|Title||Efficient Signal Inclusion With Genomic Applications.|
|Publication Type||Journal Article|
|Year of Publication||2019|
|Authors||X Jeng, Jessie, Teng Zhang, and Jung-Ying Tzeng|
|Journal||J Am Stat Assoc|
This paper addresses the challenge of efficiently capturing a high proportion of true signals for subsequent data analyses when sample sizes are relatively limited with respect to data dimension. We propose the signal missing rate as a new measure for false negative control to account for the variability of false negative proportion. Novel data-adaptive procedures are developed to control signal missing rate without incurring many unnecessary false positives under dependence. We justify the efficiency and adaptivity of the proposed methods via theory and simulation. The proposed methods are applied to GWAS on human height to effectively remove irrelevant SNPs while retaining a high proportion of relevant SNPs for subsequent polygenic analysis.
|Alternate Journal||J Am Stat Assoc|
|Original Publication||Efficient signal inclusion with genomic applications|
|PubMed Central ID||PMC6953619|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R03 HG008642 / HG / NHGRI NIH HHS / United States
Efficient Signal Inclusion With Genomic Applications.