Publications

Preprints

Zhang S, Gao Y, Liu J, Wang Y, Yang C. Wasserstein-Wasserstein auto-encoders. arXiv preprint arXiv:1902.09323, 2019, Feb 25.
Huang J, Jiao Y, Liao X, Liu J^†, Yu Z. Deep dimension reduction for supervised representation learning. arXiv preprint arXiv:2006.05865, 2020, June 10. [software]

2023

Liu W^s, Liao X^s Luo Z, …, Liu J^*. Probabilistic embedding and clustering with alignment for spatial transcriptomics data integration with PRECAST. Nature Communications, 2023, accepted. [software]

2022

Cheng Q^s, Zhang X, Chen L^*, Liu J^*. Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology. Nature Communications, 2022, 13(1): 1-13. [software]
Liu W^s, Liao X, Yang Y, …, Liu J^*.Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data. Nucleic Acids Research, 2022, 50(12): e72. [software]
Cheng Q^s, Qiu T, Chai X, Sun B, Xia Y, Shi X, Liu J^*. MR-Corr²: a two-sample Mendelian randomization method that accounts for correlated horizontal pleiotropy using correlated instrumental variants. Bioinformatics, 2022, 38 (2): 303-310. [software]
Yang Y, Shi X, Zhou Q, …, Liu J^*. SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes. Briefings in Bioinformatics, 2022, 23(1): bbab466. [software]
Huang J, Jiao Y, Kang L, Liu J^†, Liu Y, Lu X. GSDAR: a fast Newton algorithm for l0 regularized generalized linear models with statistical guarantee. Computational Statistics, 2022, 37(1): 507-533.
Zhou M, Dai M, Yao Y, Liu J, Yang C, Peng H. BOLT-SSI: A statistical approach to screening interaction effects for ultra-high dimensional data. Statistica Sinica, 2022, accepted. [software]
Lau M, Yang Y, Goh D, Cheung C, … Liu J^* & Yeong J^*. Case report: Understanding the impact of persistent tissue-localization of SARS-CoV-2 on immune response activity via spatial transcriptomic analysis of two cancer patients with COVID-19 co-morbidity. Frontiers in Immunology, 2022, 13.
Kaya N, Chen J, Lai H, … & Zhai W.^*. Genome instability is associated with ethnic differences between Asians and Europeans in hepatocellular carcinoma. Theranostics, 2022, 12(10), 4703.

2021

Zhou X, Jiao Y, Liu J, Huang J. A Deep Generative Approach to Conditional Sampling. Journal of the American Statistical Association, 2021, accepted.
Goh D, Lee JN, Tien T, … , Liu J^*, Tan B^*, Yeong J^*. Comparison between non-pulmonary and pulmonary immune responses in a HIV decedent who succumbed to COVID-19. Gut, 2021, accepted.
Gao Y, Huang J, Jiao Y, Liu J^†. Deep Generative Learning via Euler Particle Transport. Proceedings of Machine Learning Research, 2021, 145, 1-33.

Liu W, Lin H, Zheng S, Liu J. Generalized factor model for ultra-high dimensional correlated variables with mixed types. Journal of the American Statistical Association, 2021, accepted.

Huang J, Jiao Y, Jin B, Liu J^†, Lu X, Yang C. A unified primal dual active set algorithm for nonconvex sparse recovery. Statistical Science, 2021, 36(2), 215-238. [software]

Huang J, Jiao Y, Liu J^†, Yang C. REMI: Regression with marginal information and its application in genome-wide association studies. Statistica Sinica, 2021, 31(4). [software]
Lu X, Zhou Q, Liu J^*, Sun L^* Protocol for comprehensive RNA sequencing analysis of murine long non-coding RNAs during aging. STAR protocols, 2021, 2(2), 100397
Gao B, Yang C, Liu J, Zhou X^* Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies. PLoS genetics, 2021, 17(1), e1009293.
Fan Q, Jia C, Liu J, Lu Y^* Robust recovery in 1-bit compressive sensing via lq-constrained least squares. Signal Processing, 2021, 179, 107822.

