scholarly journals Power Analysis for Genetic Association Test (PAGEANT) provides insights to challenges for rare variant association studies

2017 ◽  
Vol 34 (9) ◽  
pp. 1506-1513 ◽  
Author(s):  
Andriy Derkach ◽  
Haoyu Zhang ◽  
Nilanjan Chatterjee
Keyword(s):  
Genetic Association ◽  
Rare Variant ◽  
Power Analysis ◽  
Association Studies ◽  
Association Test ◽  
Rare Variant Association ◽  
Genetic Association Test

scholarly journals A novel statistical method for rare-variant association studies in general pedigrees

2016 ◽  
Vol 10 (S7) ◽  
Author(s):  
Huanhuan Zhu ◽  
Zhenchuan Wang ◽  
Xuexia Wang ◽  
Qiuying Sha
Keyword(s):  
Statistical Method ◽  
Rare Variant ◽  
Association Studies ◽  
Rare Variant Association

scholarly journals Genomic Diversity Evaluation of Populus trichocarpa Germplasm for Rare Variant Genetic Association Studies

2020 ◽  
Vol 10 ◽  
Author(s):  
Anthony Piot ◽  
Julien Prunier ◽  
Nathalie Isabel ◽  
Jaroslav Klápště ◽  
Yousry A. El-Kassaby ◽  
...  
Keyword(s):  
Genetic Association ◽  
Rare Variant ◽  
Association Studies ◽  
Populus Trichocarpa ◽  
Genetic Association Studies ◽  
Genomic Diversity ◽  
Diversity Evaluation

scholarly journals Strategies to improve the performance of rare variant association studies by optimizing the selection of controls

2015 ◽  
pp. btv457
Author(s):  
Na Zhu ◽  
Verena Heinrich ◽  
Thorsten Dickhaus ◽  
Jochen Hecht ◽  
Peter N. Robinson ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Studies ◽  
Rare Variant Association ◽  
Selection Of

scholarly journals Rare variant association test with multiple phenotypes

2016 ◽  
Vol 41 (3) ◽  
pp. 198-209 ◽  
Author(s):  
Selyeong Lee ◽  
Sungho Won ◽  
Young Jin Kim ◽  
Yongkang Kim ◽  
Bong-Jo Kim ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Test ◽  
Rare Variant Association ◽  
Multiple Phenotypes ◽  
Rare Variant Association Test

scholarly journals An adaptive test for meta‐analysis of rare variant association studies

2019 ◽  
Vol 44 (1) ◽  
pp. 104-116
Author(s):  
Tianzhong Yang ◽  
Junghi Kim ◽  
Chong Wu ◽  
Yiding Ma ◽  
Peng Wei ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Studies ◽  
Meta Analysis ◽  
Rare Variant Association ◽  
Adaptive Test

scholarly journals A method for analyzing multiple continuous phenotypes in rare variant association studies allowing for flexible correlations in variant effects

2016 ◽  
Vol 24 (9) ◽  
pp. 1344-1351 ◽  
Author(s):  
Jianping Sun ◽  
◽  
Karim Oualkacha ◽  
Vincenzo Forgetta ◽  
Hou-Feng Zheng ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Studies ◽  
Rare Variant Association

scholarly journals The exhaustive genomic scan approach, with an application to rare-variant association analysis

2019 ◽  
Author(s):  
George Kanoungi ◽  
Michael Nothnagel ◽  
Tim Becker ◽  
Dmitriy Drichel
Keyword(s):  
Rare Variant ◽  
Association Studies ◽  
A Priori ◽  
Error Rates ◽  
Age Related Macular Degeneration ◽  
Data Sets ◽  
Rare Variant Association ◽  
Age Related ◽  
Genome Wide ◽  
Definition Of

AbstractRegion-based genome-wide scans are usually performed by use of a priori chosen analysis regions. Such an approach will likely miss the region comprising the strongest signal and, thus, may result in increased type II error rates and decreased power. Here, we propose a genomic exhaustive scan approach that analyzes all possible subsequences and does not rely on a prior definition of the analysis regions. As a prime instance, we present a computationally ultra-efficient implementation using the rare-variant collapsing test for phenotypic association, the genomic exhaustive collapsing scan (GECS). Our implementation allows for the identification of regions comprising the strongest signals in large, genome-wide rare-variant association studies while controlling the family-wise error rate via permutation. Application of GECS to two genomic data sets revealed several novel significantly associated regions for age-related macular degeneration and for schizophrenia. Our approach also offers a high potential for genome-wide scans for selection, methylation and other analyses.

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