Pileup generation

Version Compatibility

Reference examples tested with: bcftools 1.19+, pysam 0.22+, samtools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Pileup Generation

Generate pileup data for variant calling and position-level analysis.

"Generate pileup from BAM" → Produce per-position read summaries showing depth, bases, and qualities.

• CLI: samtools mpileup -f ref.fa input.bam
• Python: bam.pileup(chrom, start, end) (pysam)

"Count alleles at a position" → Extract per-base read support at a specific genomic coordinate.

• Python: iterate pileup_column.pileups and count bases (pysam)

What is Pileup?

Pileup shows all reads covering each position in the reference, used for:

• Variant calling (with bcftools)
• Coverage analysis
• Allele frequency calculation
• SNP/indel detection

samtools mpileup vs bcftools mpileup (Deprecation)

samtools mpileup -g/-u (BCF output for variant calling) has been deprecated since samtools 1.9 -- the genotype-likelihood code now lives in bcftools mpileup, which keeps mpileup logic versioned alongside bcftools call and avoids version-skew bugs.

Use case	Recommended tool
Quick allele counts at known sites	samtools mpileup or pysam pileup
Germline variant calling (small genomes, simple cohorts)	bcftools mpileup -> bcftools call
Germline WGS / WES production	DeepVariant or HaplotypeCaller (not mpileup)
Somatic SNV/indel	Mutect2 / VarDict / VarScan2 (direct from BAM)
Long-read small variants	clair3 / DeepVariant ONT (direct from BAM)
Long-read SV	Sniffles / cuteSV (direct from BAM)
Ultra-low-frequency (ctDNA / MRD)	fgbio consensus -> bcftools call or hot-spot Mutect2
Per-position allele counts (custom)	pysam pileup

samtools mpileup (without -g) is still the standard tool for human-readable per-position read summaries.

Basic Pileup

samtools mpileup -f reference.fa input.bam > pileup.txt

Pileup Specific Region

samtools mpileup -f reference.fa -r chr1:1000000-2000000 input.bam

Regions from BED

samtools mpileup -f reference.fa -l targets.bed input.bam

Multiple BAM Files

samtools mpileup -f reference.fa sample1.bam sample2.bam sample3.bam > pileup.txt

Output Format

Text pileup format (6 columns per sample):

chr1    1000    A    15    ...............    FFFFFFFFFFF
chr1    1001    T    12    ............      FFFFFFFFFFFF

Column	Description
1	Chromosome
2	Position (1-based)
3	Reference base
4	Read depth
5	Read bases
6	Base qualities

Read Bases Encoding

Symbol	Meaning
.	Match on forward strand
,	Match on reverse strand
ACGT	Mismatch (uppercase = forward)
acgt	Mismatch (lowercase = reverse)
^Q	Start of read (Q = MAPQ as ASCII)
$	End of read
+NNN	Insertion of N bases
-NNN	Deletion of N bases
*	Deleted base
> / <	Reference skip (intron)

Quality Filtering Options

Minimum Mapping Quality

samtools mpileup -f reference.fa -q 20 input.bam

Minimum Base Quality

samtools mpileup -f reference.fa -Q 20 input.bam

Combined Quality Filters

samtools mpileup -f reference.fa -q 20 -Q 20 input.bam

Maximum Depth (Critical Trap)

# samtools mpileup default -d 8000 silently truncates targeted / mt-DNA / amplicon / UMI-deduped data
# bcftools mpileup default -d 250 is far lower; both must be set explicitly when piping
samtools mpileup -f reference.fa -d 0 input.bam        # no cap
samtools mpileup -f reference.fa -d 1000000 input.bam  # explicit high cap

# WRONG -- samtools 8000 cap, then bcftools 250 cap re-applied
samtools mpileup -f ref.fa in.bam | bcftools call -mv

# RIGHT -- single tool, explicit -d
bcftools mpileup -d 1000000 -f ref.fa in.bam | bcftools call -mv

BAQ: Base Alignment Quality (Critical Default)

When -f ref.fa is passed, BAQ is enabled by default. BAQ Phred-scales the probability that a base is misaligned (HMM realignment over a small window) and reduces base quality near indels. Tradeoffs: ~30% slower; suppresses FP SNVs near indels; hurts indel detection sensitivity.

Flag	Behavior
(default with -f)	BAQ on (computed from CIGAR if MD missing)
-B / --no-BAQ	Disable BAQ -- raw qualities
-E / --redo-BAQ	Force recompute (after BQSR; if MD stale)

BAQ ON for: short-read germline SNV (BWA, Bowtie2, HISAT2), short-read somatic SNV.

