|Interface||Command line interface|
|Restrictions to use||None|
|Input format||BED, BAM, VCF, GFF|
|Output format||BED, BAM, VCF, GFF, BAI|
|License||GNU General Public License version 2.0|
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- person_outline Aaron R. Quinlan <>
Publication for BEDTools
BEDTools IN pipelines(308)
[…] orientation were collapsed to a single read before subsequent analysis. density profiles were created by extending each read to the average library fragment size and then computing density using the bedtools suite. enriched regions were discovered using macs 2.0 and scored against matched input libraries. genomic ‘blacklisted’ regions were filtered […]
[…] mutant and wild-type cells were calculated using bamcompare in the deeptools, a data analysis program for high-throughput sequencing. the read counts and rpkm values were identified using the bedtools and bwtool utility program. rpkm values were calculated as: rpkm = (number of reads mapped to a gene × 1e + 09)/ (length of the gene × number of total mapped read counts in the experiment). […]
[…] -m, converts the output to bam using picard sortsam (v. 1.130; http://broadinstitute.github.io/picard/), and retains only the reads that have the most common mapped start and stop coordinates using bedtools (v. 2.19.1). reads were collapsed into consensus sequences using merge_primerid_read_groups.pl with options—ambig 600—min_freq 0.75 to require that the consensus base called makes […]
[…] peak detection using macs2. to identify repeats enriched for h4r3me2s, the number of chip-seq peaks overlapping each repeat class were compared with a random control where peaks were shuffled (using bedtools) over mappable regions of the genome. rna-seq data were aligned to mm9 using tophat v2.0.9  with -g 1 option, which assigns reads with multiple hits of equal quality to one […]
[…] around a-to-i rna editing sites in human and mouse was delineated in two steps: 1) extracting the profile of up- and down-stream sequences (15 bases on each side) flanking editing sites using bedtools getfasta ; 2) visualizing the sequence context around rna editing sites using weblogo 3(weblogo –a dna –c classic –units probability –first-index −10) ., level of expressed genes […]
In comparison, however, Homer is better if you want to intersect further files because it gives more details, ideal to create a Venn diagram !
A big plus of bedtools : tools are very well documented, with schemes ! I like: "shuffle" to randomly relocate peaks, to test significance of a pathway enrichment for example !