| Genomic landscape of lung adenocarcinoma in East Asians J Chen, H Yang, ASM Teo, LB Amer, FG Sherbaf, CQ Tan, JJS Alvarez, ... Nature Genetics 52 (2), 177-186, 2020 | 279 | 2020 |
| Prognostic value of CD8+ PD-1+ immune infiltrates and PDCD1 gene expression in triple negative breast cancer TKY Yeong, Joe and Lim, Jeffrey Chun Tatt and Lee, Bernett and Li, Huihua ... Journal for immunotherapy of cancer 7 (1), 34, 2019 | 86* | 2019 |
| Testing and controlling for horizontal pleiotropy with probabilistic Mendelian randomization in transcriptome-wide association studies Z Yuan, H Zhu, P Zeng, S Yang, S Sun, C Yang, J Liu, X Zhou Nature communications 11 (1), 3861, 2020 | 76 | 2020 |
| Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) for PD-L1 testing in triple-negative breast cancer: a translational assay compared with conventional IHC J Yeong, T Tan, ZL Chow, Q Cheng, B Lee, A Seet, JX Lim, JCT Lim, ... Journal of Clinical Pathology 73 (9), 557-562, 2020 | 60 | 2020 |
| Identification of gene–environment interactions in cancer studies using penalization J Liu, J Huang, Y Zhang, Q Lan, N Rothman, T Zheng, S Ma Genomics 102 (4), 189-194, 2013 | 51 | 2013 |
| Incorporating group correlations in genome-wide association studies using smoothed group Lasso J Liu, J Huang, S Ma, K Wang Biostatistics 14 (2), 205-219, 2012 | 46 | 2012 |
| Integrating omics data G Tseng, D Ghosh, XJ Zhou Cambridge University Press, 2015 | 45 | 2015 |
| A unified primal dual active set algorithm for nonconvex sparse recovery J Huang, Y Jiao, B Jin, J Liu, X Lu, C Yang Statistical Science 36 (2), 215-238, 2021 | 44* | 2021 |
| Integrative analysis of cancer diagnosis studies with composite penalization J Liu, S Ma, J Huang Scandinavian Journal of Statistics 41 (1), 87-103, 2014 | 41 | 2014 |
| SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes Y Yang, X Shi, W Liu, Q Zhou, M Chan Lau, J Chun Tatt Lim, L Sun, ... Briefings in bioinformatics 23 (1), bbab466, 2022 | 40 | 2022 |
| Integrative analysis of ‘‐omics’ data using penalty functions Q Zhao, X Shi, J Huang, J Liu, Y Li, S Ma Wiley Interdisciplinary Reviews: Computational Statistics 7 (1), 99-108, 2015 | 40 | 2015 |
| CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information C Yang, X Wan, X Lin, M Chen, X Zhou, J Liu Bioinformatics 35 (10), 1644-1652, 2019 | 37 | 2019 |
| Accounting for linkage disequilibrium in genome-wide association studies: a penalized regression method J Liu, K Wang, S Ma, J Huang Statistics and Its Interface 6 (1), 99 – 115, 2013 | 35 | 2013 |
| Differentially co-expressed genes in postmortem prefrontal cortex of individuals with alcohol use disorders: influence on alcohol metabolism-related pathways H Zhang, F Wang, H Xu, Y Liu, J Liu, H Zhao, J Gelernter Human Genetics 133 (11), 1383-1394, 2014 | 34 | 2014 |
| Bayesian weighted Mendelian randomization for causal inference based on summary statistics J Zhao, J Ming, X Hu, G Chen, J Liu, C Yang Bioinformatics 36 (5), 1501-1508, 2020 | 33 | 2020 |
| Canonical variate regression C Luo, J Liu, DK Dey, K Chen Biostatistics 17 (3), 468-483, 2016 | 30 | 2016 |
| Metabolomic profile of arterial stiffness in aged adults AS Koh, F Gao, J Liu, KT Fridianto, J Ching, RS Tan, JI Wong, SJM Chua, ... Diabetes and Vascular Disease Research 15 (1), 74-80, 2018 | 29 | 2018 |
| A penalized robust method for identifying gene–environment interactions X Shi, J Liu, J Huang, Y Zhou, Y Xie, S Ma Genetic Epidemiology 38 (3), 220-230, 2014 | 29 | 2014 |
| MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy Q Cheng, Y Yang, X Shi, KF Yeung, C Yang, H Peng, J Liu NAR Genomics and Bioinformatics 2 (2), lqaa028, 2020 | 28 | 2020 |
| CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies Y Yang, X Shi, Y Jiao, J Huang, M Chen, X Zhou, L Sun, X Lin, C Yang, ... Bioinformatics 36 (7), 2009-2016, 2020 | 28 | 2020 |
