vmwhere 0.2.1

Genotyping and sequence-resolved allele calling for tandem repeat regions

variant motif where? variant motif here!

vmwhere (VariantMotifwhere) is a tool for analyzing tandem repeat (microsatellite) regions from long-read sequencing data. It provides three core capabilities:

1. Discovery — identify microsatellite coordinates in a reference genome
2. Genotyping — call allele length, repeath length, and motif-level sequence decomposition at each locus
3. Visualization — generate sequence-resolved allele frequency plots

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Installation

VMwhere is available as a Python package:

pip install vmwhere

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Requirements

• Python >= 3.12.4

• R (>= 4.0) — required only for the visualize subcommand. Install required R packages:

  Rscript -e "install.packages(readLines('requirements-r.txt'), repos='https://cloud.r-project.org')"
  

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Usage

1. Find microsatellites

Scan a reference FASTA for tandem repeat regions matching a given motif.

vmwhere find \
  --motif GGAA \
  --perfect_repeats 4 \
  --max_gap 50 \
  --buffer_size 50 \
  --fasta data/reference.fasta \
  --output_dir output/

This outputs a BED file (microsatellite_coordinates.bed) with columns: chr, start, end, region_id, motif.

Parameters

Flag	Description
--motif / -m	Repeat motif sequence to search for (e.g., GGAA)
--fasta / -f	Path to the reference genome FASTA
--output_dir / -o	Output directory
--perfect_repeats / -r	Minimum number of uninterrupted tandem repeats to call a microsatellite (default: 2)
--max_gap / -g	Maximum base pairs between adjacent microsatellites before they are treated as distinct loci (default: 50)
--buffer_size / -b	Base pairs to extend beyond the outermost repeat on each side (default: 50)

See examples/run_vmwhere_find.sh for a runnable example.

2. Genotype microsatellites

Extract reads overlapping each locus, decompose sequences into motif and non-motif segments, cluster reads by Levenshtein distance, and call alleles.

vmwhere genotype \
  --sample_id example_sample \
  --bed_file data/T2T_regions.bed \
  --bam_file data/A673_sampled_reads.sorted.bam \
  --fasta data/GCF_009914755.1_T2T-CHM13v2.0_chr6_chr10.fasta \
  --cluster_distance 4 \
  --minor_threshold 0.20 \
  --major_threshold 0.80 \
  --output_dir output/ \
  --num_processes 2

See examples/run_vmwhere_genotype.sh for a runnable example.

Parameters

Required:

Flag	Description
--sample_id	Sample identifier (used in output filename)
--bam_file	Path to sorted, indexed BAM file
--fasta	Path to the reference genome FASTA
--bed_file	Headerless BED file with columns: chr, start, end, region_id, motif
--output_dir	Output directory (file will be named <sample_id>_vmwhere_results.tsv)

Optional:

Flag	Description	Default
--cluster_distance	Maximum Levenshtein distance for grouping reads into a cluster	0
--minor_threshold	Minimum read support fraction to call a minor allele	0.20
--major_threshold	Minimum read support fraction to call a homozygous genotype	0.80
--num_processes	Number of parallel processes	24

Output TSV columns

The output follows VCF-style conventions but is written as a TSV for simpler parsing.

Column	Description
CHROM	Chromosome
POS	Start coordinate of the microsatellite
ID	Locus identifier from the input BED file
REF	Reference allele sequence
ALT	Alternate allele sequence(s); . if none
END	End coordinate of the microsatellite
MOTIF	Canonical repeat motif
GT	Genotype (e.g., 0/0 = homozygous reference, 0/1 = heterozygous)
AL	Allele length in base pairs
CN	Total copy number of the canonical motif (consecutive and interrupted occurrences)
CNM	Maximum uninterrupted copy number of the canonical motif (e.g., 6GGAA_1GGAT_2GGAA = 6)
MD	Motif density — fraction of allele base pairs matching the canonical motif
DS_READ	Decomposed sequence of the allele
DS_REF	Decomposed sequence of the reference
RS	Read support for the allele

3. Visualize alleles at a microsatellite

Generate a PDF showing sequence-resolved allele structures and their frequencies at a given locus.

vmwhere visualize \
  --genotype_tsv output/example_sample_vmwhere_results.tsv \
  --microsatellite_id chr6_region_41 \
  --min_allele_count 0 \
  --output_pdf output/chr6_region_41_visualization.pdf

See examples/run_vmwhere_visualize.sh for a runnable example.