| 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 | 387 | 2020 |
| 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 | 181 | 2020 |
| 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 | 126 | 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 | 109* | 2019 |
| Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST W Liu, X Liao, Z Luo, Y Yang, MC Lau, Y Jiao, X Shi, W Zhai, H Ji, ... Nature Communications 14 (1), 296, 2023 | 69 | 2023 |
| 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 | 69 | 2020 |
| 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 | 65 | 2022 |
| Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data W Liu, X Liao, Y Yang, H Lin, J Yeong, X Zhou, X Shi, J Liu Nucleic Acids Research 50 (12), e72-e72, 2022 | 63 | 2022 |
| 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 | 57* | 2021 |
| 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 | 57 | 2013 |
| 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 | 52 | 2020 |
| A deep generative approach to conditional sampling X Zhou, Y Jiao, J Liu, J Huang Journal of the American Statistical Association 118 (543), 1837-1848, 2023 | 50 | 2023 |
| Integrating omics data G Tseng, D Ghosh, XJ Zhou Cambridge University Press, 2015 | 50 | 2015 |
| 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 | 50 | 2012 |
| Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology Q Cheng, X Zhang, LS Chen, J Liu Nature Communications 13 (1), 6490, 2022 | 49 | 2022 |
| Integrative analysis of cancer diagnosis studies with composite penalization J Liu, S Ma, J Huang Scandinavian Journal of Statistics 41 (1), 87-103, 2014 | 46 | 2014 |
| 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 | 45 | 2019 |
| 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 | 44 | 2015 |
| Canonical variate regression C Luo, J Liu, DK Dey, K Chen Biostatistics 17 (3), 468-483, 2016 | 41 | 2016 |
| 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 | 39 | 2013 |
