grit jaccard

Calculate Jaccard similarity between two BED files.

Usage

grit jaccard [OPTIONS] -a <FILE_A> -b <FILE_B>

Options

Option	Description
-a, --file-a <FILE>	Input BED file A
-b, --file-b <FILE>	Input BED file B

Examples

Basic Jaccard similarity

# Calculate Jaccard index between two BED files
grit jaccard -a peaks1.bed -b peaks2.bed

Compare replicates

# Compare ChIP-seq replicates
grit jaccard -a rep1_peaks.bed -b rep2_peaks.bed

Compare conditions

# Compare peaks between conditions
grit jaccard -a control_peaks.bed -b treatment_peaks.bed

Output

intersection    union    jaccard    n_intersections
500000    2000000    0.25    150

Column	Description
intersection	Total bases in intersection
union	Total bases in union
jaccard	Jaccard index (intersection/union)
n_intersections	Number of intersecting interval pairs

Understanding Jaccard Index

The Jaccard index measures similarity between two sets:

J(A,B) = |A ∩ B| / |A ∪ B|

Value	Interpretation
0.0	No overlap
0.5	50% similarity
1.0	Identical

Visual Example

A:    |-------|    |-------|
B:        |-------|    |-----|

Intersection: |--|         |-|
Union:    |-----------|---------|

Jaccard = intersection_bp / union_bp

Use Cases

Replicate concordance

# High Jaccard = good reproducibility
grit jaccard -a rep1.bed -b rep2.bed
# Output: jaccard = 0.85 (good concordance)

Method comparison

# Compare peak callers
grit jaccard -a macs2_peaks.bed -b homer_peaks.bed

Condition comparison

# Compare differential binding
grit jaccard -a wt_peaks.bed -b ko_peaks.bed

Quality control

# Compare to gold standard
grit jaccard -a my_peaks.bed -b encode_peaks.bed

Performance

GRIT uses an efficient streaming algorithm, using significantly less memory than bedtools for large files.

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