Noah Zaitlen

The paper introduces an orthogonal CRISPR/Cas screen to systematically activate one gene while knocking out another, enabling the identification and directionality of genetic interactions in human cancer cells.

This paper shows that DNA methylation data can capture ancestry information and introduces a method to infer ancestry from methylation data without genetic data.

This paper examines how ancestry-assortative mating affects linkage disequilibrium in admixed populations and shows it can lead to errors in demographic inference.

This study examines how ethnic self-identification and genetic ancestry influence DNA methylation patterns in individuals of Hispanic descent, finding that ancestry explains much of the variation, but environmental factors also play a significant role.

This paper introduces a local joint testing method that improves power in genetic association studies and identifies missing heritability by addressing linkage masking.

This paper introduces a new gene-gene interaction test for trio studies called the trio correlation (TC) test, which outperforms existing methods in power and identifies a bias in previous tests.

This paper introduces LDpred, a method that improves polygenic risk score accuracy by modeling linkage disequilibrium, showing increased R2 values in schizophrenia and multiple sclerosis datasets.

The paper introduces a new mixed model method for case-control studies that improves association power while controlling false positives, showing gains in power on real and simulated data.