Integrating functional annotation and statistical information in novel set-based rare-variants association tests for complex diseases
Grant Data
Project Title
Integrating functional annotation and statistical information in novel set-based rare-variants association tests for complex diseases
Principal Investigator
Professor Sham, Pak Chung
(Principal Investigator (PI))
Co-Investigator(s)
Dr Cherny Stacey Shawn
(Co-Investigator)
Professor Li Miaoxin
(Co-Investigator)
Dr Tang Sze Man
(Co-Investigator)
Duration
30
Start Date
2018-01-01
Amount
629365
Conference Title
Integrating functional annotation and statistical information in novel set-based rare-variants association tests for complex diseases
Presentation Title
Keywords
functional annotation, NGS, rare variants
Discipline
Genomic Medicine,Genetic Disease
Panel
Biology and Medicine (M)
HKU Project Code
17124017
Grant Type
General Research Fund (GRF)
Funding Year
2017
Status
Completed
Objectives
1 To implement the Kolmogorov-Smirnov (KS) test and a combined KS-burden test, and evaluate their properties and performance in simulated and real data sets. 2 To investigate the potential problems of the KS and combined KS-burden tests for rare-variants association, and to implement and evaluate possible solutions to these problems 3 To integrate functional information into the KS and combined KS-burden test to increase their statistical power. 4 To develop and implement a random forest or alternative algorithm for predicting the potential deleteriousness of nucleotide changes at all positions in a gene
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