Publications: Genomics

· D. Heckerman. Accounting for hidden common causes when inferring cause and effect from observational data. https://arxiv.org/abs/1801.00727, Jan 3, 2018.

· H. Tang, E. Kirkness, C. Lippert, W. Biggs, M. Fabani, E. Guzman, S. Ramakrishnan, V. Lavrenko, B. Kakaradov, C. Hou, B. Hicks, D. Heckerman, F.J. Och, C.T. Caskey, J.C. Venter, A. Telenti. Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes. AJHG, 101, 700-715, Nov 2017 (doi: 10.1016/j.ajhg.2017.09.013).

· C. Kadie, D. Heckerman. Ludicrous Speed Linear Mixed Models for Genome-Wide Association Studies. https://www.biorxiv.org/content/early/2018/01/03/154682.

· D. Heckerman, D. Gurdasani, C. Kadie, C. Pomilla, T. Carstensen, H. Martin, K. Ekoru, R.N. Nsubuga, G. Ssenyomo A. Kamali, P. Kaleebu, C. Widmer, and M.S. Sandhu. Linear mixed model for heritability estimation that explicitly addresses environmental variation. PNAS, 113: 7377–7382, July 2016 (doi: 10.1073/pnas.1510497113).

· C. Lippert and D. Heckerman. Computational and statistical issues in personalized medicine. XRDS 21, 24-27, Summer 2015 (doi:10.1145/2788502).

· O. Weissbrod, C. Lippert, D. Geiger, and D. Heckerman.  Accurate liability estimation improves power in ascertained case-control studies.  Nature Methods, Feb 2015 (doi:10.1038/nmeth.3285).

· C. Widmer, C. Lippert, O. Weissbrod, N. Fusi, C.M. Kadie, R.I. Davidson, J. Listgarten, and D. Heckerman. Further Improvements to Linear Mixed Models for Genome-Wide Association Studies. Scientific Reports 4, 6874, Nov 2014 (doi:10.1038/srep06874).

· C. Lippert, J. Xiang, D. Horta, C. Widmer, C.M. Kadie, D. Heckerman, J. Listgarten. Greater Power and Computational Efficiency for Kernel-Based Association Testing of Sets of Genetic Variants. Bioinformatics 30 , July 2014 (doi: 10.1093/bioinformatics/btu504).

· N. Furlotte, D. Heckerman, and C. Lippert.  Quantifying the uncertainty in heritability.  Journal of Human Genetics 27, March 2014 (doi: 10.1038/jhg.2014.15).

· J. Zou, C. Lippert, D. Heckerman, M. Aryee, and J. Listgarten.  Epigenome-wide association studies without the need for cell-type composition.  Nature Methods 11:309–311, Jan 2014 (doi:10.1038/nmeth.2815).

· I. Bartha, J.Carlson, C. Brumme, P. McLaren, Z. Brumme, M. John, D. Haas, J. Martinez-Picado, J. Dalmau, C. López-Galíndez, C. Casado, A. Rauch, H. Günthard, E. Bernasconi, P. Vernazza, T. Klimkait, S. Yerly, S. O’Brien, J. Listgarten, N. Pfeifer, C. Lippert, N. Fusi, Z. Kutalik, T. Allen, V. Müller, P. Harrigan, D. Heckerman, A. Telenti, and J. Fellay.  A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.  eLife 2013;2:e01123, October 2013 (http://dx.doi.org/10.7554/eLife.01123).

· C. Lippert, G. Quon, E.Y. Kang, C.M. Kadie, J. Listgarten, and D. Heckerman.  The benefits of selecting phenotype-specific variants for applications of mixed models in genomics.  Scientific Reports, 3, May 2013 (doi:10.1038/srep01815).

· J. Listgarten, C. Lippert, E.Y. Kang, J. Xiang, C.M. Kadie, and D. Heckerman.  A powerful and efficient set test for genetic markers that handles confounders.  Bioinformatics, May 2013 (doi: 10.1093/bioinformatics/btt177).

· J. Listgarten, C. Lippert, and D. Heckerman. FaST-LMM-Select for addressing confounding from spatial structure and rare variants.  Nature Genetics, 45: 470-471, April 2013 (doi:10.1038/ng.2620).

· G. Quon, C. Lippert, D. Heckerman, and J. Listgarten.  Patterns of methylation heritability in a genome-wide analysis of four brain regions.  Nucleic Acids Research, March 2013 (doi: 10.1093/nar/gks1449).

· C. Lippert, J. Listgarten, R.I. Davidson, J. Baxter, H. Poon, C.M. Kadie, and  D. Heckerman.  An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data.  Scientific Reports, 3, Jan 2013 (doi:10.1038/srep01099).

· J. Listgarten, C. Lippert, C.M. Kadie, R.I. Davidson, E. Eskin, and D. Heckerman.  Improved linear mixed models for genome-wide association studies.  Nature Methods, 9: 525-526, June 2012 (doi:10.1038/nmeth.2037).

· X. Zhang, W. Cheng, J. Listgarten, C. Kadie, S. Huang, W. Wang, and D. Heckerman.  Learning transcriptional regulatory relationships using sparse graphical models.  PLoS One 7(5): e35762, May 2012 (doi:10.1371/journal.pone.0035762).

· A. Renton, et al.  A Hexanucleotide Repeat Expansion in C9ORF72 Is the Cause of Chromosome 9p21-Linked ALS-FTD.  Neuron 72(2): 257-268, Oct 2011.

· C. Lippert, J. Listgarten, Y. Liu, C.M. Kadie, R.I. Davidson, and D. Heckerman.  FaST linear mixed models for genome-wide association studies.  Nature Methods, 8: 833-835, Oct 2011 (doi:10.1038/nmeth.1681).

· J. Listgarten, C. Kadie, E. Schadt, D. Heckerman.  Correction for hidden confounders in the genetic analysis of gene expression. PNAS, 107 (38): 16465-16470, September 2010 (doi: 10.1073/pnas.1002425107).

· J. Carlson, Z. Brumme, C. Rousseau, C. Brumme, P. Matthews, C. Kadie, J. Mullins, B. Walker, P. Harrigan, P. Goulder, D. Heckerman.  Phylogenetic dependency networks: Inferring patterns of CTL escape and codon covariation in HIV-1 Gag. PLoS Computational Biology, 4(11): e1000225, November 2008.

· H. Kang, N. Zaitlen, C. Wade, A. Kirby, D. Heckerman, M. Daly, and E. Eskin, Efficient Control of Population Structure in Model Organism Association Mapping, Genetics, 178:1709-1723, March, 2008 (doi: 10.1534/genetics.107.080101).

· J. Listgarten, Z. Brumme, C. Kadie, G. Xiaojiang, B. Walker, M. Carrington, P. Goulder, and D. Heckerman.  Statistical resolution of ambiguous HLA typing data.  PLoS Computational Biology, 4(2): e1000016, February, 2008.

· J. Listgarten, N. Frahm, C. Kadie, C. Brander, D. Heckerman.  A statistical framework for modeling HLA-dependent T cell response data, PLoS Computational Biology, 3(10): e188, October 2007.

· D. Heckerman, C. Kadie, and J. Listgarten.  Leveraging information across HLA alleles/supertypes improves epitope prediction. J. of Comp. Bio, 14(6): 736-746, August 2007.  Also appears as MSR-TR-05-127, Microsoft Research, September, 2005.

· J. Carlson, C. Kadie, S. Mallal, and D. Heckerman.  Leveraging hierarchical population structure in discrete association studies. PLoS ONE, 2(7): e591, July 2007.

· T. Bhattacharya, M. Daniels, D. Heckerman, B. Foley, N. Frahm, C. Kadie, J. Carlson, K. Yusim, B. McMahon, B. Gaschen, S. Mallal, J. Mullins, D. Nickle, J. Herbeck, C. Rousseau, G. Learn, T. Miura, C. Brander, B. Walker, B. Korber.  Founder effects in the assessment of HIV polymorphisms and HLA allele associations, Science, 315, 1583-1586, March 16 2007.