Forum:Bedops: The Fastest, Most Scalable, And Easily-Parallelizable Genome Analysis Toolkit!
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10.9 years ago

What is BEDOPS?

BEDOPS is an open-source command-line toolkit that performs efficient and scalable Boolean and other set operations, statistical calculations, archiving, conversion and other management of genomic data of arbitrary scale.

BEDOPS tools are flexible

Our tools fit easily into analysis pipelines, allow practically unlimited inputs, and reduce I/O overhead through standard UNIX input and output streams:

$ bedops --intersect A.bed B.bed C.bed \
    | bedmap --echo --mean - D.bed \
    | ... \
    > Answer.bed

Our bedops and bedmap tools offer numerous operations of all kinds (including those mentioned in the slides below):

BEDOPS bedops

BEDOPS bedmap

BEDOPS tools are fast and efficient

BEDOPS tools take advantage of the information in a sorted BED file to use only what data are needed to perform the analysis. Our tools are agnostic about genomes: Run BEDOPS on genomes as small as Circovirus or as large as Polychaos dubium!

Independent tests comparing various kits show that BEDOPS offers the fastest operations with the lowest memory overhead:


BEDOPS also introduces a novel lossless compression format called Starch that reduces whole-genome BED datasets to ~5% of their original size (and BAM datasets to roughly 35% of their original size), while adding useful metadata and random access, allowing instantaneous retrieval of any compressed chromosome:


BEDOPS tools make your work embarrassingly easy to parallelize

BEDOPS tools introduce the --chrom option to efficiently locate a specified chromosome within a sorted BED file, useful for “embarrassingly parallel” whole-genome analyses, where work can be logically divided by units of chromosome in a "map-reduce" fashion.

BEDOPS tools are open, documented and supported

BEDOPS is available as GPL-licensed source code and precompiled binaries for Linux and Mac OS X. We offer support through online forums (including our own) and recipes showing BEDOPS tools in use for answering common research questions.


  1. 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 (2012) 28(14): 1919-1920. doi:10.1093/bioinformatics/bts277
  2. Kristian Ovaska, Lauri Lyly, Biswajyoti Sahu, Olli A. Jänne, and Sampsa Hautaniemi, Genomic Region Operation Kit for Flexible Processing of Deep Sequencing Data. Computational Biology and Bioinformatics, IEEE/ACM Transactions on (2013) 10(1): 200-206. doi:10.1109/TCBB.2012.170
bedops genome-analysis • 6.9k views
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Thanks. Useful tools.


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