lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression

Image credit: bioRxiv

Abstract

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. Current computational tools estimate relative RNA abundances rather than cell type proportions in tissues with varying cell sizes, leading to biased estimates. We present lute, a computational tool to accurately deconvolute cell types with varying sizes. Our software wraps existing deconvolution algorithms in a standardized framework. Using simulated and real datasets, we demonstrate how lute adjusts for differences in cell sizes to improve the accuracy of cell composition. Software is available from https://bioconductor.org/packages/lute.

Publication
bioRxiv
Louise A. Huuki-Myers
Louise A. Huuki-Myers
Research Associate 2020-2022, Staff Scientist I, Data Science 2022-ongoing, PhD Student 2024-ongoing
Leonardo Collado-Torres
Leonardo Collado-Torres
Investigator @ LIBD, Assistant Professor, Department of Biostatistics @ JHBSPH

#rstats @Bioconductor/🧠 genomics @LieberInstitute/@lcgunam @jhubiostat @jtleek @andrewejaffe alumni/@LIBDrstats @CDSBMexico co-founder