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

ABSTRACT:

Background

We present here a computational shortcut to improve a powerful wavelet-based method by Shim and Stephens (Ann Appl Stat 9(2):665-686, 2015. https://doi.org/10.1214/14-AOAS776 ) called WaveQTL that was originally designed to identify DNase I hypersensitivity quantitative trait loci (dsQTL).

Results

WaveQTL relies on permutations to evaluate the significance of an association. We applied a recent method by Zhou and Guan (J Am Stat Assoc 113(523):1362-1371, 2017. https://doi.org/10.1080/01621459.2017.1328361 ) to boost computational speed, which involves calculating the distribution of Bayes factors and estimating the significance of an association by simulations rather than permutations. We called this simulation-based approach "fast functional wavelet" (FFW), and t

SUBMITTER: Denault WRP 

PROVIDER: S-EPMC7876806 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature