Approach of Fusing Multiple Tests to Analyzing Rare Genetic Variants

作者：Liao, Bo^*; Zhou, Chunguang; Li, Xiong; Chen, Haowen

来源：Journal of Computational and Theoretical Nanoscience, 2014, 11(5): 1349-1353.

DOI：10.1166/jctn.2014.3503

• Score Test
• Fusion Method
• Common Variant
• Rare Variant

In anticipation of the availability of next-generation sequencing data, there are increasing interests in investigating association between complex traits and rare variants (RVs). Recent findings suggest that rare variant play an important role in both monogenic and common diseases. Due to their rarity, it remains unclear how to appropriately analyze the association between such variants and disease. Recently, several new tests for analyzing RVs have been developed, most of which are based on the idea of pooling/collapsing RVs. Based on the method of pooling/collapsing has some deficiencies, and thus put forward some method specific for RVs. However, as the number of non-causal CVs increases and/or in the presence of opposite association directions, the best method is not always the same. Therefore, we consider the integration of multiple methods to adapt to a variety of situations. We propose a robust and strong statistical test strategy to analyze association between complex traits and RVs. This strategy is to improve detection robustness by fusing multiple tests statistics. Using simulations, we show that this method does not suffer from significant power loss in all circumstances. Compared with other tests, the proposed method can have better power in the simulation data sets.

• 出版日期2014-5
• 单位湖南大学