Deciphering the cancer microenvironment from bulk data with EcoTyper | Zendy

Andrea Rolong | Zendy; Bob Chen | Zendy; Ken S. Lau | Zendy

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Deciphering the cancer microenvironment from bulk data with EcoTyper

Author(s) -

Andrea Rolong,

Bob Chen,

Ken S. Lau

Publication year - 2021

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2021.09.028

Subject(s) - biology , tumor microenvironment , variety (cybernetics) , computational biology , cancer , transcriptome , deconvolution , tumor heterogeneity , tumor progression , cancer research , tumor cells , bioinformatics , genetics , computer science , gene expression , gene , artificial intelligence , algorithm

In this issue of Cell, Luca, Steen et al. develop the EcoTyper software to deconvolve tumor-microenvironment interactions from high volume bulk transcriptomics data. They demonstrate its effectiveness in improving predictions for tumor progression and patient prognosis for a variety of tumor types from multiple data sources.

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