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In this article, we study the estimation of high‐dimensional single index models when the response variable is censored. We hybrid the estimation methods for high‐dimensional single‐index models (but without censorship) and univariate nonparametric models with randomly censored responses to estimate the index parameters and the link function and apply the proposed methods to analyze a genomic dataset from a study of diffuse large B‐cell lymphoma. We evaluate the finite sample performance of the proposed procedures via simulation studies and establish large sample theories for the proposed estimators of the index parameter and the nonparametric link function under certain regularity conditions.

Using DNA methylation profiles (n= 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels inHOXLsubclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.