Loss-function learning for digital tissue deconvolution
F Görtler, M Schoen, J Simeth, S Solbrig… - Journal of …, 2020 - liebertpub.com
The gene expression profile of a tissue averages the expression profiles of all cells in this
tissue. Digital tissue deconvolution addresses the following inverse problem: given the
expression profile y of a tissue, what is the cellular composition c of that tissue? If X is a
matrix whose columns are reference profiles of individual cell types, the composition c can
be computed by minimizing ℒ (y− X c) for a given loss function ℒ. Current methods use
predefined all-purpose loss functions. They successfully quantify the dominating cells of a …
tissue. Digital tissue deconvolution addresses the following inverse problem: given the
expression profile y of a tissue, what is the cellular composition c of that tissue? If X is a
matrix whose columns are reference profiles of individual cell types, the composition c can
be computed by minimizing ℒ (y− X c) for a given loss function ℒ. Current methods use
predefined all-purpose loss functions. They successfully quantify the dominating cells of a …
Loss-function learning for digital tissue deconvolution
F Görtler, S Solbrig, T Wettig, PJ Oefner… - … on Research in …, 2018 - Springer
The gene expression profile of a tissue averages the expression profiles of all cells in this
tissue. Digital tissue deconvolution (DTD) addresses the following inverse problem: Given
the expression profile y of a tissue, what is the cellular composition c of that tissue? If X is a
matrix whose columns are reference profiles of individual cell types, the composition c can
be computed by minimizing L (y-Xc) for a given loss function L. Current methods use
predefined all-purpose loss functions. They successfully quantify the dominating cells of a …
tissue. Digital tissue deconvolution (DTD) addresses the following inverse problem: Given
the expression profile y of a tissue, what is the cellular composition c of that tissue? If X is a
matrix whose columns are reference profiles of individual cell types, the composition c can
be computed by minimizing L (y-Xc) for a given loss function L. Current methods use
predefined all-purpose loss functions. They successfully quantify the dominating cells of a …
