Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with bedtools (CLI) and pybedtools/pyranges/bioframe (Python). Covers the sorted-input contract and the -sorted chromosome-order footgun, reciprocal/fractional overlap (-f/-F/-r/-e) and the A-vs-B asymmetry, -split for spliced/BED12/BAM features, and jaccard/fisher as mechanics only. Use when finding overlapping or unique regions between BED/peak/feature files, building consensus peaksets, removing blacklisted regions, transferring annotation values onto intervals, or computing interval-set similarity; route overlap-significance testing to overlap-significance.
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Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with bedtools (CLI) and pybedtools/pyranges/bioframe (Python). Covers the sorted-input contract and the -sorted chromosome-order footgun, reciprocal/fractional overlap (-f/-F/-r/-e) and the A-vs-B asymmetry, -split for spliced/BED12/BAM features, and jaccard/fisher as mechanics only. Use when finding overlapping or unique regions between BED/peak/feature files, building consensus peaksets, removing blacklisted regions, transferring annotation values onto intervals, or computing interval-set similarity; route overlap-significance testing to overlap-significance.
Before using code patterns, verify installed versions match. If versions differ:
CLI: bedtools --version then bedtools <subcommand> --help to confirm flags
Python: pip show <package> then help(module.function) to check signatures
pyranges has a major-version API split: pyranges 0.x and the 1.0 rewrite (package pyranges1) differ in method names and return shapes. Verify with import pyranges; pyranges.__version__ before pasting v0 idioms. If code throws an error, introspect the installed package and adapt rather than retrying.
Interval Arithmetic
"Which of my peaks overlap promoters, and how do I combine/subtract/annotate interval sets?" -> Apply exact, deterministic set operations to sorted interval files, guarding the preconditions (prior sort, the -sorted chromosome-order contract, -split) that otherwise corrupt the answer.
CLI: bedtools intersect -a a.bed -b b.bed -u, bedtools merge, bedtools subtract, bedtools map -c 4 -o mean
The Single Most Important Modern Insight -- The Arithmetic Is Exact; the Danger Is the Silent Preconditions
The set operations themselves are exact and deterministic - bedtools, pyranges, and bioframe compute identical geometry on the same 0-based half-open intervals. The bugs are never in the arithmetic; they hide in four preconditions that fail quietly, returning a plausible wrong answer with exit code 0:
merge, map, closest, groupby require prior sort.merge only collapses records that are adjacent in file order - on unsorted input, overlapping intervals survive un-merged and downstream counts are wrong, with no warning.
-sorted requires sorted input in a shared chromosome order. It swaps intersect's in-memory interval tree for a low-memory chromosome sweep. Modern bedtools (>=~2.25) detects unsorted or differently-ordered -sorted input and errors out (exit 1: ... is not sorted / chromomsome sort ordering ... is inconsistent); older versions silently swept past overlaps and under-reported. Pass -g genome.txt to pin the expected chromosome order (reproducible, and it catches the subtler missing-chromosome cases). The mismatch that stays SILENT on every version is a chromosome-NAME difference (chr1 vs 1), which returns an empty result with no error.
-split changes whether the count is exons or the spanning envelope. A BED12 record or spliced BAM read (CIGAR N) spans introns; without -split bedtools intersects the whole intron-spanning envelope, silently inflating RNA-seq overlaps. With -split it intersects only the blocks (exons).
A raw overlap count is not association. Long features, clustered features, and uneven coverage all inflate it; the number means nothing without a null. bedtools fisher is a weak analytic screen, not the answer - route rigorous significance to overlap-significance.
Tool Taxonomy
Tool
Role
Mechanism
When
bedtools
CLI interval algebra (reference implementation)
streaming sweep on sorted input; in-memory tree otherwise
shell pipelines, large files, reproducible one-liners
pybedtools
Python wrapper over bedtools
shells out to the bedtools binary; BedTool objects, flags as kwargs
inside a Python script; need exact bedtools parity; chaining with pandas
pyranges
pure-Python vectorized engine
native NumPy/pandas PyRanges; no bedtools dependency
large in-memory joins, no bedtools install, dataframe-native; mind the v0/v1 split
bioframe
functions on a plain pandas DataFrame
vectorized pandas merges; columns chrom/start/end
data already in pandas / the cooler-Hi-C ecosystem
All three Python engines compute the same overlaps; the porting bugs are about default strand handling and return shape (pyranges overlap vs join vs intersect; bioframe overlap with how=), not geometry.
Decision Tree by Scenario
Scenario
Recommended
Why
Quick overlap on the command line
bedtools intersect -u
no Python overhead; reproducible one-liner
Inside a pandas/Python pipeline
pybedtools or pyranges/bioframe
stays in-process; pyranges/bioframe need no bedtools binary
Whole-genome-scale intersect
intersect -sorted -g genome.txt
low-memory sweep; modern bedtools errors on a sort/order mismatch, -g pins the expected chromosome order
Spliced reads / BED12 vs exons
add -split
otherwise the intron-spanning envelope is intersected (RNA-seq inflation)
Are two SV/CNV calls the same event?
-f 0.5 -r (50% reciprocal)
one-sided fractions let a giant interval swallow a tiny one
Transfer/aggregate B values onto A
bedtools map -c COL -o OP
columnar alternative to intersect -wo | groupby
Build consensus peakset from replicates
cat | sort | merge -d N
collapses replicate peaks within N bp
Multi-sample shared-region map
multiinter / unionbedg
presence/absence (intervals) or stacked signal matrix
Is the overlap more than chance?
-> overlap-significance
raw count is length/coverage-confounded; needs a permutation null
Peaks not yet called
-> chip-seq/peak-calling or atac-seq/atac-peak-calling
this category operates on existing intervals
Intersect - the Workhorse
The output-mode flags do not change what overlaps; they change what gets printed (the #1 source of confusion). Full flag semantics are in usage-guide.md.
bedtools intersect -a peaks.bed -b genes.bed -u # whole A, once, if it overlaps >=1 B
bedtools intersect -a peaks.bed -b genes.bed -v # A features with NO overlap (set difference)
bedtools intersect -a peaks.bed -b genes.bed -c # per-A count of B hits (0 if none)
bedtools intersect -a peaks.bed -b genes.bed -wa -wb # whole A + whole B, one line per pair ("join")
bedtools intersect -a peaks.bed -b genes.bed -loj # left outer join: every A, NULL B if none
bedtools intersect -a peaks.bed -b genes.bed -wo # A+B+bp-of-overlap, only A with overlap
bedtools intersect -a peaks.bed -b genes.bed -wao # like -wo but A-with-no-overlap kept (B=., overlap=0)
import pybedtools
a = pybedtools.BedTool('peaks.bed')
b = pybedtools.BedTool('genes.bed')
a.intersect(b, u=True) # flags become kwargs
a.intersect(b, wa=True, wb=True)
a.intersect(b, c=True)
Subtract, Merge, Complement, Cluster
bedtools subtract -a a.bed -b b.bed # clip the overlapping portions out of A (A can fragment)
bedtools subtract -a a.bed -b b.bed -A # drop the ENTIRE A feature if any part overlaps B
bedtools sort -i a.bed | bedtools merge -d 0 # collapse overlapping + book-ended; -d 0 is the default
bedtools sort -i a.bed | bedtools merge -c 4,5 -o distinct,sum# summarize columns while merging
bedtools complement -i a.bed -g genome.txt # the gaps: genome NOT covered by A (genome file required)
bedtools sort -i a.bed | bedtools cluster -d 0 # assign a cluster id to overlapping/adjacent features
Valid -o operations: sum, min, max, absmin, absmax, mean, median, mode, antimode, stdev, sstdev, collapse, distinct, count, count_distinct, first, last. merge -d 0 merges overlapping and book-ended (touching) features but NOT a 1 bp gap; -d 1 does.
Map - Transfer Values, and Groupby - Aggregate
Goal: Summarize a column of overlapping B features onto each A interval (e.g. mean signal per gene).
Approach: For each sorted A interval, map collects overlapping B features and applies an aggregation -o to a B column -c; groupby is the single-file SQL-style aggregator after an intersect -wo.
bedtools map -a genes.bed -b scores.bedgraph -c 4 -o mean # both inputs MUST be sorted
bedtools intersect -a genes.bed -b peaks.bed -wo \
| bedtools groupby -g 1,2,3,4 -c 13 -o sum# group on A cols, sum the overlap-bp col
bedtools multiinter -header -names s1 s2 s3 -i s1.bed s2.bed s3.bed # which files cover each sub-interval
bedtools unionbedg -header -names s1 s2 s3 -i s1.bg s2.bg s3.bg # stack bedGraph signal into a matrix
multiinter is the interval presence/absence map (build a consensus by filtering its num/list columns); unionbedg is its signal-track analog.
Jaccard and Fisher - Mechanics Only
jaccard is a single similarity scalar |A n B| / |A u B| in [0,1], useful for all-vs-all dataset clustering - it is NOT a significance test (no p-value). fisher builds a 2x2 table and returns a Fisher p, but it estimates the in-neither cell from a mean-interval-size/genome-size heuristic, ignores genome structure, and is prone to inflation - treat it as a fast triage screen only.
bedtools jaccard -a a.bed -b b.bed -g genome.txt # both sorted; reports jaccard + n_intersections
bedtools fisher -a a.bed -b b.bed -g genome.txt # weak analytic null; validate any low p by simulation
For a defensible enrichment p-value (size-preserving permutation in an accessible workspace, GAT/regioneR/LOLA/GREAT), route to overlap-significance.
Per-Method Failure Modes
Merge without sorting first
Trigger:bedtools merge (or cluster/map/groupby) on unsorted input. Mechanism: merge only collapses records adjacent in file order. Symptom: overlapping intervals survive un-merged; counts wrong, no error. Fix:bedtools sort -i in.bed | bedtools merge.
-sorted on unsorted or differently-ordered input
Trigger:intersect -sorted on unsorted input or files in different chromosome orders. Mechanism: the sweep walks both files in lockstep assuming a shared order. Symptom: modern bedtools (>=~2.25) errors out (... is not sorted / chromomsome sort ordering ... is inconsistent, exit 1); pre-2.25 returned a silently smaller set. Fix: sort every input identically and pass -g genome.txt to pin the order; on an old bedtools, suspect this when a result is surprisingly small.
Missing -split on spliced features
Trigger: intersecting BED12 / spliced BAM without -split. Mechanism: the intron-spanning envelope is treated as solid. Symptom: intronic positions "overlap" exons; RNA-seq overlap inflated/smeared. Fix: add -split whenever an operand is BED12 or a spliced alignment and exon-level truth is required.
-f vs -F swapped, or default 1 bp overlap
Trigger: thresholding the wrong set, or no -f at all. Mechanism:-f is a fraction of A, -F a fraction of B (default -f 1e-9 = any 1 bp); A and B play asymmetric roles. Symptom: a tiny peak "inside" a 2 Mb gene by one base; swapping -a/-b changes counts. Fix: threshold the small set; use -r for "same event" concordance.
complement/shuffle without a genome file
Trigger:complement (or closest/map order assumptions) without -g. Mechanism: bedtools cannot know where chromosomes end. Symptom: error, or gaps/coordinates that run past chromosome ends. Fix: pass a correct -g genome.txt built from the same assembly.
chrom-naming mismatch (chr1 vs 1)
Trigger: BED uses chr1, genome/other file uses 1. Mechanism: chromosomes never match. Symptom: empty/zero output, no error. Fix: harmonize naming across all inputs and the genome file.
Quantitative Thresholds
Threshold
Source
Rationale
Overlap fraction -f (state explicitly)
analysis choice
default -f 1e-9 (1 bp) is rarely the biological question; threshold the small set
50% reciprocal overlap (-f 0.5 -r)
SV/CNV field convention
"are these the same event"; one-sided lets a big interval swallow a small one
Merge -d (e.g. 100 bp for replicate consensus)
replicate-merge convention
collapses near-coincident replicate peaks; tune per assay/resolution
merge -d 0 (default)
bedtools default
merges overlapping + book-ended, NOT a 1 bp gap (use -d 1 for that)
Common Errors
Error / symptom
Cause
Solution
Empty intersect output
chrom naming mismatch (chr1 vs 1)
harmonize naming across files + genome.txt
merge left overlaps behind
input not sorted
sort before merge/cluster/map/groupby
-sorted errors or (old bedtools) returns too few
unsorted or mismatched chromosome order
sort all inputs identically; add -g genome.txt to pin order
RNA-seq overlap looks inflated
missing -split on BED12/spliced BAM
add -split
Negative start / past-chromosome-end
wrong/missing -g genome.txt
pass a correct chrom-sizes file
pyranges AttributeError
0.x vs 1.0 API mismatch
check pyranges.__version__; use matching method names
References
Quinlan AR, Hall IM. 2010. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26:841-842.
Dale RK, Pedersen BS, Quinlan AR. 2011. Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics 27:3423-3424.
Stovner EB, Sætrom P. 2020. PyRanges: efficient comparison of genomic intervals in Python. Bioinformatics 36:918-919.
Open2C, Abdennur N, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A, Imakaev M, Venev SV. 2024. Bioframe: operations on genomic intervals in pandas dataframes. Bioinformatics 40:btae088.
Related Skills
bed-file-basics - BED format, coordinate systems, and the conversions this skill depends on
overlap-significance - Whether an overlap count exceeds a matched null (permutation, GAT/regioneR/LOLA/GREAT)
proximity-operations - closest, window, flank, slop for adjacency rather than membership
coverage-analysis - per-base depth and bedGraph signal feeding map/unionbedg
gtf-gff-handling - exon/feature models whose -split behavior this skill depends on
chip-seq/peak-calling - source of the peak BED files these operations consume
atac-seq/consensus-peakset - replicate merge via merge/multiinter
