STRhub

Tools & Pipelines

Comprehensive suite of bioinformatics tools and pipelines for STR analysis, from raw data processing to population genetics.

Contribute a tool or tutorial

Analysis Tools

STRidER
Curated online STR allele-frequency population database providing high-quality genotype probability estimates and autosomal STR quality control.
Multi-platform
QC / Database
Online tool

Key Features:

  • • High-quality curated allele frequencies
  • • Genotype probability estimates
  • • Quality control for autosomal STR data
  • • Developed at the Institute of Legal Medicine, Medical University of Innsbruck
Input: STR datasets
Output: QC reports / frequency data
Website
STRNaming
Unbiased method to automatically generate short, informative, and human-readable descriptions of STR alleles.
Multi-platform
Annotation
Online tool

Key Features:

  • • Standardized allele naming
  • • Automated allele description
  • • Developed by the Netherlands Forensic Institute
Input: STR sequence
Output: Allele nomenclature
Website
HipSTR
Tool for genotyping short tandem repeats from Illumina sequencing data
Illumina
Short-read
Genotyping
Runs locally
Graphical interface

Key Features:

  • • High accuracy
  • • Handles complex STRs
  • • Population-scale analysis
Input: BAM/CRAM + reference
Output: VCF
GitHubOriginal publicationUser interface publication
STRspy
Python toolkit for STR analysis, allele profiling, and visualization.
ONT
Long-read
Genotyping
Runs locally

Key Features:

  • • STR profiles genotyping
  • • Statistical analysis of allele patterns
  • • Easy integration with bioinformatics pipelines
  • • Open-source toolkit
Input: FASTQ/BAM
Output: STR profile / tables
GitHubOriginal publication
GangSTR
Tool for genome-wide profiling of tandem repeats from short reads
Illumina
Short-read
Genotyping
Runs locally

Key Features:

  • • Genome-wide analysis
  • • Short read support
  • • High throughput
Input: BAM
Output: VCF
GitHubOriginal publication
STRait Razor
Lightweight motif-matching tool for Illumina-based forensic STR analysis. Suitable for teaching and training purposes in STR interpretation.
Illumina
Short-read
Genotyping
Runs locally
Online tool
Graphical interface

Key Features:

  • • Direct motif matching from FASTQ
  • • Lightweight algorithm for forensic panels
  • • Online web interface available
  • • Integrated into STRhub for Illumina-based pipelines
Input: FASTQ
Output: Allele calls / tables
GitHubOnline VersionOriginal publication
NanoMnT
STR genotyping from Oxford Nanopore alignments with allele and locus tables.
ONT
Long-read
Genotyping
Runs locally

Key Features:

  • • STR genotyping from BAM alignments
  • • Allele and locus-level output tables
  • • Designed for Nanopore long-read data
  • • Open-source pipeline
Input: BAM
Output: Allele/locus tables
GitHubOriginal publication
STRkit
Long-read STR genotyping with Gaussian models, confidence intervals, and phasing.
ONT
Long-read
Genotyping
Runs locally

Key Features:

  • • Gaussian model for allele length estimation
  • • Confidence intervals and bootstrapping
  • • Phasing with SNVs
  • • Expansion and complex repeat support
  • • Optimized for ONT R10 chemistry
Input: BAM/FASTQ
Output: Genotypes + confidence
GitHubOriginal publication
NASTRA
Structure-aware, reference-free STR caller for forensic markers.
ONT
Long-read
Genotyping
Runs locally

Key Features:

  • • Structure-aware STR calling
  • • Reference-free approach
  • • Forensic STR marker support
  • • Parallelizable pipeline
  • • Validated on cell line data
Input: FASTQ/BAM
Output: Forensic STR calls
GitHubOriginal publication
NanoSTR
Targeted STR typing from Nanopore reads with read-length ranking.
ONT
Long-read
Genotyping
Runs locally

Key Features:

  • • Targeted STR typing from FASTQ
  • • Read length ranking for allele inference
  • • Fast execution
  • • Custom BED panel support
Input: FASTQ
Output: Allele calls
GitHubOriginal publication

Essential Bioinformatics Commands

Essential Read Processing Commands

For cleaning, filtering, and preparing FASTQ reads before genotyping.

Key Features:
  • • Trim adapters and low-quality bases
  • • Filter out too-short or poor-quality reads
  • • Prepare clean FASTQ files for alignment

Trimmomatic

trimmomatic PE sample_R1.fastq sample_R2.fastq \
  output_R1_paired.fastq output_R1_unpaired.fastq \
  output_R2_paired.fastq output_R2_unpaired.fastq \
  ILLUMINACLIP:adapters.fa:2:30:10 SLIDINGWINDOW:4:20 MINLEN:50

fastp

fastp -i sample_R1.fastq -I sample_R2.fastq \
      -o clean_R1.fastq -O clean_R2.fastq \
      --detect_adapter_for_pe --html report.html

Alignment & BAM Processing Essentials

For aligning reads and generating ready-to-analyze BAM files.

Key Features:
  • • High-quality alignment
  • • Sorting and indexing
  • • BAM cleanup operations

BWA-MEM2 alignment

bwa-mem2 mem reference.fasta sample_R1.fastq sample_R2.fastq > sample.sam

Convert / sort / index

samtools view -bS sample.sam | samtools sort -o sample.sorted.bam
samtools index sample.sorted.bam

Remove duplicates

samtools rmdup sample.sorted.bam sample.rmdup.bam

Inspecting STR Regions & Coverage

For exploring coverage, flanking regions, and STR quality signals.

Key Features:
  • • Visualize STR flanking regions
  • • Inspect soft-clips and misalignments
  • • Evaluate STR coverage depth

Depth coverage

samtools depth -r chr12:100000-100300 sample.bam > depth.txt

Region inspection

samtools view sample.bam chr12:100000-100300

Quick visualization

samtools tview sample.bam reference.fasta

Nanopore (ONT) Essentials

Minimal pipeline from raw ONT signals to aligned reads.

Key Features:
  • • Basecall POD5 → reads (unaligned BAM)
  • • Align, sort & index BAM (minimap2 + samtools)
  • • QC metrics with NanoPlot

Basecalling (POD5 → BAM)

dorado basecaller dna_r10.4.1_e8.2_400bps_sup pod5/ > reads.bam

Alignment to hg38

samtools fastq reads.bam | minimap2 -ax map-ont hg38.fa - | samtools sort -o aln.bam - && samtools index aln.bam

QC with NanoPlot

NanoPlot --bam aln.bam --outdir nanoplot_out/

Installation Requirements

The tools shown above do not come pre-installed. To run these commands, you need to install the corresponding bioinformatics utilities according to your operating system.

Linux (Ubuntu/Debian)

sudo apt update && sudo apt install samtools bcftools minimap2 trimmomatic fastp

macOS (Homebrew)

brew install samtools bcftools minimap2 fastp
brew install --cask trimmomatic

Bioinformatics tools are not supported natively on Windows. Use WSL2 (Ubuntu) or a Linux container for full compatibility.

Windows (WSL2 recommended)

sudo apt update && sudo apt install samtools bcftools minimap2 trimmomatic fastp

Long-read tools may require Python ≥ 3.8 and sufficient disk space for basecalling models.

Dorado installation depends on your platform and GPU availability; obtain precompiled binaries from Oxford Nanopore releases.

Nanopore utilities (POD5 tools, NanoPlot, pycoQC)

pip install pod5 nanoplot pycoqc

A full step-by-step installation guide for each OS will be added soon.

Interactive Tutorials