Fast and robust deconvolution of tumor infiltrating lymphocyte from expression profiles using least trimmed squares.

ABSTRACT: Gene-expression deconvolution is used to quantify different types of cells in a mixed population. It provides a highly promising solution to rapidly characterize the tumor-infiltrating immune landscape and identify cold cancers. However, a major challenge is that gene-expression data are frequently contaminated by many outliers that decrease the estimation accuracy. Thus, it is imperative to develop a robust deconvolution method that automatically decontaminates data by reliably detecting and removing outliers. We developed a new machine learning tool, Fast And Robust DEconvolution of Expression Profiles (FARDEEP), to enumerate immune cell subsets from whole tumor tissue samples. To reduce noise in the tumor gene expression datasets, FARDEEP utilizes an adaptive least trimmed square to aut

SUBMITTER: Hao Y 

PROVIDER: S-EPMC6522071 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature