Identification of expression patterns in the progression of disease stages by integration of transcriptomic data.

ABSTRACT:

Background

In the study of complex diseases using genome-wide expression data from clinical samples, a difficult case is the identification and mapping of the gene signatures associated to the stages that occur in the progression of a disease. The stages usually correspond to different subtypes or classes of the disease, and the difficulty to identify them often comes from patient heterogeneity and sample variability that can hide the biomedical relevant changes that characterize each stage, making standard differential analysis inadequate or inefficient.

Results

We propose a methodology to study diseases or disease stages ordered in a sequential manner (e.g. from early stages with good prognosis to more acute or serious stages associated to poor prognosis). The methodology

SUBMITTER: Aibar S 

PROVIDER: S-EPMC5133487 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature