Keith Crandall

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Bio

Keith A. Crandall, PhD is the founding Director of the Computational Biology Institute at George Washington University. Professor Crandall studies the computational biology, population genetics, and bioinformatics of a variety of organisms, from crustaceans to agents of infectious diseases. His lab also focuses on the development and testing of data analytic approaches, especially for Omics and clinical data. He applies these methods and others to the study of the evolution of infectious diseases with particular focus on microbiome studies. Professor Crandall has published over 300 peer reviewed publications, as well as three books (The Evolution of HIV, Algorithms in Bioinformatics, and Decapod Crustacean Phylogenetics). Dr. Crandall’s research has been funded by both the National Science Foundation and the National Institutes of Health as well as from a variety of other agencies, including American Foundation for AIDS Research, National Geographic, US Forest Service, Pharmaceutical Research Manufacturer’s of America Foundation, Alfred P. Sloan Foundation, etc. He has been a Fulbright Visiting Scholar to Oxford University and an Allen Wilson Centre for Molecular Ecology and Evolution Sabbatical Fellowship at the Bioinformatics Institute at the University of Auckland. Professor Crandall has received a number of awards for research and teaching, including an Alfred P. Sloan Foundation Postdoctoral Fellowship in Molecular Evolution at the University of Texas, the American Naturalist Society Young Investigator Award, an NSF CAREER Award, a PhRMA Foundation Faculty Development Award in Bioinformatics, an NIH James A. Shannon Directors Award, ISI Highly Cited Designation, Honors Professor of the Year award at Brigham Young University, and the Edward O. Wilson Naturalist Award. He was also recently elected a Fellow in the American Association for the Advancement of Science (AAAS) and the Linnean Society of London. Professor Crandall earned his BA degree from Kalamazoo College in Biology and Mathematics, an MA degree from Washington University in Statistics, and a PhD from Washington University in Biology and Biomedical Sciences. He also served as a Peace Corps Volunteer in Puyo, Ecuador.

Expertise

Expertise:

Infectious Disease

HIV/AIDS

Biostatistics

Epidemiology

Education:

BA Kalamazoo College, 1987 (Mathematics and Biology)
MA Washington University in St. Louis, 1993 (Statistics)
PhD Washington University School of Medicine, 1993 (Biology & Biomedical Sciences)

Teaching:

PUBH 3201 - Introduction to Bioinformatics

HSML 6294 - Research Analytics

Bioinformatics Minor Director

Institutes and Centers:

Computational Biology Institute

DC CFAR

Clinical and Translational Science Institute - CN

Data Science Institute

GW Cancer Center

Research

Research:

My research program has three main aspects. The first and central component is work on the development and testing through computer simulation of methods for the analysis of DNA sequence data. We have developed methods for estimating gene genealogies, detecting recombination, detecting selection, characterizing microbiome components, and measuring diversity and demographic events in the history of a population. We develop software to implement many of these methods and then develop software to test our methods and many others by comparison through computer simulation. Through comparison and tests of robustness to assumption violations, we can gain great insights into why particular methods perform well or poorly and then are in a good position to redevelop improved methodology. In fact, we are currently embarking on the development of a comprehensive simulation software package that allows one, for the first time, to examine the impact of a host of population genetic phenomena at the same time (e.g., migration, mutation, recombination, selection, fluctuating population sizes, tracking geographic locations of alleles in a population, multiple locus populations, etc.). Through such studies, we gain a better understanding of the methodology we use to infer evolutionary and population demographic histories and associated parameter estimates when we apply them to empirical data. Furthermore, such studies provide valuable insights into the development of new and improved theory and methodology for inference from DNA sequence data.

The remaining two aspects of my research program deal with applications of the above methodologies in two fairly distinct arenas. The first is in molecular ecology, conservation biology, and systematics research. We have applied the methods developed and tested in our lab (and many others) to examine the populations genetics, historical demography, and molecular ecology of various species of freshwater crayfish. We have also examined the molecular systematics of a variety of organisms, from the origin of dogs to the origin of freshwater crayfishes. You will see from my CV that the systematic studies are typically collaborative studies. I firmly believe in collaboration, especially in systematic studies that require both organismal (including morphological and ecological) expertise and molecular (including phylogenetic analysis) expertise. We the freshwater crayfishes, we typically are the morphological and taxonomic experts as well. However, with all the other organismal groups, we develop (often international) teams of expertise to tackle outstanding questions in systematic biology. We then apply our results to a diversity of biogeographic and conservation biology questions. These typically lead naturally into broader issues relating to conservation biology such as diagnosing species and the relative importance of different sources of information regarding conservation priorities and conservation status such as ecological data versus genetic data.

