Sciweavers

BMCBI
2010

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

13 years 2 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, qua...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where BMCBI
Authors Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard Walzl, Gillian F. Black, Joachim Selbig, Shreemanta K. Parida, Stefan H. E. Kaufmann, Marc Jacobsen
Comments (0)