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 (Author), Kwang Seob Lee (Author), Jae Won Yang (Author), Younhee Ko (Author), Michael Eisenhut (Author), Keum Hwa Lee (Author), Jae Il Shin (Author), Andreas Kronbichler (Author)
Format: Book
Published: The Korean Pediatric Society, 2021-05-01T00:00:00Z.
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100 1 0 |a Seoung Wan Nam  |e author 
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700 1 0 |a Jae Won Yang  |e author 
700 1 0 |a Younhee Ko  |e author 
700 1 0 |a Michael Eisenhut  |e author 
700 1 0 |a Keum Hwa Lee  |e author 
700 1 0 |a Jae Il Shin  |e author 
700 1 0 |a Andreas Kronbichler  |e author 
245 0 0 |a Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis 
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520 |a 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. 
546 |a EN 
690 |a systemic lupus erythematosus 
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786 0 |n Clinical and Experimental Pediatrics, Vol 64, Iss 5, Pp 208-222 (2021) 
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