A method to map DNA methylation data from bisulfite sequencing approaches to CpG sites measured with the widely used Illumina methylation bead-array platforms. Correlations and median absolute deviations support the validity of using bisulfite sequencing data in combination with Illumina bead-array methylation data. The methyLiftover utility will enhance the field of epigenomic research by expanding the comparability of DNA methylation data in the absence of the common Illumina 450K methylation data. The methyLiftover tool contains functions to subset and map WGBS and RRBS data to the CpG sites specific to the Illumina 450K array, both individually and as a whole directory, and create merged data sets from two user defined methylation data files (e.g. Illumina 850K annotation).
Allows users to optimize reduced representation bisulfite sequencing (RRBS) for the biological system of interest by using combinations of restriction enzymes. cuRRBS generalizes the problem of genomic enrichment with restriction enzymes by allowing users to define both the genome and the particular sites of interest. It provides users with a variety of measures to compare the different suggested protocols.
Detects viral integration breakpoints in whole human genomes. BSVF is based on bwa-meth and can find the virus breakpoints. This tool can search breakpoints in over 5 out of 9 regions which are identified by FISH. It assists users in studying epigenetic topics and in revealing the relationship between viral integration and DNA methylation.
Measures single cell DNA methylation. Melissa introduces a method able to simultaneously cluster cells using genome-wide methylation patterns while learning methylation profiles of regions of interest. This program leans on a Bayesian hierarchical model and can be used for CpG methylation states forecasting, without the requirement of additional annotation data. Besides, it can also determine subsets of cells based solely on epigenetic state.
A web tool for the detection of significant enrichment and depletion of combinations of annotations is presented. Annotation-Modules accepts 12 different input IDs, allows free selection of the reference genes and the upload of pre-annotated gene lists. It offers an improvement over the current tools in two critical aspects. First, the underlying annotation database implements features from many different fields like gene regulation and expression, sequence properties, evolution and conservation, genomic localization and functional categories-resulting in about 60 different annotation features. Second, it examines not only single annotations but also all the combinations, which is important to gain insight into the interplay of different mechanisms in the analyzed biological system.