The second focus of my empirical research is in the area of the evolution of infectious diseases. Here we focus on microbiome diversity (functional and taxonomic) and how that relates to organismal health. We also develop methods and implement such approaches to track population dynamics of infectious diseases such as HIV, HCV, etc. We are involved in all phases of this work from the molecular approaches to the statistical models to the computational implementation.

The research outlined in these three main areas in my lab has enjoyed a diversity of funding from the National Institutes of Health, the National Science Foundation, and private agencies such as the Alfred P. Sloan Foundation and the Pharmaceutical Manufacturers of America. My research program is moving evermore into the genomics and bioinformatics arena and applying these insights into conservation management, human health, and biomedical applications.

Publications

Publications:

For a complete publication list, please visit Dr. Crandall's GoogleScholar page.

Posada, D., and K.A. Crandall. 2021. Felsenstein Phylogenetic Likelihood. Journal of Molecular Evolution https://doi.org/10.1007/s00239-020-09982-w.

Bendall, M.L., K.M. Gibson, M.C. Steiner, U. Retina, M. Pérez-Losada, and K.A. Crandall. 2021. HAPHPIPE: Haplotype reconstruction and phylodynamics for deep sequencing of intra-host viral populations. Molecular Biology and Evolution https://doi.org/10.1093/molbev/msaa315

Alekseyenko, A., B. Hamidi, K.A. Crandall, J. Powers, S.L. Carroll, J.S. Obeid, and L.A. Lenert. 2021. Each patient is a research biorepository: Informatics-enabled reuse of surplus clinical specimens via the Living BioBank. Journal of the American Medical Informatics Association 28(1):138-143 https://doi.org/10.1093/jamia/ocaa236

Kolbe, A.R., M.L. Bendall, A.T. Pearson, D. Paul, D.F. Nixon, M. Pérez-Losada, and K.A. Crandall. 2020. Human endogenous retrovirus expression is associated with head and neck cancer and differential survival. Viruses 12(9):956. https://doi.org/10.3390/v12090956

Steiner, M.C., K.M. Gibson, and K.A. Crandall. 2020. Drug resistance prediction using deep learning techniques on HIV-1 sequence data. Viruses 12(5):560. https://doi.org/10.3390/v1205056

Mavian, C., S.K. Pond, S. Marini, B.R. Magalis, A-M. Vandamme, S. Dellicour, S.V. Scarpino, C. Houldcroft, J. Villabona-Arenas, T.K. Paisie, N.S. Trovão, C. Boucher, Y. Zhang, S.H. Scheuermann, O. Gascuel, T.T. Lam, M.A. Suchard, A. Abecasis, E. Wilkinson, T. de Oliveira, A.I. Bento, H.A. Schmidt, D. Martin, J. Hadfield, N. Faria, N.D. Grubaugh, R.A. Neher, G. Baele, P. Lemey, T. Stadler, J. Albert, K.A. Crandall, T. Leitner, A. Stamatakis, M. Prosperi, and M. Salemi. 2020. Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-CoV-2 infections unreliable. Proceedings of the National Academy of Sciences, USA. https://doi.org/10.1073/pnas.2007295117

Gibson, K.M., K. Jair, A.D. Castel, M.L. Bendall, B. Wilbourn, J.A. Jordan, K.A. Crandall, M. Pérez-Losada, & the DC Cohort. 2020. A cross-sectional study to characterize local HIV-1 dynamics in Washington, DC using next-generation sequencing. Scientific Reports 1989 (2020). https://doi.org/10.1038/s41598-020-58410-y

Xavier, JB, VB Young, J Skufca, F Ginty, T. Testerman, AT Pearson, P Macklin, A Mitchell, I Shumulevich, L Xie, JG Caporaso, KA Crandall, NL Simone, F. Godoy-Vitorino, TJ Griffin, KL Whiteson, HH Gustafson, DJ Slade, TM Schmidt, MRS Walther-Antonio, T Korem, B-J Webb-Robertson, MP Styczynski, WE Johnson, C Jobin, JM Ridlon, AY Koh, M Yu, L Kelly, JA Wargo. 2020. The Cancer Microbiome: Distinguishing direct and indirect effects requires a systemic view. Trends in Cancer 6(3):192-204. https://doi.org/10.1016/j.trecan.2020.01.004

