Pittsburgh Supercomputing Center 

Advancing the state-of-the-art in high-performance computing,
communications and data analytics.



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 and flexible, facilitating the efficient and accurate analysis and management of large-scale genomic data.

Installed on blacklight and Greenfield.

Other resources that may be helpful include:

  • Shane Neph, M. Scott Kuehn, Alex P. Reynolds, Eric Haugen, Robert E. Thurman, Audra K. Johnson, Eric Rynes, Matthew T. Maurano, Jeff Vierstra, Sean Thomas, Richard Sandstrom, Richard Humbert,and John A. Stamatoyannopoulos, BEDOPS: high-performance genomic feature operations. Bioinformatics  28 (14): 1919-1920 (2012). doi:10.1093/bioinformatics/bts277
  • Website: http://code.google.com/p/bedops/

Programs in the bedops package

bedextract Efficiently extracts features from BED input
bedmap Maps source signals from map-file onto qualified target regions from ref-file. Calculates an output for every ref-file element
bedops Offers set and multiset operations for files in BED format
closest-features For every element in input-file, find those elements in query-file nearest to its left and right edges
sort-bed Sorts input BED file(s) into the order required by other utilities. Loads all input data into memory
starch Lossless compression of any BED file
starchcat Merge multiple starch archive inputs into one starch archive output
unstarch Decompression of a starch archive

Help for bedops

On Greenfield, type module help bedops for information on available commands and how to get additional information.

Running bedops

  1. Create a batch job which
    1. On blacklight, sets up the use of the module command in a batch job
    2. Loads the bedops module
      module load bedops
    3. Includes other commands to run bedops
  2. Submit the batch job with the qsub command