Does pathway analysis make it easier for common variants to tag rare ones?
Analyzing sequencing data is difficult because of the low frequency of rare variants, which may result in low power to detect associations. We consider pathway analysis to detect multiple common and rare variants jointly and to investigate whether analysis at the pathway level provides an alternativ...
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| Format: | Online |
| Language: | English |
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BioMed Central
2011
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287932/ |
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pubmed-3287932 |
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pubmed-32879322012-02-28 Does pathway analysis make it easier for common variants to tag rare ones? Uh, Hae-Won Tsonaka, Roula Houwing-Duistermaat, Jeanine J Proceedings Analyzing sequencing data is difficult because of the low frequency of rare variants, which may result in low power to detect associations. We consider pathway analysis to detect multiple common and rare variants jointly and to investigate whether analysis at the pathway level provides an alternative strategy for identifying susceptibility genes. Available pathway analysis methods for data from genome-wide association studies might not be efficient because these methods are designed to detect common variants. Here, we investigate the performance of several existing pathway analysis methods for sequencing data. In particular, we consider the global test, which does not consider linkage disequilibrium between the variants in a gene. We improve the performance of the global test by assigning larger weights to rare variants, as proposed in the weighted-sum approach. Our conclusion is that straightforward application of pathway analysis is not satisfactory; hence, when common and rare variants are jointly analyzed, larger weights should be assigned to rare variants. BioMed Central 2011-11-29 /pmc/articles/PMC3287932/ /pubmed/22373113 http://dx.doi.org/10.1186/1753-6561-5-S9-S90 Text en Copyright ©2011 Uh 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. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Uh, Hae-Won Tsonaka, Roula Houwing-Duistermaat, Jeanine J |
| spellingShingle |
Uh, Hae-Won Tsonaka, Roula Houwing-Duistermaat, Jeanine J Does pathway analysis make it easier for common variants to tag rare ones? |
| author_facet |
Uh, Hae-Won Tsonaka, Roula Houwing-Duistermaat, Jeanine J |
| author_sort |
Uh, Hae-Won |
| title |
Does pathway analysis make it easier for common variants to tag rare ones? |
| title_short |
Does pathway analysis make it easier for common variants to tag rare ones? |
| title_full |
Does pathway analysis make it easier for common variants to tag rare ones? |
| title_fullStr |
Does pathway analysis make it easier for common variants to tag rare ones? |
| title_full_unstemmed |
Does pathway analysis make it easier for common variants to tag rare ones? |
| title_sort |
does pathway analysis make it easier for common variants to tag rare ones? |
| description |
Analyzing sequencing data is difficult because of the low frequency of rare variants, which may result in low power to detect associations. We consider pathway analysis to detect multiple common and rare variants jointly and to investigate whether analysis at the pathway level provides an alternative strategy for identifying susceptibility genes. Available pathway analysis methods for data from genome-wide association studies might not be efficient because these methods are designed to detect common variants. Here, we investigate the performance of several existing pathway analysis methods for sequencing data. In particular, we consider the global test, which does not consider linkage disequilibrium between the variants in a gene. We improve the performance of the global test by assigning larger weights to rare variants, as proposed in the weighted-sum approach. Our conclusion is that straightforward application of pathway analysis is not satisfactory; hence, when common and rare variants are jointly analyzed, larger weights should be assigned to rare variants. |
| publisher |
BioMed Central |
| publishDate |
2011 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287932/ |
| _version_ |
1611508791165059072 |