A0619
Title: Scalable test of statistical significance for protein-DNA binding changes with insertion and deletion of bases
Authors: Sunyoung Shin - Pohang University of Science and Technology (Korea, South) [presenting]
Abstract: Mutations in the noncoding DNA, which represents approximately 99\% of the human genome, have been crucial to understanding disease mechanisms through the dysregulation of disease-associated genes. One key element in gene regulation that noncoding mutations mediate is the binding of proteins to DNA sequences. Insertion and deletion of bases (InDels) are the second most common type of mutations, following single nucleotide polymorphisms, that may impact protein-DNA binding. However, no existing methods can estimate and test the effects of InDels on the process of protein-DNA binding. A novel test of statistical significance, namely the binding change test (BC test), is developed using a Markov model to evaluate the impact and InDels altering protein-DNA binding is identified. The test predicts binding changer InDels of regulatory significance with an efficient importance sampling algorithm generating background sequences in favour of sizeable binding affinity changes. Simulation studies demonstrate its excellent performance. The application to human leukaemia data uncovers candidate pathological InDels on modulating MYC binding in leukemic patients. An R package atIndel is developed, which is available on GitHub.