2020

Shi X, Chai X, Yang Y, Cheng Q, Jiao Y, … & Liu J^*. A tissue-specific collaborative mixed model for jointly analyzing multiple tissues in transcriptome-wide association studies. Nucleic Acids Research, 2020, 48(19): e109-e109.
Yuan Z, Zhu H, Zeng P, Yang S, Sun S, Yang C, Liu J, Zhou X. Testing and controlling for horizontal pleiotropy with the probabilistic Mendelian randomization in transcriptome-wide association studies. Nature Communications, 2020, 11(1): 1-14.
Zhou Q, Wan Q, Jiang Y, et al. A Landscape of Murine Long Non-Coding RNAs Reveals the Leading Transcriptome Alterations in Adipose Tissue during Aging. Cell Reports, 2020, 31(8): 107694.
Cheng Q^s, Yang Y^s, Shi X^s, Yeung K^s, Yang C, Peng H, Liu J^*. MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy. NAR Genomics and Bioinformatics, 2020, 2(2): lqaa028. [software]
Cai M, Chen L, Liu J^*, Yang C^*. IGREX for quantifying the impact of genetically regulated expression on phenotypes. NAR Genomics and Bioinformatics, 2020, 2(1): lqaa010. [software]
Yang Y^s, Shi X^s, Jiao Y, Huang J, Chen M, Zhou X, Sun L, Lin X, Yang C, Liu J^*. CoMM-S²: a collaborative mixed model using summary statistics in transcriptome-wide association studies. Bioinformatics, 2020, 36(7):2009-16.[software]
Zhao J, Ming J, Hu X, Liu J, Yang C. Bayesian weighted Mendelian Randomization for causal inference based on summary statistics. Bioinformatics, 2020, March;36(5):1501-08. [software]
Chen J, … , Liu J, …, Zhai W. Genomic landscape of lung adenocarcinoma in East Asians. Nature Genetics, 2020, 52, 177-186.
Cai M, Dai M, Ming J, Peng H, Liu J, Yang C. BIVAS: A scalable Bayesian method for bi-level variable selection with applications. Journal of Computational and Graphical Statistics, 2020, 29(1), 40-52. [software]
Yeong J, … , Liu J, …, Thike AA. Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) for PD-L1 testing in triple-negative breast cancer: a translational assay compared with conventional IHC. Journal of Clinical Pathology, 2020, 73(9): 557-562.
Ma CA, … , Liu J, …, Leung YY. The association of plasma IL-1Ra and related cytokines with radiographic severity of early knee osteoarthritis. Osteoarthritis and Cartilage Open, 2020, 2(2): 100046.

2019

Dai M, Wan X, Peng H, Wang Y, Liu Y, Liu J^*, Xu Z^*, Yang C^*. Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy. Bioinformatics, 2019, 35(10):1729-36. [software]
Yang C, Wan C, Lin X, Chen M, Zhou X, Liu J^*. CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information. Bioinformatics, 2019, 35(10):1644-52. [software]
Yeong J, Lim J C T, Lee B, … Yang Y^s, …Liu J et al. Prognostic value of CD8 + PD-1+ immune infiltrates and PDCD1 gene expression in triple negative breast cancer. Journal for ImmunoTherapy of Cancer, 2019,7(1):34.
Shi X^s, Jiao Y, Yang Y^s, Cheng CY, Yang C, Lin X^*, Liu J^*. VIMCO: variational inference for multiple correlated outcomes in
genome-wide association studies. Bioinformatics, 2019, 35(19):3693-3700. [software]

2018

Yang Y^s, Dai M, Huang J, Lin X, Yang C, Chen M, Liu J^*. LPG: a four-groups probabilistic approach to leveraging pleiotropy in genome-wide association studies. BMC Genomics, 2018, 19:503. [software]
Ming J, Dai M, Cai M, Wan X, Liu J^*, Yang C^*. LSMM: A statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics, 2018, 34(16):2788-96. [software]
Koh AS, Gao F, Liu J, Fridianto KT, Ching J, Tan RS, Wong JI, Chua SJ, Leng S, Zhong L, Keng BM. Metabolomic profile of arterial stiffness in aged adults. Diabetes and Vascular Disease Research, 15(1), 74-80.

2017

Liu J^*, Wan X^*, Wang C, Yang C, Zhou X, Yang C. LLR: a latent low-rank approach to colocalizing genetic risk variants in multiple GWAS. Bioinformatics, 2017, 33(24):3878-86. [software]
Dai M, Ming J, Cai M, Liu J, Yang C, Wan X, Xu Z. IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies. Bioinformatics, 2017, 33(18):2882-89. [software]
Huang Y, Liu J, Yi H, Shia BC, Ma S. Promoting similarity of model sparsity structures in integrative analysis of cancer genetic data. Statistics in medicine, 2017 Feb 10;36(3):509-59.

