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---
name: bio-genome-intervals-bed-file-basics
description: BED file format fundamentals, creation, validation, and basic operations. Covers BED3 through BED12 formats, coordinate systems, sorting, and format conversion using bedtools and pybedtools. Use when working with genomic coordinates or preparing interval files for downstream tools.
tool_type: mixed
primary_tool: bedtools
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
  - read_file
  - run_shell_command
---

# 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)

```bash
# 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

```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

```bash
# 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

```python
import pybedtools

bed = pybedtools.BedTool('input.bed')
sorted_bed = bed.sort()
sorted_bed.saveas('sorted.bed')
```

## Validate BED Files

### Check Format

```bash
# 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

```python
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

```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

```bash
# 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

```bash
# 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

```python
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

```bash
# 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

```bash
# 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

```bash
# 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

```python
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

```bash
# 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

```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

```python
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


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