RT Journal
A1 Huang, Dandan
A1 Yi, Xianfu
A1 Zhou, Yao
A1 Yao, Hongcheng
A1 Xu, Hang
A1 Wang, Jianhua
A1 Zhang, Shijie
A1 Nong, Wenyan
A1 Wang, Panwen
A1 Shi, Lei
A1 Xuan, Chenghao
A1 Li, Miaoxin
A1 Wang, Junwen
A1 Li, Weidong
A1 Kwan, Hoi Shan
A1 Sham, Pak Chung
A1 Wang, Kai
A1 Li, Mulin Jun
T1 Ultrafast and scalable variant annotation and prioritization with big functional genomics data
JF Genome Research 
JO Genome Research 
YR 2020 
FD December 01 
VO 30 
IS 12 
SP 1789 
OP 1801 
DO 10.1101/gr.267997.120 
UL http://genome.cshlp.org/content/30/12/1789.abstract 
AB The advances of large-scale genomics studies have enabled compilation of cell type–specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.