Estimation of p-values with Reduced Set of Genomic Association Data

• 발행기관: 한국자료분석학회
• 저자명: 이재용(Jaeyong Yee) 박미라(Mira Park)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.20 No.4, 1633~1643쪽, 전체 11쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2018.08.31

영문 초록

Permutation test has been in common use to get a statistical significance of an association measure when genomic association study is conducted. Its process involves repeated randomizing of the relationships between phenotype and genotype parts of the data as well as the calculation of the testing measure to form a null distribution point from each of the repetition. To compensate for the multiple comparison effect, which can result in overly optimistic p-values, the null distribution should be constructed by the maximum values among all the SNP combinations from each iteration. With increasing number of SNPs, especially when studying higher order gene-gene interactions, the amount of computation may soon become formidable. Possibility of dealing with reduced number of SNPs while producing the comparable result has been investigated in this paper. We found that, down to about 5% of the data considered, the estimated null distribution, verified by p-values were comparable to the one with original set of data.

목차

1. Introduction

2. Methods

3. Analysis

4. Conclusion

References

키워드

permutation test genomic association multiple comparison null distribution