NITUMID: Nonnegative matrix factorization-based Immune-TUmor MIcroenvironment Deconvolution.

ABSTRACT:

Motivation

A number of computational methods have been proposed recently to profile tumor microenvironment (TME) from bulk RNA data, and they have proved useful for understanding microenvironment differences among therapeutic response groups. However, these methods are not able to account for tumor proportion nor variable mRNA levels across cell types.

Results

In this article, we propose a Nonnegative Matrix Factorization-based Immune-TUmor MIcroenvironment Deconvolution (NITUMID) framework for TME profiling that addresses these limitations. It is designed to provide robust estimates of tumor and immune cells proportions simultaneously, while accommodating mRNA level differences across cell types. Through comprehensive simulations and real data analyses, we demonstrate that

SUBMITTER: Tang D 

PROVIDER: S-EPMC8215918 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature