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A simple method for assessing the strength of evidence for association at the level of the whole gene

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A simple method for assessing the strength of evidence for association at the level of the whole gene. / Curtis, David; Vine, Anna E.; Knight, Jo.

In: Advances and Applications in Bioinformatics and Chemistry : AABC, Vol. 1, 17.11.2008, p. 115-120.

Research output: Contribution to journalJournal articlepeer-review

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Curtis, D, Vine, AE & Knight, J 2008, 'A simple method for assessing the strength of evidence for association at the level of the whole gene', Advances and Applications in Bioinformatics and Chemistry : AABC, vol. 1, pp. 115-120. https://doi.org/10.2147/AABC.S4095

APA

Curtis, D., Vine, A. E., & Knight, J. (2008). A simple method for assessing the strength of evidence for association at the level of the whole gene. Advances and Applications in Bioinformatics and Chemistry : AABC, 1, 115-120. https://doi.org/10.2147/AABC.S4095

Vancouver

Curtis D, Vine AE, Knight J. A simple method for assessing the strength of evidence for association at the level of the whole gene. Advances and Applications in Bioinformatics and Chemistry : AABC. 2008 Nov 17;1:115-120. https://doi.org/10.2147/AABC.S4095

Author

Curtis, David ; Vine, Anna E. ; Knight, Jo. / A simple method for assessing the strength of evidence for association at the level of the whole gene. In: Advances and Applications in Bioinformatics and Chemistry : AABC. 2008 ; Vol. 1. pp. 115-120.

Bibtex

@article{a390ba2838fb4b7aab6f1bd812d705d5,
title = "A simple method for assessing the strength of evidence for association at the level of the whole gene",
abstract = "INTRODUCTION: It is expected that different markers may show different patterns of association with different pathogenic variants within a given gene. It would be helpful to combine the evidence implicating association at the level of the whole gene rather than just for individual markers or haplotypes. Doing this is complicated by the fact that different markers do not represent independent sources of information.METHOD: We propose combining the p values from all single locus and/or multilocus analyses of different markers according to the formula of Fisher, X = ∑(-2ln(p(i))), and then assessing the empirical significance of this statistic using permutation testing. We present an example application to 19 markers around the HTRA2 gene in a case-control study of Parkinson's disease.RESULTS: Applying our approach shows that, although some individual tests produce low p values, overall association at the level of the gene is not supported.DISCUSSION: Approaches such as this should be more widely used in assimilating the overall evidence supporting involvement of a gene in a particular disease. Information can be combined from biallelic and multiallelic markers and from single markers along with multimarker analyses. Single genes can be tested or results from groups of genes involved in the same pathway could be combined in order to test biologically relevant hypotheses. The approach has been implemented in a computer program called COMBASSOC which is made available for downloading.",
author = "David Curtis and Vine, {Anna E.} and Jo Knight",
note = "This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.",
year = "2008",
month = nov,
day = "17",
doi = "10.2147/AABC.S4095",
language = "English",
volume = "1",
pages = "115--120",
journal = "Advances and Applications in Bioinformatics and Chemistry : AABC",
issn = "1178-6949",
publisher = "Dove Medical Press Ltd.",

}

RIS

TY - JOUR

T1 - A simple method for assessing the strength of evidence for association at the level of the whole gene

AU - Curtis, David

AU - Vine, Anna E.

AU - Knight, Jo

N1 - This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

PY - 2008/11/17

Y1 - 2008/11/17

N2 - INTRODUCTION: It is expected that different markers may show different patterns of association with different pathogenic variants within a given gene. It would be helpful to combine the evidence implicating association at the level of the whole gene rather than just for individual markers or haplotypes. Doing this is complicated by the fact that different markers do not represent independent sources of information.METHOD: We propose combining the p values from all single locus and/or multilocus analyses of different markers according to the formula of Fisher, X = ∑(-2ln(p(i))), and then assessing the empirical significance of this statistic using permutation testing. We present an example application to 19 markers around the HTRA2 gene in a case-control study of Parkinson's disease.RESULTS: Applying our approach shows that, although some individual tests produce low p values, overall association at the level of the gene is not supported.DISCUSSION: Approaches such as this should be more widely used in assimilating the overall evidence supporting involvement of a gene in a particular disease. Information can be combined from biallelic and multiallelic markers and from single markers along with multimarker analyses. Single genes can be tested or results from groups of genes involved in the same pathway could be combined in order to test biologically relevant hypotheses. The approach has been implemented in a computer program called COMBASSOC which is made available for downloading.

AB - INTRODUCTION: It is expected that different markers may show different patterns of association with different pathogenic variants within a given gene. It would be helpful to combine the evidence implicating association at the level of the whole gene rather than just for individual markers or haplotypes. Doing this is complicated by the fact that different markers do not represent independent sources of information.METHOD: We propose combining the p values from all single locus and/or multilocus analyses of different markers according to the formula of Fisher, X = ∑(-2ln(p(i))), and then assessing the empirical significance of this statistic using permutation testing. We present an example application to 19 markers around the HTRA2 gene in a case-control study of Parkinson's disease.RESULTS: Applying our approach shows that, although some individual tests produce low p values, overall association at the level of the gene is not supported.DISCUSSION: Approaches such as this should be more widely used in assimilating the overall evidence supporting involvement of a gene in a particular disease. Information can be combined from biallelic and multiallelic markers and from single markers along with multimarker analyses. Single genes can be tested or results from groups of genes involved in the same pathway could be combined in order to test biologically relevant hypotheses. The approach has been implemented in a computer program called COMBASSOC which is made available for downloading.

U2 - 10.2147/AABC.S4095

DO - 10.2147/AABC.S4095

M3 - Journal article

C2 - 21918610

VL - 1

SP - 115

EP - 120

JO - Advances and Applications in Bioinformatics and Chemistry : AABC

JF - Advances and Applications in Bioinformatics and Chemistry : AABC

SN - 1178-6949

ER -