BAQ OFF (-B) for: long-read variant calling (ONT, PacBio HiFi), SV calling, RNA-seq near splice junctions, viral / amplicon, ultra-deep ctDNA from consensus reads (consensus quality already inflated), aDNA (qualities pre-rescaled by mapDamage).

-A (count anomalous read pairs / orphans) is required for amplicon -- amplicon reads are by design not properly paired.

-aa (output all positions, including zero-coverage) is required for ARTIC SARS-CoV-2 consensus generation.

Library-Typed Flags Cheat Sheet

Library	Flags
Short-read germline WGS (BWA)	-q 20 -Q 20 -d 0 (BAQ on default)
Short-read tumor WGS	-q 1 -Q 13 -d 0 -B (low MAPQ kept; BAQ off)
Amplicon viral (ARTIC)	-aa -A -d 600000 -B -Q 20
Capture / exome	-q 20 -Q 20 -d 250
Long-read ONT R10.4+	-q 30 -Q 0 -B -d 0 --max-BQ 50
PacBio HiFi	-q 20 -Q 0 -B -d 0
RNA-seq variants	-q 20 -Q 20 -B -d 0
Forensic / aDNA	-q 0 -Q 0 -A -d 0 -B

Variant Calling Pipeline (Modern: bcftools mpileup)

Goal: Call variants from alignment data using the pileup-based approach.

Approach: Use bcftools mpileup (not samtools mpileup -g) so genotype-likelihood code is co-versioned with bcftools call. Apply quality and depth caps explicitly; annotate FORMAT fields needed for downstream filtering.

Modern Germline Calling

bcftools mpileup -f reference.fa -d 1000000 -q 20 -Q 20 \
    --annotate FORMAT/AD,FORMAT/DP,FORMAT/SP,INFO/AD \
    input.bam | \
  bcftools call -mv -Oz -o variants.vcf.gz
bcftools index -t variants.vcf.gz

Multi-Sample Joint Calling

bcftools mpileup -f reference.fa --threads 4 -d 250 -q 20 -Q 20 \
    -a FORMAT/AD,FORMAT/DP s1.bam s2.bam s3.bam | \
  bcftools call -mv --threads 4 -Oz -o joint.vcf.gz

For somatic / low-VAF, prefer Mutect2 / Strelka2 / DeepVariant -- materially better than mpileup-based callers.

Overlap Detection Defaults

When fragment length < 2 * read_length, R1 and R2 overlap. Both samtools mpileup and bcftools mpileup enable overlap detection by default (per samtools-mpileup(1)) and count overlapping bases once; pass -x/--ignore-overlaps to disable. Disabling overlap correction can inflate somatic VAFs at sites covered by overlapping pairs (especially in cfDNA / FFPE).

pysam Python Alternative

Basic Pileup

import pysam

with pysam.AlignmentFile('input.bam', 'rb') as bam:
    for pileup_column in bam.pileup('chr1', 1000000, 1001000):
        print(f'{pileup_column.reference_name}:{pileup_column.pos} depth={pileup_column.n}')

Access Reads at Position

import pysam

with pysam.AlignmentFile('input.bam', 'rb') as bam:
    for pileup_column in bam.pileup('chr1', 1000000, 1000001, truncate=True):
        print(f'Position: {pileup_column.pos}')
        print(f'Depth: {pileup_column.n}')

        for pileup_read in pileup_column.pileups:
            if pileup_read.is_del:
                print('  Deletion')
            elif pileup_read.is_refskip:
                print('  Reference skip')
            else:
                qpos = pileup_read.query_position
                base = pileup_read.alignment.query_sequence[qpos]
                qual = pileup_read.alignment.query_qualities[qpos]
                print(f'  {base} (Q{qual})')

Count Alleles at Position

import pysam
from collections import Counter

def allele_counts(bam_path, chrom, pos):
    counts = Counter()

    with pysam.AlignmentFile(bam_path, 'rb') as bam:
        for pileup_column in bam.pileup(chrom, pos, pos + 1, truncate=True):
            if pileup_column.pos != pos:
                continue

            for pileup_read in pileup_column.pileups:
                if pileup_read.is_del:
                    counts['DEL'] += 1
                elif pileup_read.is_refskip:
                    continue
                else:
                    qpos = pileup_read.query_position
                    base = pileup_read.alignment.query_sequence[qpos]
                    counts[base.upper()] += 1

    return dict(counts)

counts = allele_counts('input.bam', 'chr1', 1000000)
print(counts)  # {'A': 45, 'G': 5}

