Goldmine integrates information placing genomic ranges into meaningful biological contexts

Nucleic Acids Res. 2016 Jul 8;44(12):5550-6. doi: 10.1093/nar/gkw477. Epub 2016 Jun 1.


Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • DNA Methylation / genetics*
  • Genomics / methods*
  • High-Throughput Nucleotide Sequencing
  • Molecular Sequence Annotation / methods
  • Protein Binding / genetics
  • Software*