Andrew McDavid, PhD
Ph.D. (2016) University of Washington
University of Rochester
Dept of Biostatistics and Computational Biology
265 Crittenden Boulevard, CU 420630
Rochester, New York 14642-0630
Office: Saunders Research Building 4206
Phone: (585) 275-5983
Fax: (585) 273-1031
Andrew McDavid's Personal Website
I am interested in methods and applications of single cell gene expression assays. There is great hope, for good reason, that measuring expression profiles in single cells will aid in immunological and cancer research, and provide new insight in cellular biology (though it still only provides a cross-sectional sample of cells at various points in their lifespan and cell cycle.) However, the biochemical, computational and statistical challenges are sizable.
I am focusing on the combinations of all three. Through the use of unique molecular identifiers, it may be possible to better understand the biases and sources of variability current protocols introduce. I am writing R software packages to allow easier manipulation of single-cell data sets (which are sometimes almost as "tall" as they are "wide"). I am developing statistical methods that accommodate the bimodality of single cell data, which yield more sensitive and better calibrated tests.
Statistical questions I am currently interested in include:
- Graphical modeling and gene-gene interaction networks
- Clustering and distance measures for zero-inflated data
- Gene-enrichment analysis
- Regularizing vector generalized linear models through empirical Bayes' procedures
- 2nd-order univariate phenomena, such as exceptional stability or heterogeneity of expression (and how this can be identified given differing levels of technical variability).
- Lu DR, McDavid AN, Kongpachith S, Lingampalli N, Glanville J, Ju CH, Gottardo R, Robinson WH. T Cell-Dependent Affinity Maturation and innate Immune Pathways Differentially Drive Autoreactive B Cell Response in Rheumatoid Arthritis. Arthritis Rheumatol. 2018 Nov;70(11):1732-1744. doi:10.1002/art.40578. Epub 2018 Sept 24. PubMed PMID: 29855173; PubMed Central PMCID: PMCID: PMC6203609.
- Grier A, McDavid A, Wang B, Qiu X, Java J, Bandyopadhyay S, Yang H, Holden-Wiltse J, Kessler HA, Gill AL, Huyck H, Falsey AR, Topham DJ, Scheible KM, Caserta MT, Pryhuber GS, Gill SR. Neonatal gut and respiratory microbiota: coordinated development through time and space. Microbiome. 2018 Oct 26;6(1):193. doi: 10.1186/s40168-018-0566-5. PubMed PMID: 30367675; PubMed Central PMCID: PMC6204011.
- McDavid, A., Finak, G., and Gottardo, R. (2016). "The contribution of cell cycle to heterogeneity in single-cell RNA-seq data." Nature Biotechnology 34(6): 591-593.
- Conway, A. B., McDavid, A., Emert, J. M., Kudenchuk, P. J., Stubbs, B. A., Rea, T. D., Yin, L, Olsufka, M., McCoy, A. M., and Sayre, M. R. (2016). "Impact of Building Height and Volume on Cardiac Arrest Response Time." Prehospital Emergency Care 20(2): 212-219.
- Finak, G., McDavid, A., Yajima, M., Deng, J., Gersuk, V., Shalek, A. K., Slichter, C. K., Miller, H. W., McElrath, M. J., and Prlic, M. (2015). "MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data." Genome Biology 16(1):1.
- McDavid, A., Crane, P. K., Newton, K. M., Crosslin, D. R., McCormick, W., Weston, N., Ehrlich, K., Hart, E., Harrison, R., and Kukull, W. A. (2013). "Enhancing the power of genetic association studies through the use of silver standard cases derived from electronic medical records." PLoS ONE 8(6): e63481.
- McDavid, A., Finak, G., Chattopadyay, P. K., Dominguez, M., Lamoreaux, L., Ma, S. S., Roederer, M., and Gottardo, R. (2013). "Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments." Bioinformatics 29(4): 461-467.
- Schick, U. M., McDavid, A., Crane, P. K., Weston, N., Ehrlich, K., Newton, K. M., Wallace, R., Bookman, E., Harrison, T., and Aragaki, A. (2013). "Confirmation of the reported association of clonal chromosomal mosaicism with an increased risk of incident hematologic cancer." PLoS ONE 8(3): e59823.
- Finak, G., McDavid, A., Chattopadhyay, P., Dominguez, M., De Rosa, S., Roederer, M., and Gottardo, R. (2013). "Mixture models for single-cell assays with applications to vaccine studies." Biostatistics: kxt024.