The Huff lab is excited to announce the recent addition of a new post-doctoral fellow, Yao Yu. Yao's research interests include high-throughput genomics and transcriptomics. He completed his doctoral research at the Shanghai Institutes for Biological Sciences, and his work will be focused on the genetic basis of common cancers from high-throughput omics data.
Author Archives: Loni Huff
Jiun-Sheng Chen joins Huff Lab
The Huff lab is happy to welcome its first graduate student, Jiun-Sheng (Roger) Chen. Roger is a Ph.D. student at the University of Texas Graduate School of Biomedical Sciences and will initially be focused on identifying common, complex disease genes using pVAAST on whole-exome and whole-genome sequencing data. Welcome, Roger!
pVAAST publicly available
We are pleased to announce that the paper describing pVAAST (the pedigree Variant Annotation, Analysis, and Search Tool has just been published in Nature Biotechnology.
pVAAST is a software tool that searches whole-exome and whole-genome sequence data in families to identify genetic variants that directly influence disease risk. pVAAST analyzes the DNA sequences of patients, their relatives, and healthy people in a highly automated fashion to provide probabilistic predictions of the specific genetic variants and genes that are increasing the risk of developing disease. pVAAST combines the existing variant prioritization and case-control association features in VAAST with a new linkage analysis method specifically designed for sequence data. This model is broadly similar to traditional linkage analysis but is capable of modeling de novo mutations and is more sensitive in scenarios with incomplete penetrance or locus heterogeneity. pVAAST supports dominant, recessive, and de novo inheritance models, and maintains high power across a wide variety of study designs, from monogenic, Mendelian diseases in a single family to highly polygenic, common diseases involving hundreds of families.
In a separate paper published two weeks ago in Cancer Discovery and led by our collaborators at the University of Utah and the University of Melbourne, we used pVAAST to aid in the discovery that rare variants in the gene RINT1 increase the risk of developing breast cancer and Lynch-Syndrome spectrum cancers.
Learn more about pVAAST or click here to register to download pVAAST as part of the VAAST software package.