherent technology dependent variation in sequencing depth causes systematic differences in the value of the statistic among genomic regions. RESULTS: We have developed an approach that accommodates the uncertainty of the data when calculating site frequency based neutrality test statistics. A salient feature of this approach is that it implicitly solves the problems of varying sequencing depth, missing data and avoids the need to infer variable sites for the analysis and thereby avoids ascertainment problems introduced by a SNP discovery process. CONCLUSION: Using an empirical Bayes approach for fast computations, we show that this method produces results for low-coverage NGS data comparable to those achieved when the genotypes are known without uncertainty. We also validate the method in an analysis of data from the 1000 genomes project. The method is implemented in a fast framework which enables researchers to perform these neutrality tests on a genome-wide scale. BioMed Central 2013-10-02 /pmc/articles/PMC4015034/ /pubmed/24088262 http://dx.doi.org/10.1186/1471-2105-14-289 Text en Copyright © 2013 Korneliussen et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Korneliussen, Thorfinn Sand Moltke, Ida Albrechtsen, Anders Nielsen, Rasmus Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data |
title | Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data |
title_full | Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data |
title_fullStr | Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data |
title_full_unstemmed | Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data |
title_short | Calculation of Tajima’s D and other neutrality test statistics from low depth next-generation sequencing data |
title_sort | calculation of tajima’s d and other neutrality test statistics from low depth next-generation sequencing data |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015034/ https://www.ncbi.nlm.nih.gov/pubmed/24088262 http://dx.doi.org/10.1186/1471-2105-14-289 |
work_keys_str_mv | AT korneliussenthorfinnsand calculationoftajimasdandotherneutralityteststatisticsfromlowdepthnextgenerationsequencingdata AT moltkeida calculationoftajimasdandotherneutralityteststatisticsfromlowdepthnextgenerationsequencingdata AT albrechtsenanders calculationoftajimasdandotherneutralityteststatisticsfromlowdepthnextgenerationsequencingdata AT nielsenrasmus calculationoftajimasdandotherneutralityteststatisticsfromlowdepthnextgenerationsequencingdata |