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A non-threshold region-specific method for detecting rare variants in complex diseases
A region-specific method, NTR (non-threshold rare) variant detection method, was developed—it does not use the threshold for defining rare variants and accounts for directions of effects. NTR also considers linkage disequilibrium within the region and accommodates common and rare variants simultaneo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5708778/ https://www.ncbi.nlm.nih.gov/pubmed/29190701 http://dx.doi.org/10.1371/journal.pone.0188566 |
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author | Hsieh, Ai-Ru Chen, Dao-Peng Chattopadhyay, Amrita Sengupta Li, Ying-Ju Chang, Chien-Ching Fann, Cathy S. J. |
author_facet | Hsieh, Ai-Ru Chen, Dao-Peng Chattopadhyay, Amrita Sengupta Li, Ying-Ju Chang, Chien-Ching Fann, Cathy S. J. |
author_sort | Hsieh, Ai-Ru |
collection | PubMed |
description | A region-specific method, NTR (non-threshold rare) variant detection method, was developed—it does not use the threshold for defining rare variants and accounts for directions of effects. NTR also considers linkage disequilibrium within the region and accommodates common and rare variants simultaneously. NTR weighs variants according to minor allele frequency and odds ratio to combine the effects of common and rare variants on disease occurrence into a single score and provides a test statistic to assess the significance of the score. In the simulations, under different effect sizes, the power of NTR increased as the effect size increased, and the type I error of our method was controlled well. Moreover, NTR was compared with several other existing methods, including the combined multivariate and collapsing method (CMC), weighted sum statistic method (WSS), sequence kernel association test (SKAT), and its modification, SKAT-O. NTR yields comparable or better power in simulations, especially when the effects of linkage disequilibrium between variants were at least moderate. In an analysis of diabetic nephropathy data, NTR detected more confirmed disease-related genes than the other aforementioned methods. NTR can thus be used as a complementary tool to help in dissecting the etiology of complex diseases. |
format | Online Article Text |
id | pubmed-5708778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57087782017-12-15 A non-threshold region-specific method for detecting rare variants in complex diseases Hsieh, Ai-Ru Chen, Dao-Peng Chattopadhyay, Amrita Sengupta Li, Ying-Ju Chang, Chien-Ching Fann, Cathy S. J. PLoS One Research Article A region-specific method, NTR (non-threshold rare) variant detection method, was developed—it does not use the threshold for defining rare variants and accounts for directions of effects. NTR also considers linkage disequilibrium within the region and accommodates common and rare variants simultaneously. NTR weighs variants according to minor allele frequency and odds ratio to combine the effects of common and rare variants on disease occurrence into a single score and provides a test statistic to assess the significance of the score. In the simulations, under different effect sizes, the power of NTR increased as the effect size increased, and the type I error of our method was controlled well. Moreover, NTR was compared with several other existing methods, including the combined multivariate and collapsing method (CMC), weighted sum statistic method (WSS), sequence kernel association test (SKAT), and its modification, SKAT-O. NTR yields comparable or better power in simulations, especially when the effects of linkage disequilibrium between variants were at least moderate. In an analysis of diabetic nephropathy data, NTR detected more confirmed disease-related genes than the other aforementioned methods. NTR can thus be used as a complementary tool to help in dissecting the etiology of complex diseases. Public Library of Science 2017-11-30 /pmc/articles/PMC5708778/ /pubmed/29190701 http://dx.doi.org/10.1371/journal.pone.0188566 Text en © 2017 Hsieh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hsieh, Ai-Ru Chen, Dao-Peng Chattopadhyay, Amrita Sengupta Li, Ying-Ju Chang, Chien-Ching Fann, Cathy S. J. A non-threshold region-specific method for detecting rare variants in complex diseases |
title | A non-threshold region-specific method for detecting rare variants in complex diseases |
title_full | A non-threshold region-specific method for detecting rare variants in complex diseases |
title_fullStr | A non-threshold region-specific method for detecting rare variants in complex diseases |
title_full_unstemmed | A non-threshold region-specific method for detecting rare variants in complex diseases |
title_short | A non-threshold region-specific method for detecting rare variants in complex diseases |
title_sort | non-threshold region-specific method for detecting rare variants in complex diseases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5708778/ https://www.ncbi.nlm.nih.gov/pubmed/29190701 http://dx.doi.org/10.1371/journal.pone.0188566 |
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