/bio-alignment-filtering

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--- name: bio-alignment-filtering description: Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

• read_file
• run_shell_command

---

Alignment Filtering

Filter alignments by flags, quality, and regions using samtools and pysam.

Filter Flags

| Option | Description | |--------|-------------| | `-f FLAG` | Include reads with ALL bits set | | `-F FLAG` | Exclude reads with ANY bits set | | `-G FLAG` | Exclude reads with ALL bits set | | `-q MAPQ` | Minimum mapping quality | | `-L BED` | Include reads overlapping regions |

Common FLAG Values

| Flag | Hex | Meaning | |------|-----|---------| | 1 | 0x1 | Paired | | 2 | 0x2 | Proper pair | | 4 | 0x4 | Unmapped | | 8 | 0x8 | Mate unmapped | | 16 | 0x10 | Reverse strand | | 32 | 0x20 | Mate reverse strand | | 64 | 0x40 | First in pair (read1) | | 128 | 0x80 | Second in pair (read2) | | 256 | 0x100 | Secondary alignment | | 512 | 0x200 | Failed QC | | 1024 | 0x400 | Duplicate | | 2048 | 0x800 | Supplementary |

Filter by FLAG

Keep Only Mapped Reads

samtools view -F 4 -o mapped.bam input.bam

Keep Only Unmapped Reads

samtools view -f 4 -o unmapped.bam input.bam

Keep Only Properly Paired

samtools view -f 2 -o proper.bam input.bam

Remove Duplicates

samtools view -F 1024 -o nodup.bam input.bam

Remove Secondary and Supplementary

samtools view -F 2304 -o primary.bam input.bam

Keep Only Primary Alignments

samtools view -F 256 -F 2048 -o primary.bam input.bam
# Or combined: -F 2304

Keep Read1 Only

samtools view -f 64 -o read1.bam input.bam

Keep Read2 Only

samtools view -f 128 -o read2.bam input.bam

Forward Strand Only

samtools view -F 16 -o forward.bam input.bam

Reverse Strand Only

samtools view -f 16 -o reverse.bam input.bam

Filter by Mapping Quality

Minimum MAPQ

samtools view -q 30 -o highqual.bam input.bam

MAPQ and Mapped

samtools view -F 4 -q 30 -o filtered.bam input.bam

Common MAPQ Thresholds

| MAPQ | Meaning | |------|---------| | 0 | Mapped to multiple locations equally well | | 20 | ~1% chance of wrong mapping | | 30 | ~0.1% chance of wrong mapping | | 40 | ~0.01% chance of wrong mapping | | 60 | Unique mapping (BWA max) |

Filter by Region

Single Region

samtools view -o region.bam input.bam chr1:1000000-2000000

Multiple Regions

samtools view -o regions.bam input.bam chr1:1000-2000 chr2:3000-4000

Regions from BED File

samtools view -L targets.bed -o targets.bam input.bam

Combine Region and Quality

samtools view -q 30 -L targets.bed -o filtered.bam input.bam

Combined Filters

Standard Quality Filter

# Primary, mapped, non-duplicate, MAPQ >= 30
samtools view -F 3332 -q 30 -o filtered.bam input.bam
# 3332 = 4 (unmapped) + 256 (secondary) + 1024 (duplicate) + 2048 (supplementary)

Variant Calling Prep

# Properly paired, primary, no duplicates, MAPQ >= 20
samtools view -f 2 -F 3328 -q 20 -o clean.bam input.bam
# 3328 = 256 (secondary) + 1024 (duplicate) + 2048 (supplementary)
# Note: -f 2 (proper pair) implies mapped, so -F 4 is not strictly needed

ChIP-seq Filter

# Remove duplicates and low MAPQ
samtools view -F 1024 -q 30 -o filtered.bam input.bam

Subsample Reads

Random Subsample

# Keep ~10% of reads
samtools view -s 0.1 -o subset.bam input.bam

# With seed for reproducibility
samtools view -s 42.1 -o subset.bam input.bam

Subsample to Target Count

# Calculate fraction needed
total=$(samtools view -c input.bam)
frac=$(echo "scale=4; 1000000 / $total" | bc)
samtools view -s "$frac" -o subset.bam input.bam

pysam Python Alternative

Basic Filtering

import pysam

with pysam.AlignmentFile('input.bam', 'rb') as infile:
    with pysam.AlignmentFile('filtered.bam', 'wb', header=infile.header) as outfile:
        for read in infile:
            if read.is_unmapped:
                continue
            if read.mapping_quality < 30:
                continue
            if read.is_duplicate:
                continue
            outfile.write(read)

Filter with Function

import pysam

def passes_filter(read):
    if read.is_unmapped:
        return False
    if read.is_secondary or read.is_supplementary:
        return False
    if read.is_duplicate:
        return False
    if read.mapping_quality < 30:
        return False
    return True

with pysam.AlignmentFile('input.bam', 'rb') as infile:
    with pysam.AlignmentFile('filtered.bam', 'wb', header=infile.header) as outfile:
        for read in infile:
            if passes_filter(read):
                outfile.write(read)

Filter by Region

import pysam

with pysam.AlignmentFile('input.bam', 'rb') as infile:
    with pysam.AlignmentFile('region.bam', 'wb', header=infile.header) as outfile:
        for read in infile.fetch('chr1', 1000000, 2000000):
            outfile.write(read)

Filter from BED File

import pysam

def read_bed(bed_path):
    regions = []
    with open(bed_path) as f:
        for line in f:
            if line.startswith('#'):
                continue
            parts = line.strip().split('\t')
            regions