John “Jack” Kamm, Ph.D.

I am a statistician and bioinformaticist. My original training was in population genetics; I was advised by Yun Song for my Ph.D. and Richard Durbin for my postdoc. Since then, I have worked in different areas of statistical genetics including metagenomics, pathogen phylogenetics, and single cell RNAseq.

Outside of research, I contribute to the Emacs packages org-mode and org-caldav, and maintain some packages on the Arch User Repository.

Selected publications

• Fine-scale cellular deconvolution via generalized maximum entropy on canonical correlation features. Kamm, J. BioRxiv (2024). {Preprint} {Code}

• Upper airway gene expression differentiates COVID-19 from other acute respiratory illnesses and reveals suppression of innate immune responses by SARS-CoV-2. Mick, E.*, Kamm, J.*, Pisco, A., …, Kistler, A., Langelier, C. Nature Communications (2020). {Journal} {Preprint} {Code}

• Efficiently inferring the demographic history of many populations with allele count data. Kamm, J., Terhorst, J., Durbin, R., and Song, Y.S. Journal of the American Statistical Association (2019). {Journal} {Preprint} {Software: momi2}

• The first horse herders and the impact of early Bronze Age steppe expansions into Asia. de Barros Damgaard, P.*, Martiniano, R.*, Kamm, J.*, Moreno-Mayar, J. V.*, … Durbin, R., and Willerslev, E. Science (2018). {Journal}

• Robust and scalable inference of population history from hundreds of unphased whole genomes. Terhorst, J., Kamm, J.A., and Song, Y.S. Nature Genetics, Vol. 49 (2017) 303-309. {Journal} {Software: SMC++}

• The site frequency spectrum for general coalescents. Spence, J.*, Kamm, J.A.*, and Song, Y.S.
  Genetics, Vol. 202 No. 4 (2016) 1549-1561. {Journal} {Preprint}