RT Journal Article SR Electronic T1 Discovery of methylation loci and analyses of differential methylation from replicated high-throughput sequencing data JF bioRxiv FD Cold Spring Harbor Laboratory SP 021436 DO 10.1101/021436 A1 Thomas J. Hardcastle YR 2015 UL http://biorxiv.org/content/early/2015/07/21/021436.abstract AB Motivation Cytosine methylation is widespread in most eukaryotic genomes and is known to play a substantial role in various regulatory pathways. Unmethylated cytosines may be converted to uracil through the addition of sodium bisulphite, allowing genome-wide quantification of cytosine methylation via high-throughput sequencing. The data thus acquired allows the discovery of methylation ‘loci’, contiguous regions of methylation consistently methylated across biological replicates. The mapping of these loci allows for associations with other genomic factors to be identified, and for analyses of differential methylation to take place.Results The segmentSeq R package has been extended to identify methylation loci from high-throughput sequencing data from multiple conditions. A statistical model is then developed that accounts for biological replication and variable rates of non-conversion of cytosines in each sample to compute posterior likelihoods of methylation at each locus within an empirical Bayesian framework. The same model is used as a basis for analysis of differential methylation between multiple experimental conditions with the baySeq R package. These analyses are demonstrated on a set of data derived from Dicer-like mutants in Arabidopsis to reveal complex interactions between the different Dicer-like mutants and their methylation pathways.Availability The segmentSeq and baySeq packages are available on the Bioconductor http://www.bioconductor.org.Contact tjh48{at}cam.ac.uk