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Lemaçon, A. et al. VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis. Bioinformatics 33, 1389-1391 (2017).
Li, H. et al. A synthetic-diploid benchmark for accurate variant-calling evaluation. Nat Methods 15, 595-597 (2018).
Li, X. et al. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nat Genet 52, 969-983 (2020).
Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239-243 (2017).
Li, R. et al. Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression. Bioinformatics (2021). doi:10.1093/bioinformatics/btab095
Li, R. et al. Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank. Biostatistics (2020). doi:10.1093/biostatistics/kxaa038
Liu, D. et al. A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Genes for Pancreatic Cancer Risk. Cancer Res 80, 4346-4354 (2020).
Liu, B. & Montgomery, S. B. Identifying causal variants and genes using functional genomics in specialized cell types and contexts. Hum Genet 139, 95-102 (2020).
Liu, Y. et al. ACAT: A Fast and Powerful p Value Combination Method for Rare-Variant Analysis in Sequencing Studies. Am J Hum Genet 104, 410-421 (2019).
Liu, Z. & Lin, X. Multiple phenotype association tests using summary statistics in genome-wide association studies. Biometrics 74, 165-175 (2018).
Luo, R., Sedlazeck, F. J., Lam, T. - W. & Schatz, M. C. A multi-task convolutional deep neural network for variant calling in single molecule sequencing. Nat Commun 10, 998 (2019).