Accounting for unobserved covariates with varying degrees of estimability in high-dimensional biological data

DOI10.1093/biomet/asz037zbMath1435.62396arXiv1801.00865OpenAlexW2973427420WikidataQ91386939 ScholiaQ91386939MaRDI QIDQ5212908

Chris McKennan, Dan L. Nicolae

Publication date: 30 January 2020

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1801.00865

zbMATH Keywords

confoundingunobserved covariatesbatch effectunwanted variationcell-type heterogeneityhigh-dimensional factor analysis

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Protein sequences, DNA sequences (92D20) Statistical aspects of big data and data science (62R07)

Related Items (4)

Estimating and Accounting for Unobserved Covariates in High-Dimensional Correlated Data ⋮ Adaptive estimation in multivariate response regression with hidden variables ⋮ Estimation and inference in metabolomics with nonrandom missing data and latent factors ⋮ Unifying and Generalizing Methods for Removing Unwanted Variation Based on Negative Controls

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