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

Abstract

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.

Keywords

• systemic lupus erythematosus
• false-positive report probability
• bayesian false-discovery probability
• string database
• protein-protein interaction