title: annotatr: genomic regions in context.
abstract: BACKGROUND
  Analysis of next-generation sequencing data often results in a list of genomic regions. These may include differentially methylated CpGs/regions, transcription factor binding sites, interacting chromatin regions, or GWAS-associated SNPs, among others. A common analysis step is to annotate such genomic regions to genomic annotations (promoters, exons, enhancers, etc.). Existing tools are limited by a lack of annotation sources and flexible options, the time it takes to annotate regions, an artificial one-to-one region-to-annotation mapping, a lack of visualization options to easily summarize data, or some combination thereof.
  
  
  RESULTS
  We developed the annotatr Bioconductor package to flexibly and quickly summarize and plot annotations of genomic regions. The annotatr package reports all intersections of regions and annotations, giving a better understanding of the genomic context of the regions. A variety of graphics functions are implemented to easily plot numerical or categorical data associated with the regions across the annotations, and across annotation intersections, providing insight into how characteristics of the regions differ across the annotations. We demonstrate that annotatr is up to 27× faster than comparable R packages. Overall, annotatr enables a richer biological interpretation of experiments.
  
  
  METHODS
  http://bioconductor.org/packages/annotatr/ and https://github.com/rcavalcante/annotatr.
  
  
  BACKGROUND
  rcavalca@umich.edu.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computational Medicine and Bioinformatics.
authors.forename: Raymond G
authors.initials: RG
authors.lastname: Cavalcante
authors.affiliation: Department of Computational Medicine and Bioinformatics.|Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Maureen A
authors.initials: MA
authors.lastname: Sartor
mesh_terms: D002843:Chromatin / Q000378:metabolism; D005091:Exons; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D058977:Molecular Sequence Annotation / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D012045:Regulatory Sequences, Nucleic Acid; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
chemical_list: D002843:Chromatin