Statistical Inference of Cell-type Proportions Estimated from Bulk Expression Data.

ABSTRACT: There is a growing interest in cell-type-specific analysis from bulk samples with a mixture of different cell types. A critical first step in such analyses is the accurate estimation of cell-type proportions in a bulk sample. Although many methods have been proposed recently, quantifying the uncertainties associated with the estimated cell-type proportions has not been well studied. Lack of consideration of these uncertainties can lead to missed or false findings in downstream analyses. In this article, we introduce a flexible statistical deconvolution framework that allows a general and subject-specific covariance of bulk gene expressions. Under this framework, we propose a decorrelated constrained least squares method called DECALS that estimates cell-type proportions as well as the samp

SUBMITTER: Cai B 

PROVIDER: S-EPMC12002418 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature