Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis

Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis

The publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, si...

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Main Authors: Seoung Wan Nam, Kwang Seob Lee, Jae Won Yang, Younhee Ko, Michael Eisenhut, Keum Hwa Lee, Jae Il Shin, Andreas Kronbichler
Format: Article
Language:English
Published: The Korean Pediatric Society 2021-05-01
Series:Clinical and Experimental Pediatrics
Subjects:
systemic lupus erythematosus
false-positive report probability
bayesian false-discovery probability
string database
protein-protein interaction
Online Access:http://www.e-cep.org/upload/pdf/cep-2020-00633.pdf
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spelling doaj-e86b4a14e68d429da9bc3f48403d866d2021-05-04T06:14:44ZengThe Korean Pediatric SocietyClinical and Experimental Pediatrics2713-41482021-05-0164520822210.3345/cep.2020.0063320125555167Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysisSeoung Wan Nam0Kwang Seob Lee1Jae Won Yang2Younhee Ko3Michael Eisenhut4Keum Hwa Lee5Jae Il Shin6Andreas Kronbichler7 Department of Rheumatology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea Department of Nephrology, Yonsei University Wonju College of Medicine, Wonju, Korea Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin-si, Gyeonggi-do, Republic of Korea Department of Pediatrics, Luton & Dunstable University Hospital NHS Foundation Trust, Luton, United Kingdom Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea Department of Internal Medicine IV (Nephrology and Hypertension), Medical University Innsbruck, Innsbruck, AustriaThe publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, since most claimed candidate gene associations were false-positives, correctly interpreting the published results is important. In this review, we emphasize the importance of interpreting the results of genetic epidemiology meta-analyses using Bayesian statistics and gene network analysis, which could be applied in other diseases.http://www.e-cep.org/upload/pdf/cep-2020-00633.pdfsystemic lupus erythematosusfalse-positive report probabilitybayesian false-discovery probabilitystring databaseprotein-protein interaction
collection DOAJ
language English
format Article
sources DOAJ
author Seoung Wan Nam
Kwang Seob Lee
Jae Won Yang
Younhee Ko
Michael Eisenhut
Keum Hwa Lee
Jae Il Shin
Andreas Kronbichler
spellingShingle Seoung Wan Nam
Kwang Seob Lee
Jae Won Yang
Younhee Ko
Michael Eisenhut
Keum Hwa Lee
Jae Il Shin
Andreas Kronbichler
Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis
Clinical and Experimental Pediatrics
systemic lupus erythematosus
false-positive report probability
bayesian false-discovery probability
string database
protein-protein interaction
author_facet Seoung Wan Nam
Kwang Seob Lee
Jae Won Yang
Younhee Ko
Michael Eisenhut
Keum Hwa Lee
Jae Il Shin
Andreas Kronbichler
author_sort Seoung Wan Nam
title Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis
title_short Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis
title_full Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis
title_fullStr Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis
title_full_unstemmed Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis
title_sort understanding the genetics of systemic lupus erythematosus using bayesian statistics and gene network analysis
publisher The Korean Pediatric Society
series Clinical and Experimental Pediatrics
issn 2713-4148
publishDate 2021-05-01
description The publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, since most claimed candidate gene associations were false-positives, correctly interpreting the published results is important. In this review, we emphasize the importance of interpreting the results of genetic epidemiology meta-analyses using Bayesian statistics and gene network analysis, which could be applied in other diseases.
topic systemic lupus erythematosus
false-positive report probability
bayesian false-discovery probability
string database
protein-protein interaction
url http://www.e-cep.org/upload/pdf/cep-2020-00633.pdf
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