Postdoctoral Scholar at University of California, San Francisco
Aarhus, Central Denmark Region, Denmark
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Summary
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Senior
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Top School
Nathan Schaefer is a postdoctoral bioinformatician with nine years of experience applying population genomics, statistical methods, and single-cell multi-omic analysis to probe human-specific brain development and disease vulnerability. He develops practical tools—most notably CellBouncer—for demultiplexing, QC, and ambient RNA correction in pooled single-cell experiments, and has implemented fast heuristic algorithms for ancestral recombination graph inference to enable novel population-genomic scans. At UCSF he combines tetraploid inter-species cell lines, Perturb-seq analyses, and evolutionary history to tie regulatory mutations to cellular phenotypes across development. Nathan blends deep computational rigor with an experimental sensibility, prioritizing QC and scalable pipelines that reduce batch effects and make complex pooled designs tractable. He is interested in leveraging neural-network predictors of variant impact and integrating allele-frequency history with single-cell functional genomics to reveal human-specific biology.
10 years of coding experience
11 years of employment as a software developer
Bachelor’s Degree, Biology, Botany, Computer Science certificate, Honors in the Liberal Arts, Bachelor’s Degree, Biology, Botany, Computer Science certificate, Honors in the Liberal Arts at University of Wisconsin-Madison
Tools for pooled single cell sequencing experiments: demultiplex cells, infer doublet rate, assign treatments/sgRNAs, infer ambient RNA from allele matching
Contributions:1 release, 1 PR, 68 pushes in 1 year 7 months
Contributions:1 release, 22 pushes, 1 branch in 1 year 8 months
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