Kathryn Roeder

Google Scholar

Selected and Recent Publications

    Zhu, L, Lei, J, and Roeder, K. A unified statistical framework for rna sequence data from individual cells and tissue. arXiv:1609.08028, 2016.

    Zhu, L, Lei, J, Devlin, B, and Roeder, K. Testing high dimensional covariance matrices, with application to detecting schizophrenia risk genes. arXiv:1606.00252, 2016.

    Fromer, M. et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci, 19:1442–1453, 2016.

    Bodea CA, Ripke S, Daly, MJ, Devlin, B, and Roeder K. A method to exploit the structure of genetic ancestry space to enhance case-control studies. Am J Hum Genet, 98:857–868, 2016.

    Liu, L, Lei, J, and Roeder, K. Network assisted analysis to reveal the genetic basis of autism. Ann Appl Stat, 9:1571–1600, 2015.

    Sanders, S.J. et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron, 87(6):1215–33, Sep 2015.

    Cotney, J. et al. The autism-associated chromatin modifier chd8 regulates other autism risk genes during human neurodevelopment. Nat Commun, 6:6404, 2015.

    De Rubeis, S. et al. Synaptic, transciptional and chromatin genes disrupted in autism. Nature, Oct. 2014.

    Samocha, K. et al. A framework for the interpretation of de novo mutation in human disease. Nat Genet, 46(9):944-50, Sep 2014.

    Liu, L. et al. Dawn: A framework to identify autism genes and subnetworks using gene expression and genetics. Mol Autism, 5:22, 2014.

    Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat Genet, 46(8):881-5, Aug 2014.

    Cicek, A.E. et al. Mira mutual information based reporter algorithm. Bioinformatics, 15:175--184, 2014.

    Blumenthal, I. et al. Transcriptional consequences of 16p11.2 deletion and duplication in mouse coretex and multiplex autism families. Am J Hum Genet, 94:870--883, 2014.

    Zhao, T., Roeder, K. and Liu, H. Positive semidefinite rank-based correlation matrix estimation with application to semiparametric graph estimation. Journal of Computational and Graphical Statistics, (DOI: 10.1080/10618600.2013.858633), 2013.

    Willsey, A.J. et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell, 155(5):997--1007, Nov 2013.

    Schafer, C.M. et al. Whole exome sequencing reveals minimal differences between cell line and whole blood derived dna. Genomics, Jun 2013.

    Ringquist, S., Bellone, G., Lu, Y., Roeder, K., and Trucco, M. Clustering and alignment of polymorphic sequences for hla-drb1 genotyping. PLoS One, 8(3):e59835, 2013.

    Liu, L. et al. Analysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls. PLoS Genet, 9(4):e1003443, Apr 2013.

    Lim, E.T. et al. Rare complete knockouts in humans: population distribution and significant role in autism spectrum disorders. Neuron, 77(2):235--42, Jan 2013.

    He, X and Roeder, K. Integrated model of de novo and inherited genetic variants yields greater power to identify risk genes. PLoS Genet. (in press), 2013.

    Crossett, A., Lee, L., Klei, B., Devlin, B. and Roeder, K. Refining genetically inferred relationships using treelet covariance smoothing. Annals of Applied Statistics, 7:669-690, 2013.

    Zhao, T., Roeder, K., and Liu, H. Smooth-projected neighborhood pursuit for high-dimensional nonparanormal graph estimation. In Bartlett, P., Pereira, F.C.N., Burges, C.J.C., Bottou, L., and Weinberger, K.Q., editors, Advances in Neural Information Processing Systems 25, pages 162--170. 2012.

    Klei, L. et al. Common genetic variants, acting additively, are a major source of risk for autism. Mol Autism, 3(1):9, Oct 2012.

    Zhao, T., Roeder, K., and Liu, H. High-dimensional nonparanormal graph estimation via smooth-projected neighborhood pursuit. In review, 2012.

    Zhao, T., Liu, H. Roeder, K., Lafferty, J., and Wasserman, L. The HUGE package for high-dimensional undirected graph estimation in R. Journal of Machine Learning Research, 13(Apr):1059-1062, 2012.

    Mechanic, L. E. et al. Next generation analytic tools for large scale genetic epidemiology studies of complex diseases. Genet. Epidemiol., 36(1):22-35, Jan. 2012.

    Liu, Li, Liu, Han, and Roeder, Kathryn. Discrepancy pursuit: A nonparametric framework for high dimensional variable selection. JASA (submitted), 2012.

    Sanders, S.J. et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature, 485(7397):237-241, May 2012.

    Neale, B.M. et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature, 485(7397): 242-245, 2012.

    Achkar, J-P. et al. Amino acid position 11 of HLA-DRB1 is a major determinant of chromosome 6p association with ulcerative colitis. Genes Immmun, 13(3):245-252, Apr. 2012.

    Sanders, S. J. et al. Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism. Neuron, 70:863–885, Jun 2011.

    Percival, D., Roeder, K., Rosenfeld, R., and Wasserman, L. Structured, sparse regression with application to HIV drug resistance. Ann Appl Stat, 5:628–644, Jun 2011.

    Neale, B. M. et al. Testing for an unusual distribution of rare variants. PLoS Genet., 7:e1001322, Mar 2011.

    Melhem, N. et al. Copy number variants for schizophrenia and related psychotic disorders in Oceanic Palau: risk and transmission in extended pedigrees. Biol. Psychiatry, 70:1115–1121, Dec 2011.

    Devlin, B., Melhem, N., and Roeder, K. Do common variants play a role in risk for autism? Evidence and theoretical musings. Brain Res., 1380:78–84, Mar 2011.

    Chu, S. H. et al. TOMM40 poly-T repeat lengths, age of onset and psychosis risk in Alzheimer disease. Neurobiol. Aging, 32:1–9, Dec 2011.

    Achkar, J. P. et al. Amino acid position 11 of HLA-DRB1 is a major determinant of chromosome 6p association with ulcerative colitis. Genes Immun, Dec 2011.

    Liu H, Roeder K and Wasserman L (2010) Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models

    Wu, J., Devlin, B., Ringquist, S., Trucco, M., and Roeder, K. Screen and clean: a tool for identifying interactions in genome-wide association studies. Genet. Epidemiol., 34:275–285, Apr 2010.

    Pinto, D. et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature, 466:368–372, Jul 2010.

    McGovern, D. P. et al. Genome-wide association identities multiple ulcerative colitis susceptibility loci. Nat. Genet., 42:332–337, Apr 2010.

    Lee, A. B., Luca, D., and Roeder, K. A spectral graph approach to discovering genetic ancestry. Ann Appl Stat, 4:179–202, 2010.

    Lee, A. B., Luca, D., Klei, L., Devlin, B., and Roeder, K. Discovering genetic ancestry using spectral graph theory. Genet. Epidemiol., 34:51–59, Jan 2010.

    Devlin, B., Melhem, N., and Roeder, K. Do common variants play a role in risk for autism? evidence and theoretical musings. Brain Res., Nov 2010.

    Crossett, A. et al. Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies. Stat Med, 29:2932–2945, Dec 2010.

    Anney, R. et al. A genome-wide scan for common alleles affecting risk for autism. Hum. Mol. Genet., 19:4072–4082, Oct 2010.

    Wasserman, L. and Roeder, K. High dimensional variable selection. Ann Stat, 37:2178–2201, Jan 2009.

    Silverberg, M. S. et al. Ulcerative colitis-risk loci on chromosomes 1p36 and 12q15 found by genome-wide association study. Nat. Genet., 41:216–220, Feb 2009.

    Roeder, K. and Wasserman, L. Genome-Wide Significance Levels and Weighted Hypothesis Testing. Stat Sci, 24:398–413, Nov 2009.

    Roeder, K. and Luca, D. Searching for disease susceptibility variants in structured populations. Genomics, 93:1–4, Jan 2009.

    Luca, D. et al. On the use of general control samples for genome-wide association studies: genetic matching highlights causal variants. Am. J. Hum. Genet., 82:453–463, Feb 2008.

    Klei, L., Luca, D., Devlin, B., and Roeder, K. Pleiotropy and principal components of heritability combine to increase power for association analysis. Genet. Epidemiol., 32:9–19, Jan 2008.

    Roeder, K., Devlin, B., and Wasserman, L. Improving power in genome-wide association studies: weights tip the scale. Genet. Epidemiol., 31:741–747, Nov 2007.

    Klei, L. and Roeder, K. Testing for association based on excess allele sharing in a sample of related cases and controls. Hum. Genet., 121:549–557, Jun 2007.

    Devlin, B. et al. Genetic liability to schizophrenia in Oceanic Palau: a search in the affected and maternal generation. Hum. Genet., 121:675–684, Jul 2007.

    Roeder, K., Bacanu, S. A., Wasserman, L., and Devlin, B. Using linkage genome scans to improve power of association in genome scans. Am. J. Hum. Genet., 78:243–252, Feb 2006.

    Genovese, C., Roeder, K., and Wasserman, L. False discovery control with p-value weighting. Biometrika, 93:509–524, 2006.

