Shuang Feng

Shuang Feng is a PhD student in Department of Biostatistics, working with professor Gonçalo Abecasis. She joined the program in 2010. Before joining the University of Michigan, she worked as an IT specialist in Southern Research Institute High-throughput Screening Center. Shuang earned her bachelor's and master's degrees from Shanghai JiaoTong University.

Shuang's research focuses on the development of statistical methods and tools for the identification and study of genetic variants influencing human disease. Under the lead of professor Gonçalo Abecasis, software that have been developed and released to public are:

• rarefy is a C++ tool to facilitate sequencing study design using family samples by selecting informative families and individuals from a sample. It takes account pedigree structure and calculates an informative score for each individual to evaluate the potential of carrying trait-influencing rare variants. Rarefy has been used for selecting individuals in Minnesota Twins substance abuse whole-genome sequencing project and SardiNia deep sequencing project.

• famRvTest is an efficient C++ tool for rare variant association analysis using a linear-mixed model approach. It handles population structure, familial relatedness and study-specific covariates. The tool supports both single variant and gene-level associations with various methods implemented. It has been used in eQTL and quantitative traits association analyses in T2Dgenes project.

• RAREMETALWORKER is a C++ tool to generate summary statistics for meta-analysis of rare variants using raremetal. FamRvTest handles both related and unrelated individuals. It has been used in tens of research centers and institutions around the world since its first release in 2012.

• RAREMETAL is a C++ tool for meta-analysis of rare variants. Raremetal supports both single variant and gene-level tests. It is currently being used in Exomechip blood lipids consortium meta-analyses and EMADS project.