2016

Allen Jr JC, Nault JC, Zhu G, Khor AY, Liu J, Lim TK, Zucman-Rossi J, Chow PK. The transcriptomic G1–G6 signature of hepatocellular carcinoma in an Asian population: Association of G3 with microvascular invasion. Medicine. 2016, 95(47).
Liu J, Yang C, Shi X, Li C, Huang J, Zhao H, Ma S. Analyzing Association Mapping in Pedigree‐Based GWAS Using a Penalized Multitrait Mixed Model. Genetic epidemiology. 2016, 40(5):382-93.
Luo C, Liu J, Dey DK, Chen K. Canonical variate regression. Biostatistics. 2016, 17(3):468-83.
Yang C, Wan X, Liu J, Ng M. Introduction to Statistical Methods for Integrative Data Analysis in Genome-Wide Association Studies. In Big Data Analytics in Genomics 2016 (pp. 3-23). Springer International Publishing. (Book Chapter)
Liu J, Wan X, Ma S, Yang C. EPS: an empirical Bayes approach to integrating pleiotropy and tissue-specific information for prioritizing risk genes. Bioinformatics, 2016, 32(12):1856-64. [software]
Zhang Q, Zhang S, Liu J, Huang J, Ma S. Penalized integrative analysis under the accelerated failure time model. Statistica Sinica, 2016, 26, 493-508.

2015

Zhao Q, Shi X, Huang J, Liu J, Li Y, Ma S. Integrative analysis of ‘‐omics’ data using penalty functions. Wiley Interdisciplinary Reviews: Computational Statistics. 2015, 7(1):99-108.
Liu J, Shi X, Huang J and Ma S. Penalized integrative analysis of high-dimensional omics data. Integrating omics data: statistical and computational methods. ISBN: 9781107069114. (Book Chapter)
Liu J, Wang F, Gao X, Zhang H, Wan X, Yang C. A penalized regression approach for integrative analysis in genome-wide association studies. Journal of Biometrics and Biostatistics. 2015, 6(2):228.

2014

Liu J, Huang J, Zhang Y, Lan Q, Rothman N, Zheng T, Ma S. Integrative analysis of prognosis data on multiple cancer subtypes. Biometrics. 2014, 70(3):480-8.
Zhang H, Wang F, Xu H, Liu Y, Liu J, Zhao H, Gelernter J. Differentially co-expressed genes in postmortem prefrontal cortex of individuals with alcohol use disorders: influence on alcohol metabolism-related pathways. Human genetics. 2014, 133(11):1383-94.
Shi X, Shen S, Liu J, Huang J, Zhou Y, Ma S. Similarity of markers identified from cancer gene expression studies: observations from GEO. Briefings in bioinformatics. 2013, 15(5):671-84.
Liu J, Huang J, Ma S. Penalized multivariate linear mixed model for longitudinal genome-wide association studies. In BMC proceedings 2014 (Vol. 8, No. 1, p. S73). BioMed Central.
Shi X, Liu J, Huang J, Zhou Y, Xie Y, Ma S. A penalized robust method for identifying gene–environment interactions. Genetic epidemiology. 2014, 38(3):220-30.
Liu J, Ma S, Huang J. Integrative analysis of cancer diagnosis studies with composite penalization. Scandinavian Journal of Statistics. 2014, 41(1):87-103.
Shi X, Liu J, Huang J, Zhou Y, Shia B, Ma S. Integrative Analysis of High‐throughput Cancer Studies With Contrasted Penalization. Genetic epidemiology. 2014, 38(2):144-51.

2013 and earlier

Liu J, Huang J, Ma S. Integrative analysis of multiple cancer genomic datasets under the heterogeneity model. Statistics in medicine. 2013, 32(20):3509-21.
Liu J, Huang J, Xie Y, Ma S. Sparse group penalized integrative analysis of multiple cancer prognosis datasets. Genetics research. 2013, 95(2-3):68-77.
Liu J, Wang K, Ma S, Huang J. Accounting for linkage disequilibrium in genome-wide association studies: a penalized regression method. Statistics and its interface. 2013, 6(1):99.
Liu J, Huang J, Ma S. Incorporating network structure in integrative analysis of cancer prognosis data. Genetic epidemiology. 2013, 37(2):173-83.
Liu J, Huang J, Ma S. Integrative analysis of multiple cancer prognosis datasets under the heterogeneity model. In Topics in Applied Statistics 2013 (pp. 257-269). Springer, New York, NY.
Liu J, Huang J, Ma S. Analysis of genome-wide association studies with multiple outcomes using penalization. PloS one. 2012, 7(12):e51198.
Liu J^*, Huang J, Ma S, Wang K. Incorporating group correlations in genome-wide association studies using smoothed group Lasso. Biostatistics. 2012, 14(2):205-19.
Liu J, Wang K, Ma S, Huang J. Regularized regression method for genome-wide association studies. In BMC proceedings 2011 (Vol. 5, No. 9, p. S67). BioMed Central.
Thomas A, Abel HJ, Di Y, Faye LL, Jin J, Liu J, Wu Z, Paterson AD. Effect of linkage disequilibrium on the identification of functional variants. Genetic epidemiology. 2011, 35(S1).

^†: alphabetical order

^* :corresponding/ co-corresponding author

^s :work from lab members

Liu Lab

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