Title
Comparative Studies On Multivariate Tests For Joint-Snvs Analysis And Detection For Bipolar Disorder Susceptibility Genes
Abstract
Instead of the single nucleotide variants (SNVs) analysis, many joint-SNVs analysis methods were proposed to tackle the `missing heritability problem' in the genome-wide association studies (GWASs). In this paper, we performed a comparative study on five typical methods for joint-SNVs analysis and a recently proposed method called Statistics-space Boundary-based test (Sspace BBT). For a fair and comprehensive comparison, we conducted simulation experiments by considering dominant single variant, effect direction, minor allele frequency (MAF), odds ratio (OR) and the linkage disequilibrium (LD). The results indicated that the S-space BBT not only does not swamp the significant SNV but also maintains stronger detection power under different configurations. As a result, we applied the S-space BBT to the dataset of bipolar disorder and obtained a list of biomarkers. Besides, the literature researches were conducted to validate the reliability of the results.
Year
DOI
Venue
2017
10.1504/IJDMB.2017.085714
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
Keywords
Field
DocType
GWAS, sequence analysis, joint-SNVs analysis, odds ratio, dominant single variant, effect direction, minor allele frequency, the linkage disequilibrium, S-space boundary-based test, bipolar disorder
Bipolar disorder,Linkage disequilibrium,Missing heritability problem,Multivariate statistics,Computer science,Genome-wide association study,Genetic association,Odds ratio,Minor allele frequency,Statistics
Journal
Volume
Issue
ISSN
17
4
1748-5673
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Jin-Xiong Lv101.69
Han-Chen Huang200.34
Runsheng Chen340431.48
Lei Xu43590387.32