The last appointment for the Seminar series in Statistics and Data Science​ this semester will take place on Tuesday 08.12.2020.

The speaker will be William Robert Paul Denault, from the Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, welcome!

It will be possible to follow the seminar on Zoom using this link: https://uio.zoom.us/j/66468377366?pwd=WkFQNHBTM1hheUN5NVQyc2Zpd3R6UT09.

The seminar will start at 14:15​, as usual.

Title:
Detecting differentially methylated regions using a fast wavelet-based approach to functional association analysis

Abstract:
We present here a computational shortcut to improve a powerful wavelet-based method by Shim and Stephens (2015) called WaveQTL that was originally designed to identify DNase I hypersensitivity quantitative trait loci (dsQTL). WaveQTL relies on permutations to evaluate the significance of an association. To boost computational speed, we applied a recent method by Zhou and Guan (2017) for calculating the distribution of Bayes factors, which allowed the significance of an association to be estimated by simulations rather than permutations. We called this simulation-based approach ``fast functional wavelet" (FFW), and tested it on a publicly available DNA methylation (DNAm) dataset on colorectal cancer. Our simulations confirmed a substantial gain in computational speed compared to the permutation-based approach in WaveQTL. Furthermore, we show that FFW controls the type I error satisfactorily and has good power for detecting differentially methylated regions. Our approach has broad utility and can be applied to detect associations between different types of functions and phenotypes.

Best regards,
Riccardo De Bin & Riccardo Parviero​