Xing Qiu, PhD
Professor of Biostatistics and Computational Biology
Ph.D. (2004) University of Rochester
Contact Information
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University of Rochester
Dept of Biostatistics and Computational Biology
265 Crittenden Boulevard, CU 420630
Rochester, New York 14642-0630
Office: Saunders Research Building 4220
Phone: (585) 275-0666
Fax: (585) 273-1031
E-mail: xing_qiu@urmc.rochester.edu
Research Interests
I am a statistician and computational biologist working in the field of BigData analytics (high-throughput data analysis). I received my PhD in Mathematics (area: stochastic differential equations) from the University of Rochester in 2004. I joined the faculty of the Department of Biostatistics and Computational Biology at the University of Rochester in 2007.
I have developed many statistical and computational methods for analyzing and integrating large-scale data with complex correlation structures such as various Omics data (gene expression, protein expression, microbiota abundance and diversity, etc) and medical image data (primarily structural MRI data).
I have published 100 journal articles and book chapters, covering research topics such as Omics data pre-processing, hypothesis testing, multiple testing adjustment, functional data analysis, cluster analysis, network analysis, gene set enrichment analyses, and spatial statistical analysis for Diffusion Tensor Imaging data.
Examples of my ongoing research projects:
- A Multi-step Integrative Analysis Pipeline for Multi-Omics Data
- Multi-site data integration based on novel batch effect removal method and cross-platform normalization method
- A robust normalization and differential expression analysis pipeline (the super-delta method)
- A penalized multi-set CCA method for dimension reduction
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A computationally efficient linear mixed effects regression framework based on moment method, which can be used to estimate parameters and make correct inferences for correlated data with heterogeneous variance-covariance structure
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A robust meta-analysis framework to combine results from multiple studies
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Machine learning techniques for building predictive models based on features exacted from various datasets.
- Multi-dimensional functional data analysis
- Computationally efficient representation methods based on tensor decomposition for multidimensional functional date (e.g., various neuro-image data; spatial and spatio-temporal data)
- Hypothesis testing for functional data analysis
- Partial differential equation modeling based on multidimensional data analysis
- Network Analysis
- Network reconstruction based on High-dimensional Ordinary Differential Equations and State Space Modeling
- Network hypothesis testing
- Network feature extraction and dimensionality reduction
- Personalized Analyses for Longitudinal Imaging Data Based on Perona-Malik Equation and other diffusion equations
- Multiple Testing Procedure and P-value combination test for Data with Rank-deficient Correlation Structure
- Using Lie Groups and Haar Measure in manifold-based statistical learning.
Collaborative research:
I am an active participant in collaborative research. Over the years, I have been involved in 20+ NIH or University of Rochester sponsored collaborative research projects; most of them are related to infectious diseases such as influenza, respiratory syncytial virus, and HIV. I was in Data Management, Informatics and Computational Biology Core Leader of the University of Rochester Respiratory Pathogens Research Center (RPRC) and the Bioinformatics and Computational Biology Unit Leader of Center for AIDS Research (CFAR) at the University of Rochester.
Full List of Publications
Please visit my URMC Profile or my Google Scholar page for the complete list of my publications.
Selected Publications
Novel Methodologies for Omics Data Analysis
- McCall, M.N., Chu, C.Y., Wang, L., Benoodt, L., Thakar, J., Corbett, A., Holden-Wiltse, J., Slaunwhite, C., Grier, A., Gill, S.R., Ann R. Falsey, A.R., Topham, D.J., Caserta, M.T., Walsh, E.E., Qiu, X.*, and Mariani*, T.J. (2022+) A systems genomics approach uncovers molecular associates of RSV severity. PLoS Computational Biology, in press. [*Co-corresponding author] PMID: 34962914
- Cui, Z., Liu, Y., Zhang*, J., and Qiu*, X. (2022) Super-delta2: An Enhanced Differential Expression Analysis Procedure for Multi-Group Comparisons of RNA-seq Data. Bioinformatics, in press. [*Senior authorship shared] PMID: 33693477
- Zhang, S., Shao, J., Yu, D., Qiu, X., and Zhang*, J. (2020) MatchMixeR: A Cross-platform Normalization Method for Gene Expression Data Integration. Bioinformatics, 36(8), 2486-2491. [*Senior authorship shared] PMID: 31904810.
- Wu*, L., Qiu, X., Yuan, Y.X., and Wu, H. (2019) Parameter Estimation and Variable Selection for Big systems of High-Dimensional Linear Ordinary Differential Equations: A Matrix-Based Approach. Journal of American Statistical Association, 114(526): 657-667. [*First authorship shared]
- Zhang, Y., Topham, J.D., Thakar*, J., and Qiu, X. (2017) FUNNEL-GSEA: FUNctioNal ELastic-net Regression in time-course Gene Set Enrichment Analysis. Bioinformatics, 33(13): 1944-1952. [*Senior authorship shared] PMID: 28334094.
- Hu, R., Qiu, X., and Glazko, G. (2010). A new gene selection procedure based on the covariance distance. Bioinformatics, 26(3):348-354. PMCID: PMC2815661.
- Gordon, A., Glazko, G., Qiu, X. and Yakovlev, A. (2007). Control of the Mean Number of False Discoveries, Bonferroni, and Stability of Multiple Testing, Annals of Applied Statistics, 1(1):179-190.
- Klebanov, L., Qiu, X., Welle, S., and Yakovlev, A. (2007). Statistical methods and microarray data, Nature Biotechnology, 25(1):25-26. PMID: 17211383
Novel Methodologies for Diffusion Tensor Imaging Analysis
- Asselin, P. D., Gu, Y., Merchant-Borna, K., Abar, B., Wright, D. W., Qiu, X., & Bazarian, J. J. (2020). Spatial regression analysis of MR diffusion reveals subject-specific white matter changes associated with repetitive head impacts in contact sports. Scientific Reports, 10(1), 1-12. [*Corresponding author] PMID: 32788605, PMCID: PMC7423936.
- Liu*, B., Qiu, X., Zhu, T., Tian, W., Hu, R., Ekholm, S., Schifitto, G., Zhong, J. (2016) Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects, Physics in Medicine and Biology, 61(6): 2497. [*First authorship shared] PMID: 26948513.
- Liu*, B., Qiu, X., Zhu, T., Tian, W., Hu, R., Ekholm, S., Schifitto, G., Zhong, J. (2016) Spatial regression analysis of serial DTI for subject-specific longitudinal changes of neurodegenerative disease, NeuroImage: Clinical 11: 291-301. [*First authorship shared] PMID: 26977399, PMCID: PMC4782002.
- Zhu, T., Hu, R., Tian, W., Ekholm, S., Schifitto, G., Qiu, X., and Zhong*, J. (2013) Spatial regression analysis of diffusion tensor imaging (spread) for longitudinal progression of neurodegenerative disease in individual subjects. Magnetic Resonance Imaging, 31(10), 1657-1667. [*Senior authorship shared] PMID: 24099667
- Zhu, T., Hu, R., Qiu, X., Taylor, M., Tso, Y., Yiannoutsos, C., Navia, B., Mori, S., Ekholm, S., Schifitto, G., and Zhong, J. (2011) Quantification of accuracy and precision of multi-center DTI measurements: A diffusion phantom and human brain study. Neuroimage, 56(3):1398–1411. PMID:21316471; PMCID: PMC3085553
- Zhu, T., Hu, R., Tian, W., Ekholm, S., Schifitto, G., Qiu*, X., and Zhong*, J. (2013) Spatial regression analysis of diffusion tensor imaging (spread) for longitudinal progression of neurodegenerative disease in individual subjects. Magnetic Resonance Imaging, 31(10), 1657-1667. [*Senior authorship shared] PMID: 24099667
Collaborative Research Related to Infectious Diseases
- Wang, L., Chu, C.Y., McCall, M.N., Slaunwhite, C., Holden-Wiltse, J., Corbett, A., Ann R. Falsey, A.R., Topham, D.J., Caserta, M.T., Mariani*, T.J., Walsh*, E.E., Qiu, X. (2021) Airway Gene-Expression Classifiers for Respiratory Syncytial Virus (RSV) Disease Severity in Infants. BMC Medical Genomics, 14(57). [*Senior authorship shared] PMID: 33632195 PMCID: PMC7908785
- Chu*, C., Qiu, X., Wang, L., Bhattacharya, S., Lofthus, G., Corbett, A., Holden-Wiltse, J., Grier, A., Tesini, B., Gill, S.R., Falsey, A.R., Caserta, M.T., Walsh, E.E., and Mariani, T.J. (2016) The Healthy Infant Nasal Transcriptome: A Benchmark Study. Scientific Reports 6: 33994. [*First authorship shared] PMID: 27658638, PMCID: PMC5034274
- Qiu, X., Wu*, S., Hilchey, S. P., Thakar, J., Liu, Z. P., Welle, S. L., Henn, A.D., Wu, H., and Zand, M. S. (2015). Diversity in Compartmental Dynamics of Gene Regulatory Networks: The Immune Response in Primary Influenza A Infection in Mice. PloS one, 10(9), e0138110. [*First authorship shared] PMID: 26413862; PMCID: PMC4586376
Last updated: March 23, 2022