Our new method predicts transcription factor and chromatin factor locations in a cell type using new kinds of data like chromatin factor binding in other cell types and learning the association of gene expression patterns with chromatin factor binding patterns. We've made free software available and a track hub that can load our predictions for 36 chromatin factors in 33 human tissue types into the UCSC Genome Browser.
The second major version of semi-automated genome annotation software Segway is now available! It now runs on any Linux system, no longer needing a fancy compute cluster with Grid Engine or LSF. Now you can also install it and all its dependencies with a single Bioconda command!
conda install -c bioconda segway. Includes fancy new modeling methods like mixtures of Gaussians. Turns out a single Gaussian isn't the best distribution for genomic signal data. Who knew? Previously.
Many biological experiments use DNA sequencing as a readout. We can often map the sequenced DNA back to a specific region of the genome. Sometimes, however, we can't. Genomic data is less reliable in those regions. My lab has developed software that makes it easy to identify these regions. We also developed a new method that lets us find those regions in the context of bisulfite sequencing, a technique used to determine where DNA is chemically modified. [more inside]
Database of chemical modifications of DNA found in nature, with detailed information on each one. Includes links to scientific literature describing these modifications and how to sequence them.
BEDOPS is a suite of tools to address common questions raised in genomic studies, mostly with regard to overlap and proximity relationships between data sets. BEDOPS aims to be scalable, flexible and performant, facilitating the efficient and accurate analysis and management of large-scale genomic data.
The free Segway software package contains a novel method for analyzing multiple tracks of functional genomics data. Our method uses a dynamic Bayesian network (DBN) model, which enables it to analyze the entire genome at 1-bp resolution even in the face of heterogeneous patterns of missing data. This method is the first application of DBN techniques to genome-scale data and the first genomic segmentation method designed for use with the maximum resolution data available from ChIP-seq experiments without downsampling. Our software has extensive documentation and was designed from the outset with external users in mind. Researchers at other universities and institutes have already installed and used Segway for their own projects.