Feb 4, 2016

chromstaR: Tracking combinatorial chromatin state dynamics in space and time

BioRxiv : the Preprint Server for Biology
Aaron TaudtMaria Colome-Tatche

Abstract

Background: Post-translational modifications of histone residue tails are an important component of genome regulation. It is becoming increasingly clear that the combinatorial presence and absence of various modifications define discrete chromatin states which determine the functional properties of a locus. An emerging experimental goal is to track changes in chromatin state maps across different conditions, such as experimental treatments, cell-types or developmental time points. Results: Here we present chromstaR, an algorithm for the computational inference of combinatorial chromatin state dynamics across an arbitrary number of conditions. ChromstaR uses a multivariate Hidden Markov Model to determine the number of discrete combinatorial chromatin states using multiple ChIP-seq experiments as input and assigns every genomic region to a state based on the presence/absence of each modification in every condition. We demonstrate the advantages of chromstaR in the context of three common experimental data scenarios. First, we study how different histone modifications combine to form combinatorial chromatin states in a single tissue. Second, we infer genome-wide patterns of combinatorial state differences between two cell types o...Continue Reading

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Mentioned in this Paper

Computer Software
Histone antigen
Genome
Post-Translational Protein Processing
Regulation of Biological Process
Anatomical Space Structure
Cell Differentiation Process
Objective (Goal)
Genomics
Histone Modification

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