Identifying interesting relationships between pairs of variables in large data sets is increasingly
important. Here, we present a measure of dependence for two-variable relationships: the …

We introduce an approach to identify disease-relevant tissues and cell types by analyzing
gene expression data together with genome-wide association study (GWAS) summary …

Models for predicting phenotypic outcomes from genotypes have important applications to
understanding genomic function and improving human health. Here, we develop a machine-…

The selective pressures that shape clonal evolution in healthy individuals are largely unknown.
Here we investigate 8,342 mosaic chromosomal alterations, from 50 kb to 249 Mb long, …

Given a high-dimensional data set, we often wish to find the strongest relationships within it.
A common strategy is to evaluate a measure of dependence on every variable pair and …

Haplotype phasing is a fundamental problem in medical and population genetics. Phasing
is generally performed via statistical phasing in a genotyped cohort, an approach that can …

As single-cell datasets grow in sample size, there is a critical need to characterize cell states
that vary across samples and associate with sample attributes, such as clinical phenotypes. …

Recent studies have examined the genetic correlations of single‐nucleotide polymorphism (SNP)
effect sizes across pairs of populations to better understand the genetic architectures …

Biological interpretation of genome-wide association study data frequently involves assessing
whether SNPs linked to a biological process, for example, binding of a transcription factor, …

… The first states roughly that an equitable measure of dependence gives similar scores to
equally noisy relationships of different types [Reshef et al. (2011)]. In this viewpoint, a highly …