Document Type

Article

Publication Date

12-15-2015

Publication Title

BioMed Central Genomics

Department

Geisel School of Medicine

Abstract

BackgroundLarge collections of paraffin-embedded tissue represent a rich resource to test hypotheses based on gene expression patterns; however, measurement of genome-wide expression is cost-prohibitive on a large scale. Using the known expression correlation structure within a given disease type (in this case, high grade serous ovarian cancer; HGSC), we sought to identify reduced sets of directly measured (DM) genes which could accurately predict the expression of a maximized number of unmeasured genes.

DOI

10.1186/s12864-015-2250-5

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