bg-szy BED File Basics
BED (Browser Extensible Data) format stores genomic intervals. Uses 0-based, half-open coordinates.
BED Format Columns
BED3: chr start end
BED4: chr start end name
BED5: chr start end name score
BED6: chr start end name score strand
BED12: chr start end name score strand thickStart thickEnd rgb blockCount blockSizes blockStarts
Coordinate System
BED uses 0-based, half-open coordinates:
- Start: 0-based (first base is 0)
- End: exclusive (not included)
- Position 100-200 means bases at positions 100-199
Create BED Files
From Text (CLI)
# Create simple BED3
echo -e "chr1\t100\t200\nchr1\t300\t400" > regions.bed
# Create BED6 with name and strand
echo -e "chr1\t100\t200\tpeak1\t100\t+" > peaks.bed
From Python
import pybedtools
# From string
bed_string = '''chr1\t100\t200\tpeak1\t100\t+
chr1\t300\t400\tpeak2\t200\t-'''
bed = pybedtools.BedTool(bed_string, from_string=True)
# From list of tuples
intervals = [
('chr1', 100, 200, 'peak1', 100, '+'),
('chr1', 300, 400, 'peak2', 200, '-'),
]
bed = pybedtools.BedTool(intervals)
# From pandas DataFrame
import pandas as pd
df = pd.DataFrame({
'chrom': ['chr1', 'chr1'],
'start': [100, 300],
'end': [200, 400],
'name': ['peak1', 'peak2'],
'score': [100, 200],
'strand': ['+', '-']
})
bed = pybedtools.BedTool.from_dataframe(df)
# Save to file
bed.saveas('output.bed')
Sort BED Files
CLI
# Sort by chromosome and position
sort -k1,1 -k2,2n input.bed > sorted.bed
# Using bedtools
bedtools sort -i input.bed > sorted.bed
# Sort by chromosome, start, then end
sort -k1,1 -k2,2n -k3,3n input.bed > sorted.bed
Python
import pybedtools
bed = pybedtools.BedTool('input.bed')
sorted_bed = bed.sort()
sorted_bed.saveas('sorted.bed')
Validate BED Files
Check Format
# Check column count
awk -F'\t' '{print NF}' input.bed | sort -u
# Check for invalid coordinates (start >= end)
awk '$2 >= $3' input.bed
# Check for negative coordinates
awk '$2 < 0 || $3 < 0' input.bed
# Validate with bedtools
bedtools sort -i input.bed > /dev/null 2>&1 && echo "Valid" || echo "Invalid"
Python Validation
import pybedtools
def validate_bed(filepath):
try:
bed = pybedtools.BedTool(filepath)
for interval in bed:
if interval.start < 0 or interval.end < 0:
return False, 'Negative coordinates'
if interval.start >= interval.end:
return False, f'Invalid interval: {interval.start} >= {interval.end}'
return True, 'Valid'
except Exception as e:
return False, str(e)
valid, msg = validate_bed('input.bed')
print(f'{msg}')
Read BED Files
Python
import pybedtools
# Load BED file
bed = pybedtools.BedTool('input.bed')
# Iterate over intervals
for interval in bed:
print(f'{interval.chrom}:{interval.start}-{interval.end}')
print(f'Name: {interval.name}, Score: {interval.score}, Strand: {interval.strand}')
# Count intervals
n_intervals = bed.count()
# Convert to pandas DataFrame
df = bed.to_dataframe()
# Access specific columns
df = bed.to_dataframe(names=['chrom', 'start', 'end', 'name', 'score', 'strand'])
Filter BED Files
By Chromosome
# Single chromosome
grep "^chr1\t" input.bed > chr1.bed
# Multiple chromosomes
grep -E "^(chr1|chr2)\t" input.bed > chr1_2.bed
# Exclude chromosome
grep -v "^chrM\t" input.bed > no_chrM.bed
By Size
# Intervals >= 100bp
awk '($3 - $2) >= 100' input.bed > large.bed
# Intervals between 100-500bp
awk '($3 - $2) >= 100 && ($3 - $2) <= 500' input.bed > medium.bed
Python Filtering
import pybedtools
bed = pybedtools.BedTool('input.bed')
# Filter by chromosome
chr1 = bed.filter(lambda x: x.chrom == 'chr1')
# Filter by size
large = bed.filter(lambda x: len(x) >= 100)
# Filter by strand
plus_strand = bed.filter(lambda x: x.strand == '+')
# Filter by score
high_score = bed.filter(lambda x: float(x.score) >= 500)
# Chain filters
result = bed.filter(lambda x: x.chrom == 'chr1' and len(x) >= 100)
result.saveas('filtered.bed')
Convert Formats
BED to Other Formats
# BED to GFF
bedtools bed12togff -i input.bed > output.gff
# BED to FASTA (extract sequences)
bedtools getfasta -fi reference.fa -bed input.bed -fo output.fa
# BED to FASTA with names
bedtools getfasta -fi reference.fa -bed input.bed -name -fo output.fa
From VCF to BED
# Extract variant positions
bcftools query -f '%CHROM\t%POS0\t%END\n' input.vcf > variants.bed
# Or using awk (simpler for SNPs)
grep -v "^#" input.vcf | awk '{print $1"\t"$2-1"\t"$2}' > snps.bed
From BAM to BED
# Convert alignments to BED
bedtools bamtobed -i input.bam > alignments.bed
# BED12 for spliced alignments
bedtools bamtobed -i input.bam -split > spliced.bed
Interval Arithmetic Basics
import pybedtools
interval = pybedtools.create_interval_from_list(['chr1', '100', '200', 'peak1', '0', '+'])
# Access fields
print(interval.chrom) # chr1
print(interval.start) # 100 (int)
print(interval.end) # 200 (int)
print(interval.name) # peak1
print(interval.score) # 0
print(interval.strand) # +
# Get length
print(len(interval)) # 100
# Get fields list
print(interval.fields) # ['chr1', '100', '200', 'peak1', '0', '+']
Make Windows - Create Genomic Intervals
CLI
# Fixed-size windows across genome
bedtools makewindows -g genome.txt -w 10000 > windows_10kb.bed
# Windows with step size (sliding windows)
bedtools makewindows -g genome.txt -w 10000 -s 5000 > sliding_10kb.bed
# Fixed number of windows per chromosome
bedtools makewindows -g genome.txt -n 100 > 100_windows_per_chr.bed
# Windows within BED regions
bedtools makewindows -b regions.bed -w 1000 > windows_in_regions.bed
# Add window ID
bedtools makewindows -g genome.txt -w 10000 -i winnum > numbered_windows.bed
# Source chromosome in name
bedtools makewindows -g genome.txt -w 10000 -i srcwinnum > windows_with_source.bed
Python
import pybedtools
# From genome file
windows = pybedtools.BedTool().window_maker(g='genome.txt', w=10000)
# Sliding windows
windows = pybedtools.BedTool().window_maker(g='genome.txt', w=10000, s=5000)
# From BED regions
bed = pybedtools.BedTool('regions.bed')
windows = pybedtools.BedTool().window_maker(b=bed.fn, w=1000)
windows.saveas('windows.bed')
Common BED Extensions
| Format | Description | Columns |
|---|---|---|
| narrowPeak | ENCODE narrow peaks | BED6 + signalValue, pValue, qValue, peak |
| broadPeak | ENCODE broad peaks | BED6 + signalValue, pValue, qValue |
| bedGraph | Signal track | chr, start, end, value |
| bedpe | Paired intervals | chr1, s1, e1, chr2, s2, e2, name, score, strand1, strand2 |
Cleanup Temp Files
import pybedtools
# At end of script
pybedtools.cleanup()
# Or use context manager (auto-cleanup)
pybedtools.set_tempdir('/tmp/pybedtools')
Related Skills
- interval-arithmetic - intersect, subtract, merge operations
- gtf-gff-handling - annotation file parsing
- coverage-analysis - depth calculations
- alignment-files/sam-bam-basics - BAM to BED conversion