A Hidden Markov Model for Analyzing ChIP-chip Experiments on Genome Tiling Arrays
A model-based algorithm for finding enriched regions in ChIP-Chip experiments
An integrated webserver for analyzing ChIP-chip data
A intuitive and efficient algorithm for the mapping of millions of query oligonucleotide fragments to the genome of any given length, at least an order of magnitude faster than other popular existing tools
A model-based algorithm for finding enriched regions in ChIP-Seq experiments.
Bisulfite sequencing is a powerful technique to study DNA cytosine methylation. Bisulfite treatment followed by PCR amplification specifically converts unmethylated cytosines to thymine. Coupled with next generation sequencing technology, it is able to detect the methylation status of every cytosine in the genome. However, mapping high-throughput bisulfite reads to the reference genome remains a great challenge due to the increased searching space, reduced complexity of bisulfite sequence, asymmetric cytosine to thymine alignments, and multiple CpG heterogeneous methylation. We developed an efficient bisulfite reads mapping algorithm BSMAP to address the above issues. BSMAP combines genome hashing and bitwise masking to achieve fast and accurate bisulfite mapping. Compared with existing bisulfite mapping approaches, BSMAP is faster, more sensitive and more flexible. BSMAP is the first general-purpose bisulfite mapping software. It is able to map high-throughput bisulfite reads at whole genome level with feasible memory and CPU usage. It is freely available under GPL v3 license at http://code.google.com/p/bsmap/