SAGAconf

Our ability to sequence--or read--DNA and RNA has been rapidly accelerating, even faster than Moore's Law. With this voluminous stream of incoming data, automated algorithms are needed to help us interpret and leverage it to understand the "language" of the genome, our DNA.

Specifically, genomes are comprised of many functional elements. Each of these sections of our DNA can be classified into functional classes, from gene bodies that serve as "recipes" encoding the contents of the proteins that run our lives, to promoters, enhancers and repressors that dynamically regulate the transcription--or "building"--of proteins in response to environmental variables.

Getting a picture of the functional elements that comprise genomes is important for human, plant and animal health, as well as advancing our understanding of gene regulation in general. So, how can we do so? 

It turns out that cells maintain a system of chemical "tags" on DNA, collectively called the epigenome, and that each class of functional element tends to carry a characteristic epigenetic "profile". Laboratory techniques like ChIP-seq have been developed to characterize the epigenome. Segmentation And Annotation Algorithms (SAGAs) segment genomes, predicting the functional elements that it comprises of from data from said lab techniques.

Note: Please read the review Segmentation and genome annotation algorithms for identifying chromatin state and other genomic patterns for a proper introduction to SAGAs.