Calculate Allele Frequency

import pysam
from collections import Counter

def allele_frequency(bam_path, chrom, pos, min_qual=20):
    counts = Counter()

    with pysam.AlignmentFile(bam_path, 'rb') as bam:
        for pileup_column in bam.pileup(chrom, pos, pos + 1, truncate=True,
                                         min_base_quality=min_qual):
            if pileup_column.pos != pos:
                continue

            for pileup_read in pileup_column.pileups:
                if pileup_read.is_del or pileup_read.is_refskip:
                    continue
                qpos = pileup_read.query_position
                base = pileup_read.alignment.query_sequence[qpos]
                counts[base.upper()] += 1

    total = sum(counts.values())
    if total == 0:
        return {}

    return {base: count / total for base, count in counts.items()}

freq = allele_frequency('input.bam', 'chr1', 1000000)
for base, f in sorted(freq.items(), key=lambda x: -x[1]):
    print(f'{base}: {f:.1%}')

Pileup with Quality Filtering

import pysam

with pysam.AlignmentFile('input.bam', 'rb') as bam:
    for pileup_column in bam.pileup('chr1', 1000000, 1001000,
                                     truncate=True,
                                     min_mapping_quality=20,
                                     min_base_quality=20):
        print(f'{pileup_column.pos}: {pileup_column.n}')

Generate Pileup Text

import pysam

def pileup_text(bam_path, ref_path, chrom, start, end):
    with pysam.AlignmentFile(bam_path, 'rb') as bam:
        with pysam.FastaFile(ref_path) as ref:
            for pileup_column in bam.pileup(chrom, start, end, truncate=True):
                pos = pileup_column.pos
                ref_base = ref.fetch(chrom, pos, pos + 1)
                depth = pileup_column.n

                bases = []
                for pileup_read in pileup_column.pileups:
                    if pileup_read.is_del:
                        bases.append('*')
                    elif pileup_read.is_refskip:
                        bases.append('>')
                    else:
                        qpos = pileup_read.query_position
                        base = pileup_read.alignment.query_sequence[qpos]
                        if base.upper() == ref_base.upper():
                            bases.append('.' if not pileup_read.alignment.is_reverse else ',')
                        else:
                            bases.append(base.upper() if not pileup_read.alignment.is_reverse else base.lower())

                print(f'{chrom}\t{pos+1}\t{ref_base}\t{depth}\t{"".join(bases)}')

pileup_text('input.bam', 'reference.fa', 'chr1', 1000000, 1000100)

Pileup Options Summary

Option	Description	Common pitfall
-f FILE	Reference FASTA	Triggers BAQ ON by default
-r REGION	Restrict to region
-l FILE	BED file of regions
-q INT	Min mapping quality	Aligner-dependent semantics
-Q INT	Min base quality	-Q 0 with default overlap detection has subtle behavior
-d INT	Max depth	Default 8000 silently truncates; bcftools mpileup default is 250
-B	Disable BAQ	Often correct for long reads, SV, viral, consensus
-A	Count anomalous pairs	Required for amplicon
-aa	Output all positions	Required for consensus generation
--ignore-overlaps	Disable mate-overlap correction	Rarely correct
--max-BQ INT	Cap BQ (default 60)	Useful for ONT (Q values inflated)
-g (DEPRECATED)	Old BCF output	Use bcftools mpileup instead

Quick Reference

Task	Command
Basic pileup	samtools mpileup -f ref.fa in.bam
Quality filter	samtools mpileup -f ref.fa -q 20 -Q 20 in.bam
Region	samtools mpileup -f ref.fa -r chr1:1-1000 in.bam
To bcftools	bcftools mpileup -f ref.fa -d 1000000 in.bam | bcftools call -mv

Common Errors

Error	Cause	Solution
No FASTA reference	Missing -f option	Add -f reference.fa
Reference mismatch	Wrong reference	Use same reference as alignment
Out of memory	High coverage region	Use -d to cap depth

Related Skills

• alignment-filtering - Filter BAM before pileup
• reference-operations - Index reference for pileup; M5 cross-check
• bam-statistics - mosdepth, depth tool selection
• variant-calling/variant-calling - Full variant calling workflows
• variant-calling/vcf-basics - VCF/BCF I/O
• variant-calling/joint-calling - Multi-sample joint calling