title: 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 imaging data and develop a multiple functional linear model (MFLM) in which functional principal scores of images are taken as multiple quantitative traits and RNA-seq profile across a gene is taken as a function predictor for assessing the association of gene expression with images. The developed method has been applied to image and RNA-seq data of ovarian cancer and kidney renal clear cell carcinoma (KIRC) studies. We identified 24 and 84 genes whose expressions were associated with imaging variations in ovarian cancer and KIRC studies, respectively. Our results showed that many significantly associated genes with images were not differentially expressed, but revealed their morphological and metabolic functions. The results also demonstrated that the peaks of the estimated regression coefficient function in the MFLM often allowed the discovery of splicing sites and multiple isoforms of gene expressions.
authors.affiliation: Human Genetics Center, Division of Biostatistics, The University of Texas School of Public Health, Houston, TX 77030, USA.
authors.forename: Junhai
authors.initials: J
authors.lastname: Jiang
authors.affiliation: Human Genetics Center, Division of Biostatistics, The University of Texas School of Public Health, Houston, TX 77030, USA.
authors.forename: Nan
authors.initials: N
authors.lastname: Lin
authors.affiliation: Human Genetics Center, Division of Biostatistics, The University of Texas School of Public Health, Houston, TX 77030, USA; State Key Laboratory of Genetic Engineering and Ministry of Education, Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China.
authors.forename: Shicheng
authors.initials: S
authors.lastname: Guo
authors.affiliation: Department of Epidemiology, Division of OVP, Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
authors.forename: Jinyun
authors.initials: J
authors.lastname: Chen
authors.affiliation: Human Genetics Center, Division of Biostatistics, The University of Texas School of Public Health, Houston, TX 77030, USA.
authors.forename: Momiao
authors.initials: M
authors.lastname: Xiong
keywords: RNA-seq; functional linear model; functional principal component analysis; imaging; imaging genomics