Postdoctoral Research Fellow
Department of Biomedical Informatics, Harvard Medical School
Dr. Koch is a postdoctoral researcher in the Department
of Biomedical Informatics at Harvard Medical School. He works on statistical
and theoretical problems in population and evolutionary genetics. His current
research projects include using precise mutation rate estimates in the human
genome to measure natural selection on a fine scale, and the investigation of
selection on human traits using the results of genome-wide association studies.
He has also worked on arabidopsis and wolf genetics, and currently has added
the SARS-CoV-2 virus to this mix.
Dr. Koch obtained my PhD in Ecology and Evolution from the University of Chicago, where he was an NSF GRFP fellow. Before that, he graduated from the University of Texas with a BS in Biology (honors), and a certificate in computational science.
Postdoctoral Research Fellow
Department of Biomedical Informatics, Harvard Medical School
Dr. Koch is a postdoctoral researcher in the Department
of Biomedical Informatics at Harvard Medical School. He works on statistical
and theoretical problems in population and evolutionary genetics. His current
research projects include using precise mutation rate estimates in the human
genome to measure natural selection on a fine scale, and the investigation of
selection on human traits using the results of genome-wide association studies.
He has also worked on arabidopsis and wolf genetics, and currently has added
the SARS-CoV-2 virus to this mix.
Dr. Koch obtained my PhD in Ecology and Evolution from the University of Chicago, where he was an NSF GRFP fellow. Before that, he graduated from the University of Texas with a BS in Biology (honors), and a certificate in computational science.
Journal article
The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC...
Journal article
The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC...