Spurr, L, N Alomran, P Bousounis, D. Reece-Stremtan, NM Prashant, H. Liu, P Slowinski, J Li, Q Zhang, J Sein, G Asher, KA Crandall, K Tsaneva-Atanasova, and A Horvath. 2019. ReQTL: Identifying correlations between expressed SNVs and gene expression using RNA-sequencing data. Bioinformatics 36(5):1351-1359. https://doi.org/10.1093/bioinformatics/btz750

Iñiguez, LP, M de Mulder Rougvie, N Stearrett, RB Jones, CE Ormsby, G Reyes-Terán, KA Crandall, DF Nixon, and ML Bendall. 2019. Potential sources of error in the transcriptomic analyses of human endogenous retroviruses in SLE. Proceedings of the National Academy of Sciences, USA 116(43):21350-21351. https://doi.org/10.1073/pnas.1907705116

Bendall, M.L., M. de Mulder, A. Lecanda-Sánchez, M. Pérez-Losada, M.A, Ostriowski, R.B. Jones, L.C.F. Mulder, G. Reyes-Terán, K.A. Crandall, C.E. Ormsby, and D.F. Nixon. 2019. TELESCOPE: Characterization of the retrotranscriptome by accurate estimation of transposable element expression. PLoS Computational Biology 15(9):e1006453 https://doi.org/10.1371/journal.pcbi.1006453

Hourigan, S.K., M. Ahn, K. Gibson, M. Pérez-Losada, G. Felix, M. Weidner, I. Leibowitz, J.E. Niederhuber, C.L. Sears, K.A. Crandall, and M. Oliva-Hemker. 2019. Fecal transplant in children with Clostridioides difficile gives sustained reduction in antimicrobial resistance and pathogenic burden. Open Forum Infectious Diseases https://doi.org/10.1093/ofid/ofz379

King, C.H., H. Desai, A.C. Sylvetsky, J. LoTempio, S. Ayanyan, J. Carrie, K.A. Crandall, B.C. Fochtman, L. Gasparayan, N. Gulzar, P. Howell, N. Issa, K. Krampis, L. Mishra, H. Morizono, J.R. Pisegna, S. Rao, Y. Ren, V. Simonyan, K. Smith, S. VedBrat, M.D. Yao, and R. Mazumder. 2019. Baseline human gut microbiota profile in healthy people and standard reporting template. PLoS One 14(9), e0206484 https://doi.org/10.1371/journal.pone.0206484

Gibson, K.M., B.N. Nguyen, L.M. Neumann, M. Miller, P. Buss, S. Daniels, M.J. Ahn, K.A. Crandall, and B. Pukazhenthi. 2019. Gut microbiome differences between wild and captive black rhinoceros – implications for rhino health. Scientific Reports 9:7570. https://www.nature.com/articles/s41598-019-43875-3

Kegerreis, B., A. Labonte, C. Zeng, N. Stearrett, K.A. Crandall, A. Grammer, and P. Lipsky. Accepted. Machine learning approaches to predict disease activity and treatment in lupus. Scientific Reports 9(1):9617. https://www.nature.com/articles/s41598-019-45989-0

Gibson KM, Steiner MC, Kassaye S, Maldarelli F, Grossman Z, Pérez-Losada M, Crandall KA. 2019. A 28-Year History of HIV-1 Drug Resistance and Transmission in Washington, DC. Frontiers in Microbiology 10:369. doi: 10.3389/fmicb.2019.00369

Stern, DB and KA Crandall. 2018. The evolution of gene expression underlying vision loss in cave animals. Molecular Biology and Evolution 35(8):2005-2014. doi:10.1093/molbev/msy106.

Pérez-Losada, M., K.J. Authelet, C.E. Hoptay, C. Kwak, K.A. Crandall, and R.J. Freishtat. 2018. Pedatric asthma comprises different phenotypic clusters with unique nasopharyngeal microbiotas. Microbiome 6(1):179. https://doi.org/10.1186/s40168-018-0564-7.

Hahn, A, ML Bendall, K Gibson, H Chaney, I Sami, GF Perez, AC Koumbourlis, TA McCaffrey, RJ Freishtat, and KA Crandall. 2018. Benchmark evaluation of true single molecular sequencing to determine cystic fibrosis airway microbiome diversity. Frontiers in Microbiology 9:1069. doi: 10.3389/fmicb.2018.01069.

Houzet, L, M Pérez-Losada, G Matusali, C Deleage, N Dereuddre-Bosquet, AP Satie, F Aubry, E Becker, B Jégou, R Le Grand, BF Keele, KA Crandall, and N Dejucq-Rainsford. 2018. Semen in SIV chronically-infected cynomolgus macaques is dominated by viruses originated from multiple genital organs. Journal of Virology 92:e00133-18. https://doi.org/10.1128/JVI.00133-18.

Stern, DB and KA Crandall. 2018. Phototransduction gene expression and evolution in cave and surface crayfish. Integrative and Comparative Biology 58(3):398-410. doi:10.1093/icb/icy029.

Lewin, H.A., G. Robinson, W.J. Kress, W. Baker, J. Coddington, K. Crandall, R. Durbin, S. Edwards, F. Forest, T. Gilbert, M. Goldstein, I. Grigoriev, K. Hackett, D. Haussler, E. Jarvis, W. Johnson, A. Patrinos, S. Richards, J.C. Castilla Rubio, M.A. van Sluys, P. Soltis, X. Xu, H. Yang, and G. Zhang. 2018. The Earth BioGenome Project: Sequencing Life for the Future of Life. Proceedings of the National Academy of Sciences 115(17):4325-4333. Doi/10.1073/pnas.1720115115

Pérez-Losada M, Castel AD, Lewis B, Kharfen M, Cartwright CP, Huang B, Maxwell T, Greenberg AE, Crandall KA. 2017. Characterization of HIV diversity, phylodynamics and drug resistance in Washington, DC. PLoS ONE 12(9): e0185644. https://doi.org/10.1371/journal.pone.0185644

Restrepo, P., M. Movassagh, N. Alomran, C. Miller, M. Li, C. Trenkov, Y. Manchev, S. Bahl, S. Warnken, L. Spurr, T. Apanasovich, K. Crandall, N. Edwards, and A. Horvath. 2017. Overexpressed somatic alleles are enriched in functional elements in Breast Cancer. Scientific Reports 7:8287. doi:10.1038/s41598-017-08416-w

Pérez-Losada M, Crandall K.A., Freishtat R.J. 2016. Two sampling methods yield distinct microbial signatures in the nasopharynges of asthmatic children. Microbiome 4:25 DOI: 10.1186/s40168-016-0170-5

Hilton SK, Castro-Nallar E, Perez-Losada M, Toma I, McCaffrey TA, Hoffman EP, Siegel MO, Simon GL, Johnson WE, Crandall KA. 2016. Metataxonomic and Metagenomic Approaches vs. Culture-Based Techniques for Clinical Pathology. Frontiers in Microbiology, 7:484.

Hinchliff, C., S.A. Smith, J.F. Allman, J.G. Burleigh, R. Chaudhary, L.M. Coghill, K.A. Crandall, J. Deng, B.T. Drew, R. Gazis, K. Gude, D.S. Hibbett, L.A. Katz, H.D. Laughinghouse, E.J. McTavish, P.E. Midford, C.L. Owen, R. Ree, J.A. Rees, D.E. Soltis, T. Wiliams, and K.A. Cranston. 2015. Synthesis of phylogeny and taxonomy into a comprehensive tree of life. Proceedings of the National Academy of Sciences, USA 112(41):12764-12769. doi: 10.1073/pnas.1423041112

Castro-Nallar, E., Y. Shen, R. J. Freishtat, M. Pérez-Losada, S. Manimaran, G. Liu, A. Spira, W. E. Johnson, K. A. Crandall. 2015. Integrating metagenomics and host gene expression to characterize asthma-associated microbial communities. BMC Medical Genomics 8:50, DOI 10.1186/s12920-015-0121-1.

Hong, C., S. Manimaran, Y. Shen, J.F. Perez-Rogers, A.L. Byrd, E. Castro-Nallar, K.A. Crandall, and W.E. Johnson. 2014. PathoScope 2.0: A complete computational framework for strain identification in environmental or clinical sequencing samples. Microbiome 2:33.

Faison, W.J., A. Rostovtsev, E. Castro-Nallar, K.A. Crandall, K. Chumakov, V. Simonyan, and R. Mazumder. 2014. Whole genome single-nucleotide variation profile-based phylogenetic tree building methods for analysis of viral, bacterial, and human genomes. Genomics 104(1):1-7

Byrd, A.L., J.F. Perez-Rogers, C. Hong, S. Manimaran, E. Castro-Nallar, I. Toma, T. McCaffrey, S. Siegel, G. Benson, K.A. Crandall, and W.E. Johnson. 2014. Clinical PathoScope: Rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data. BMC Bioinformatics 15:262.

Web 2019 Update - CSS

Keith A.

Crandall

Professor, Director of Computational Biology Institute, Director of Genomics Core

Keith Crandall

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