B1784
Title: Identifying rare and weak effects in discrete count data from high throughput sequencing experiment
Authors: Anat Reiner-Benaim - Ben-Gurion University of the Negev (Israel) [presenting]
Sebastian Doehler - Darmstadt University of Applied Science (Germany)
Abstract: The Bardet Biedl syndrome (BBS) is a rare multisystemic disease with several known causative genes. The aim is to find single nucleotide polymorphisms (SNPs) that are associated with the phenotypic presentation of the disease. A real high-throughput sequencing dataset is described from patients who are carriers of BBS, of which only some are afflicted by the disease. The statistical challenges in analyzing such data are discussed, where the effects to be identified are potentially rare and weak, while the data consists of counts with small sample sizes, leading to high discreteness in the resulting p-value distributions. Some ongoing work is presented on developing analysis methods for this type of data, with an emphasis on multiple testing.
