Software

BiQ Analyzer HT

BiQ Analyzer HT is an enhanced version of BiQ Analyzer that provides extensive support for high-throughput bisulfite sequencing. BiQ Analyzer HT facilitates the processing, quality control and initial analysis of single-basepair resolution DNA methylation data. It was developed for deep bisulfite sequencing of one or more loci using the Roche 454 platform, but it easily extends to other sequencing platforms. BiQ Analyzer HT features a biologist-friendly graphical user interface, a fast alignment algorithm and a variety of ways to visualize DNA methylation data. Nevertheless, users of clonal bisulfite sequencing who do not need these new features are encouraged to keep using the classical BiQ Analyzer.

BiQ Analyzer HT emerged as a result of the intensive cooperation with the Computational Biology Department at the Max-Planck Institute for Informatics. More information on getting and using BiQ Analyzer HT can be found in the publication describing it and at the program web-site.

RnBeads

Illumina's HumanMethylation BeadChips are enjoying increasing popularity and are widely used for the genome-wide DNA methylation profiling of epidemiological and clinical samples. Based on the bisulfite conversion and subsequent primer extension, these microarrays can yield quantitative DNA methylation estimates at single CpG resolution. Until recently no integrative data processing and analysis solutions existed that would be easy to use and comprehensive for the users with a life-science background. In cooperation with the Max-Planck Institute for Informatics Computational Biology department our group has now filled this gap. RnBeads R-package is a turnkey pipeline which leads the user from raw input data of various formats, through numerous quality assessment, normalization and filtering steps to differentially methylated CpGs, promoters and genes. Multiple facets of data representation by RnBeads enable a deep and through understanding of the HumanMethylation450 data sets, and simplify the gain of valuable biological insights. Publication-quality graphics based on novel R-graphics grammar, and solid statistical methods in the background, make it much easier for life-science users to report on their results, without being swamped in creation of the custom bioinformatic solutions.