Josh Weinstock

Assistant Research Scientist

Johns Hopkins University


I am a research scientist in the Department of Biomedical Engineering at Johns Hopkins University working at the nexus of human genetics, computation, and statistics to discover and characterize disease associated genetic variation. Previously, I was a postdoctoral scholar working jointly with Jonathan Pritchard (Stanford, Genetics) and Alexis Battle (Johns Hopkins, Biomedical Engineering) on using gene regulatory networks to describe the etiology of complex traits. I completed a PhD in the Biostatistics department of the University of Michigan, where I was advised by Goncalo Abecasis. At Michigan, my contributions included analysis of somatic variation called from whole genomes generated by the NHLBI TOPMed consortium.


  • biostatistics
  • statistical genetics
  • statistical computing
  • sports statistics


  • PhD in Biostatistics, 2021

    University of Michigan

  • MS in Biostatistics, 2018

    University of Michigan

  • BA in Mathematics, 2015

    Emory University

Selected Publications

Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease

We mapped the gene regulatory network of key immune disease genes in primary CD4+ T cells using causal inference methods

The genetic determinants of recurrent somatic mutations in 43,693 blood genomes

We discovered thousands of unexpectedly common somatic mutations in blood

Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis

We identified TCL1A as a key mediator of clonal expansion in CHIP clones

LabWAS: Novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks

We performed a GWAS meta-analysis of lab derived phenotypes from the Michigan Genomics Initiative (Umich) and BioVU (Vanderbilt)

Inherited causes of clonal haematopoiesis in 97,691 whole genomes

We discovered the genetic determinants of CHIP in ~97,000 TOPMed whole genomes


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