AgentSkillsCN

bio-alignment-filtering

利用 samtools view 和 pysam 按标记、比对质量以及区域范围对序列进行过滤。适用于提取特定读段、去除低质量比对,或按目标区域进行子集筛选。

SKILL.md
--- frontmatter
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

Alignment Filtering

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

Filter Flags

OptionDescription
-f FLAGInclude reads with ALL bits set
-F FLAGExclude reads with ANY bits set
-G FLAGExclude reads with ALL bits set
-q MAPQMinimum mapping quality
-L BEDInclude reads overlapping regions

Common FLAG Values

FlagHexMeaning
10x1Paired
20x2Proper pair
40x4Unmapped
80x8Mate unmapped
160x10Reverse strand
320x20Mate reverse strand
640x40First in pair (read1)
1280x80Second in pair (read2)
2560x100Secondary alignment
5120x200Failed QC
10240x400Duplicate
20480x800Supplementary

Filter by FLAG

Keep Only Mapped Reads

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

Keep Only Unmapped Reads

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

Keep Only Properly Paired

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

Remove Duplicates

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

Remove Secondary and Supplementary

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

Keep Only Primary Alignments

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

Keep Read1 Only

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

Keep Read2 Only

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

Forward Strand Only

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

Reverse Strand Only

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

Filter by Mapping Quality

Minimum MAPQ

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

MAPQ and Mapped

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

Common MAPQ Thresholds

MAPQMeaning
0Mapped 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
60Unique mapping (BWA max)

Filter by Region

Single Region

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

Multiple Regions

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

Regions from BED File

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

Combine Region and Quality

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

Combined Filters

Standard Quality Filter

bash
# 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

bash
# 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

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

Subsample Reads

Random Subsample

bash
# 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

bash
# 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

python
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

python
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

python
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

python
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.append((parts[0], int(parts[1]), int(parts[2])))
    return regions

regions = read_bed('targets.bed')

with pysam.AlignmentFile('input.bam', 'rb') as infile:
    with pysam.AlignmentFile('targets.bam', 'wb', header=infile.header) as outfile:
        for chrom, start, end in regions:
            for read in infile.fetch(chrom, start, end):
                outfile.write(read)

Subsample

python
import pysam
import random

random.seed(42)
fraction = 0.1

with pysam.AlignmentFile('input.bam', 'rb') as infile:
    with pysam.AlignmentFile('subset.bam', 'wb', header=infile.header) as outfile:
        for read in infile:
            if random.random() < fraction:
                outfile.write(read)

Quick Reference

Tasksamtools command
Mapped onlyview -F 4
Unmapped onlyview -f 4
Properly pairedview -f 2
Primary onlyview -F 2304
No duplicatesview -F 1024
High MAPQview -q 30
Regionview file.bam chr1:1-1000
BED regionsview -L file.bed
Subsample 10%view -s 0.1
Standard filterview -F 3332 -q 30

Common Filter Combinations

PurposeFlags
Clean reads-F 3332 -q 30 (mapped, primary, no dups, high qual)
Variant calling-f 2 -F 3328 -q 20 (proper pair, primary, no dups)
Coverage analysis-F 1284 -q 1 (mapped, primary, no dups)
Count unique-F 2304 (primary only)

Flag breakdowns:

  • 2304 = 256 + 2048 (secondary + supplementary)
  • 3328 = 256 + 1024 + 2048 (secondary + duplicate + supplementary)
  • 3332 = 4 + 256 + 1024 + 2048 (unmapped + secondary + duplicate + supplementary)
  • 1284 = 4 + 256 + 1024 (unmapped + secondary + duplicate)

Related Skills

  • sam-bam-basics - View and understand alignment files
  • alignment-sorting - Sort before/after filtering
  • alignment-indexing - Required for region filtering
  • duplicate-handling - Mark duplicates before filtering
  • bam-statistics - Check filter effects