Multiple functional linear model for association analysis of RNA-seq with imaging.

ABSTRACT: Emerging integrative analysis of genomic and anatomical imaging data which has not been well developed, provides invaluable information for the holistic discovery of the genomic structure of disease and has the potential to open a new avenue for discovering novel disease susceptibility genes which cannot be identified if they are analyzed separately. A key issue to the success of imaging and genomic data analysis is how to reduce their dimensions. Most previous methods for imaging information extraction and RNA-seq data reduction do not explore imaging spatial information and often ignore gene expression variation at the genomic positional level. To overcome these limitations, we extend functional principle component analysis from one dimension to two dimensions (2DFPCA) for representing i

SUBMITTER: Jiang J 

PROVIDER: S-EPMC4705549 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature