Using genomic annotations increases statistical power to detect eGenes-Reference-Cited by-同舟云学术

Using genomic annotations increases statistical power to detect eGenes

Published:2016-06-15 Issue:12 Volume:32 Page:i156-i163
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:Bioinformatics

Author:

Duong Dat,Zou Jennifer,Hormozdiari Farhad,Sul Jae Hoon,Ernst Jason,Han Buhm,Eskin Eleazar

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/32/12/i156/6694802/btw272.pdf

Reference18 articles.

1. Benner C. . (2016) FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics, btw018.

2. The landscape of genetic complexity across 5,700 gene expression traits in yeast

3. Cis and Trans Effects of Human Genomic Variants on Gene Expression

4. Incorporating prior information into association studies

5. An Efficient Multiple-Testing Adjustment for eQTL Studies that Accounts for Linkage Disequilibrium between Variants

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