Making STR Research
Simpler

A public research platform dedicated to promoting the STRprofiler tool, supporting life science research, and advancing genetic analysis technology.

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Joined by 200+ research teams worldwide

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STRprofiler is intended only for research purposes.

Our Core Values

Dedicated to making life science research tools more accessible and easier to use, promoting inclusive scientific advancement

Tool Accessibility

Lowering the barrier to STR analysis technology, enabling more researchers to use professional tools conveniently and accelerating research progress.

Knowledge Sharing

Building an open knowledge community to share STR analysis experiences, case studies, and best practices, fostering research collaboration.

Public Research Support

Providing free resources and technical support to grassroots research institutions and student teams, promoting balanced development in life science research.

About STRprofiler

STRprofiler is a professional tool for analyzing the similarity of Short Tandem Repeat (STR) profiles, widely used in genetics, forensics, and molecular biology research.

Important Notice

STRprofiler is intended only for research purposes. This tool should not be used for clinical diagnosis, forensic identification, or other formal application scenarios.

Core Features

  • Calculate similarity scores for STR profiles from different samples
  • Provide three different scoring algorithms to meet diverse research needs
  • Support custom parameter settings, such as including Amelogenin marker analysis
  • Generate detailed sample analysis reports to assist research decisions

Similarity Scoring Algorithms

1. Tanabe (Sørenson-Dice Coefficient)

score = (2 × number of shared alleles) / (number of query alleles + number of reference alleles)

Balances differences in gene counts between two samples, comprehensively measuring overall overlap, suitable for scenarios requiring fair comparison.

2. