Open AccessNITUMID: Nonnegative matrix factorization-based Immune-TUmor MIcroenvironment Deconvolution
Author(s) -
Daiwei Tang,
Seyoung Park,
Hongyu Zhao
Publication year - 2019
Publication title -
bioinformatics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz748
Subject(s) - deconvolution , non negative matrix factorization , matrix decomposition , computer science , tumor microenvironment , immune system , factorization , matrix (chemical analysis) , computational biology , algorithm , mathematics , algebra over a field , biology , chemistry , physics , immunology , pure mathematics , chromatography , eigenvalues and eigenvectors , quantum mechanics
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.
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