    Roeder, K., Bacanu, S. A., Sonpar, V., Zhang, X., and Devlin, B. Analysis of single-locus tests to detect gene/disease associations. Genet. Epidemiol., 28:207–219, Apr 2005.

    Rinaldo, A. et al. Characterization of multilocus linkage disequilibrium. Genet. Epidemiol., 28:193–206, Apr 2005.

    Devlin, B., Bacanu, S. A., and Roeder, K. Genomic Control to the extreme. Nat. Genet., 36:1129–1130, Nov 2004.

    Tzeng, J. Y., Devlin, B., Wasserman, L., and Roeder, K. On the identification of disease mutations by the analysis of haplotype similarity and goodness of fit. Am. J. Hum. Genet., 72:891–902, Apr 2003.

    Tzeng, J. Y., Byerley, W., Devlin, B., Roeder, K., and Wasserman, L. Outlier detection and false discovery rates for whole-genome dna matching. J. Amer. Statist. Assoc., 98:236–247, 2003.

    Seltman, H., Roeder, K., and Devlin, B. Evolutionary-based association analysis using haplotype data. Genet. Epidemiol., 25:48–58, Jul 2003.

    Devlin, B., Roeder, K., and Wasserman, L. False discovery or missed discovery? Heredity (Edinb), 91:537–538, Dec 2003.

    Devlin, B., Roeder, K., and Wasserman, L. Analysis of multilocus models of association. Genet. Epidemiol., 25:36–47, Jul 2003.

    Devlin, B., Jones, B. L., Bacanu, S. A., and Roeder, K. Mixture models for linkage analysis of affected sibling pairs and covariates. Genet. Epidemiol., 22:52–65, Jan 2002.

    Devlin, B., Jones, B. L., Bacanu, S. A., and Roeder, K. Mixture and linear models for linkage analysis with covariates. Genetic Epidemiology, 23:449–455, 2002.

    Bacanu, S. A., Devlin, B., and Roeder, K. Association studies for quantitative traits in structured populations. Genet. Epidemiol., 22:78–93, Jan 2002.

    Seltman, H., Roeder, K., and Devlin, B. Transmission/disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes. Am. J. Hum. Genet., 68:1250–1263, May 2001. https://acis.as.cmu.edu:9903/isqlplus

    Lockwood, J. R., Roeder, K., and Devlin, B. A Bayesian hierarchical model for allele frequencies. Genet. Epidemiol., 20:17–33, Jan 2001.

    Jones, B., Nagin, D., and Roeder, K. A SAS procedure based on mixture model for estimating developmental trajectories. Sociological Methods and Research, 29(3):374–393, 2001.

    Devlin, B., Roeder, K., and Wasserman, L. Genomic control, a new approach to genetic-based association studies. Theor Popul Biol, 60:155–166, Nov 2001.

    Devlin, B., Roeder, K., and Bacanu, S. A. Unbiased methods for population-based association studies. Genet. Epidemiol., 21:273–284, Dec 2001.

    Bacanu, S. A., Devlin, B., and Roeder, K. The power of genomic control. Am. J. Hum. Genet., 66:1933–1944, Jun 2000.

    Devlin, B. and Roeder, K. Genomic control for association studies. Biometrics, 55:997–1004, Dec 1999.

    Devlin, B., Daniels, M., and Roeder, K. The heritability of IQ. Nature, 388:468–471, Jul 1997.

    Roeder, K., Carroll, R. J., and Lindsay, B.G. A nonparametric maximum likelihood approach to case-control studies with errors in covariables. J. Amer. Statist. Assoc., 91:722–732, 1996.

    Roeder, K. DNA Fingerprinting: A review of the controversy (with discussion). Statistical Science, 9:222–278, 1994.

    Devlin, B., Risch, N., and Roeder, K. Statistical evaluation of DNA Fingerprinting: a critique of the NRC's report. Science, 259:748–749, 1993.

    Devlin, B., Risch, N., and Roeder, K. NRC report on DNA typing. Science, 260:1057–1059, May 1993.

    Devlin, B., Risch, N., and Roeder, K. Response. Science, 253:1039–1041, Aug 1991.

    Roeder, K. Density estimation with confidence sets exemplified by superclusters and voids in the galaxies. J. Amer. Statist. Assoc., 85:616–624, 1990.

    Devlin, B., Risch, N., and Roeder, K. No excess of homozygosity at loci used for DNA fingerprinting. Science, 249:1416–1420, Sep 1990.

Professor of Statistics
Carnegie Mellon University
Department of Statistics
Baker Hall 228B
Pittsburgh, PA 15213
Contact: kathryn.roeder (gmail)
Phone: (412) 268-2513
Fax: (412) 268-7828