Zobrazeno 1 - 10
of 653
pro vyhledávání: '"Roeder, Kathryn"'
With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-cell-level measurements. However, the individual gene expression levels
Externí odkaz:
http://arxiv.org/abs/2404.09119
Quantitative measurements produced by mass spectrometry proteomics experiments offer a direct way to explore the role of proteins in molecular mechanisms. However, analysis of such data is challenging due to the large proportion of missing values. A
Externí odkaz:
http://arxiv.org/abs/2403.15802
We study several variants of the high-dimensional mean inference problem motivated by modern single-cell genomics data. By taking advantage of low-dimensional and localized signal structures commonly seen in such data, our proposed methods not only h
Externí odkaz:
http://arxiv.org/abs/2403.05679
Tens of thousands of simultaneous hypothesis tests are routinely performed in genomic studies to identify differentially expressed genes. However, due to unmeasured confounders, many standard statistical approaches may be substantially biased. This p
Externí odkaz:
http://arxiv.org/abs/2309.07261
Ensemble methods such as bagging and random forests are ubiquitous in various fields, from finance to genomics. Despite their prevalence, the question of the efficient tuning of ensemble parameters has received relatively little attention. This paper
Externí odkaz:
http://arxiv.org/abs/2302.13511
In genomics studies, the investigation of the gene relationship often brings important biological insights. Currently, the large heterogeneous datasets impose new challenges for statisticians because gene relationships are often local. They change fr
Externí odkaz:
http://arxiv.org/abs/2203.01990
CRISPR genome engineering and single-cell RNA sequencing have accelerated biological discovery. Single-cell CRISPR screens unite these two technologies, linking genetic perturbations in individual cells to changes in gene expression and illuminating
Externí odkaz:
http://arxiv.org/abs/2201.01879
Test of independence is of fundamental importance in modern data analysis, with broad applications in variable selection, graphical models, and causal inference. When the data is high dimensional and the potential dependence signal is sparse, indepen
Externí odkaz:
http://arxiv.org/abs/2110.07652
Autor:
Zhang, Tianyu, Zhou, Geyu, Klei, Lambertus, Liu, Peng, Chouldechova, Alexandra, Zhao, Hongyu, Roeder, Kathryn, G’Sell, Max, Devlin, Bernie
Publikováno v:
In Human Genetics and Genomics Advances 11 April 2024 5(2)
We describe an R package named huge which provides easy-to-use functions for estimating high dimensional undirected graphs from data. This package implements recent results in the literature, including Friedman et al. (2007), Liu et al. (2009, 2012)
Externí odkaz:
http://arxiv.org/abs/2006.14781