Fast eQTL Analysis for Twin Studies
The availability of high throughput genotyping technologies has lead to many successful genome-wide association (GWA) studies in mapping genes of complex traits such as mental disorders like depression and schizophrenia. However, most of the genetic variants detected by GWA studies can only explain a small fraction of the heritability associated with these traits. Furthermore, the functional and regulatory consequences of the detected genetic variants are not clear, making the identification of causal genetic variants challenging. To gain insight into the possible regulatory role of single nucleotide polymorphisms (SNPs), it is popular to perform genetic mapping of expression quantitative trait loci (eQTLs) where gene expression of each transcript is treated as a complex trait whose association with SNPs is assessed. The integrated analysis of SNP and expression data could identify novel genetic pathways involved in complex traits. Many eQTL analyses on human data have revealed novel functional effects of thousands of single nucleotide polymorphisms (SNPs) and have uncovered novel genetic pathways involved in phenotypic variation.
Fei Zou Zhaoyu Yin
Department of Biostatistics The University of North Carolina at Chapel Hill Chapel Hill, NC 27599 Department of Biostatistics The University of North Carolina at Chapel Hill Chapel Hill,NC 27599
国际会议
Second Joint Biostatistics Symposium(第二届生物统计国际研讨会2012)
北京
英文
2-4
2012-07-08（万方平台首次上网日期，不代表论文的发表时间）