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Activity Number: 570 - Joint Modeling of Longitudinal and Survival Data
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #304907 Presentation
Title: A Joint Modeling Approach of Repeated Measure and Time-To-Event Data for Differentially Expressed/Spliced Isoform Transcripts
Author(s): Huining Kang* and Xichen Li and Li Luo and Scott A Ness
Companies: University of New Mexico and University of New Mexico and University of New Mexico and University of New Mexico
Keywords: Joint model; Repeated measure; time-to-event; Alternative splicing; isoform switch

RNA-sequencing technology has made it possible to reconstruct and quantify the alternative spliced isoform transcripts. However, statistical methods for detection of differentially expressed/spliced isoforms still need development, especially when time-to-event data are involved. We propose a joint modeling approach of repeated measure and time-to-event data to identifying isoforms that are differentially expressed/spliced with respect to survival outcome. The model depicts three types of genes related to alternatively splicing events concerning their associations with survival outcome: genes with (1) no differentially expressed isoforms; (2) differential expression of isoforms but no differential splicing; and (3) differentially spliced isoforms with differential expression at the isoform level but not necessarily at the gene level such as genes with isoform switches. The model takes into account correlation among the isoforms of the same gene, which have typically been ignored in other existing approaches to differential isoforms. We demonstrate our approach through application to an RNA-Sequencing dataset from a study of adenoid cystic carcinoma (ACC) of salivary glands.

Authors who are presenting talks have a * after their name.

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