Carnegie Mellon University

 Kathryn Roeder

UPMC Professor of Statistics and Life Sciences, Department of Statistics, Computational Biology Department


228B Baker Hall
Department of Statistics
Carnegie Mellon University
Pittsburgh, PA 15213
Work Phone: 412-268-5775

Administrative Assistant: Mari Alice McShane


Kathryn Roeder’s research focuses on developing statistical methods for analysis of genetic and genomic data with an aim to find associations between patterns of genetic variation and complex disease. To solve biologically relevant problems, her team utilizes modern statistical methods such as high dimensional statistics, statistical machine learning, nonparametric methods and networks. Her group developed tools for identifying autism risk genes from de novo mutations and, together with the Autism Sequencing Consortium, they have identified more than one hundred autism risk genes. Roeder’s team has developed some of the key statistical tools for the analysis of whole-genome sequencing data, and these methods have helped interpret the impact of noncoding variants on autism and other neuropsychiatric disorders. A recent focus of her group is developing tools for the analysis of single-cell multi-omic data.

Lab Members

 Tim Barry

Ph.D Student

 Zhanrui Cui

Ph.D. Student

 David Choi

Assistant Professor Statistics and Information Science

 Bernie Devlin


 Jin-Hong Du

Ph.D. Student

 Max G'Sell

Assistant Professor

 Jing Lei

Associate Professor

 Yue Li

Ph.D. Student

 Peng Liu

Postdoctoral Researcher

 Maya Shen

Ph.D. Student

 Jinjin Tian

Ph.D Student

 Catherine Wang

Ph.D Student

 Xuran Wang

Postdoctoral Researcher

 Ron Yurko

Ph.D. Student

Highlighted Publications

Tian, Jinjin, Jing Lei, and Kathryn Roeder. “From local to global gene co-expression estimation using single-cell RNA-seq data.” arXiv preprint arXiv:2203.01990 (2022).

Mahjani, Behrang, Lambertus Klei, Manuel Mattheisen, Matthew W. Halvorsen, Abraham Reichenberg, Kathryn Roeder, Nancy L. Pedersen et al. “The genetic architecture of obsessive-compulsive disorder: contribution of liability to OCD from alleles across the frequency spectrum.” American Journal of Psychiatry 179, no. 3 (2022): 216-225.

Chen, Danfeng, Katherine Tashman, Duncan S. Palmer, Benjamin Neale, Kathryn Roeder, Alex Bloemendal, Claire Churchhouse, and Zheng Tracy Ke. “A data harmonization pipeline to leverage external controls and boost power in GWAS.” Human Molecular Genetics 31, no. 3 (2022): 481-489.

Barry, Timothy, Eugene Katsevich, and Kathryn Roeder. “Exponential family measurement error models for single-cell CRISPR screens.” arXiv preprint arXiv:2201.01879 (2022).

Cai, Zhanrui, Jing Lei, and Kathryn Roeder. “Model-free Prediction Test with Application to Genomics Data.” bioRxiv (2022).

Wang, Xuran, David Choi, and Kathryn Roeder. “Constructing local cell-specific networks from single-cell data.” Proceedings of the National Academy of Sciences 118, no. 51 (2021): e2113178118.

Barry, Timothy, Xuran Wang, John A. Morris, Kathryn Roeder, and Eugene Katsevich. “SCEPTRE improves calibration and sensitivity in single-cell CRISPR screen analysis.” Genome biology 22, no. 1 (2021): 1-19.

Mahjani, Behrang, Silvia De Rubeis, Christina Gustavsson Mahjani, Maureen Mulhern, Xinyi Xu, Lambertus Klei, F. Kyle Satterstrom et al. “Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder.” Molecular autism 12, no. 1 (2021): 1-12.

Klei, Lambertus, Lora Lee McClain, Behrang Mahjani, Klea Panayidou, Silvia De Rubeis, Anna-Carin Säll Grahnat, Gun Karlsson et al. “How rare and common risk variation jointly affect liability for autism spectrum disorder.” Molecular autism 12, no. 1 (2021): 1-13.

Yurko, Ronald, Kathryn Roeder, Bernie Devlin, and Max G’Sell. “An approach to gene-based testing accounting for dependence of tests among nearby genes.” Briefings in Bioinformatics 22, no. 6 (2021): bbab329.

Cai, Zhanrui, Jing Lei, and Kathryn Roeder. “A distribution-free independence test for high dimension data.” arXiv preprint arXiv:2110.07652 (2021).

Qiu, Yixuan, Jiebiao Wang, Jing Lei, and Kathryn Roeder. “Identification of cell-type-specific marker genes from co-expression patterns in tissue samples.” Bioinformatics 37, no. 19 (2021): 3228-3234.

Wang, Jiebiao and Roeder, Kathryn and Devlin, Bernie, Bayesian estimation of cell type-specific gene expression with prior derived from single-cell data, Genome Research, gr–268722, 2021.

Katsevich, Eugene and Barry, Timothy and Roeder, Kathryn, Conditional resampling improves calibration and sensitivity in single cell CRISPR screen analysis, bioRxiv, 2020–08, 2021.

Lin, Kevin Z and Lei, Jing and Roeder, Kathryn, Exponential-family embedding with application to cell developmental trajectories for single-cell RNA-seq data, Journal of the American Statistical Association, 1–14, 2021.

Qiu, Yixuan and Wang, Jiebiao and Lei, Jing and Roeder, Kathryn, Identification of cell-type-specific marker genes from co-expression patterns in tissue samples, Bioinformatics, 37(19), 3228–3234, 2021.

Peng, Minshi and Wamsley, Brie and Elkins, Andrew G and Geschwind, Daniel M and Wei, Yuting and Roeder, Kathryn, Cell type hierarchy reconstruction via reconciliation of multi-resolution cluster tree, bioRxiv, 2021.

Peng, Minshi and Li, Yue and Wamsley, Brie and Wei, Yuting and Roeder, Kathryn, Integration and transfer learning of single-cell transcriptomes via cFIT, Proceedings of the National Academy of Sciences, 118(10), 2021.

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