Detection and accurate False Discovery Rate control of differentially methylated regions from Whole Genome Bisulfite Sequencing

Abstract

Summary 10With recent advances in sequencing technology, it is now feasible to measure DNA methylation 11 at tens of millions of sites across the entire genome. In most applications, biologists are 12 interested in detecting differentially methylated regions, composed of multiple sites with 13 differing methylation levels among populations. However, current computational approaches for 14 detecting such regions do not provide accurate statistical inference. A major challenge in 15 reporting uncertainty is that a genome-wide scan is involved in detecting these regions, which 16 needs to be accounted for. A further challenge is that sample sizes are limited due to the costs 17 associated with the technology. We have developed a new approach that overcomes these 18 challenges and assesses uncertainty for differentially methylated regions in a rigorous manner. 19Region-level statistics are obtained by fitting a generalized least squares (GLS) regression model 20 with a nested autoregressive correlated error structure for the effect of interest on transformed 21 methylation proportions. We develop an inferential approach, based on a pooled null 22 distribution, that can be implemented even when as few as two samples per population are 23available. Here we demonstrate the advantages of our method using both experimental data and 24Monte Carlo simulation. We find that the new method improves the specificity and sensitivity of 25 list of regions and accurately controls the False Discovery Rate (FDR).

High‐throughput identification of RNA nuclear enrichment sequences

“…We designed the oligo‐pool to tile each of the 38 lncRNAs with a 10‐nt shift between sequential oligonucleotides. This densely overlapping tiling approach offers us a unique advantage of allowing the computational “stitching” of sequential oligos (Jaffe et al , ; preprint: Korthauer et al , ), thus enabling identification of longer regions required for nuclear enrichment. Second, we cloned the pool of oligonucleotides to the 3′ end of a cytosolic‐localized Sox2 construct ( fsSox2 ).…”

Cord blood DNA methylome in newborns later diagnosed with autism spectrum disorder reflects early dysregulation of neurodevelopmental and X-linked genes

“…Sequencing reads were preprocessed, aligned to the human genome, and converted to CpG methylation count matrices with CpG_Me (v1.0, [69][70][71] autoregressive correlated error structure as implemented in the dmrseq package [79,80]. In this approach, candidate regions are identified based on consistent differences in mean methylation between groups, and region-level statistics are estimated which account for coverage, mean methylation, and correlation between CpGs.…”

“…DMBs were also identified with the dmrseq() function using the default parameters for blocks, except the single CpG methylation difference coefficient cutoff was set to 0.01 and the minimum number of CpGs was set to 3. As described in the dmrseq package vignette [79], the default parameters for DMBs differ from those for DMRs in that the minimum width for DMBs is 5 kilobases and the maximum gap between CpGs in a DMB is also 5 kilobases. Additionally, the smoothing span window is widened by setting the minimum CpGs in a smoothing window to 500, the width of the window to 50 kilobases, and the maximum gap between CpGs in the same smoothing cluster to 1 megabase.…”

Whole genome bisulfite sequencing of Down syndrome brain reveals regional DNA hypermethylation and novel disorder insights

“…DMRs were called utilizing the DMRichR workflow (https://github.com/benlaufer/DMRichR). This workflow primarily utilizes the dmrseq 54 and bsseq 55 packages for inference of the DMRs and the annotatr 56 and ChIPseeker 57 packages for gene symbol, gene region, and CpG annotations. Briefly, CpG count matrixes (Bismark cytosine reports) were processed to merge symmetric CpG sites across strands and filtered for at least 1x coverage across samples.…”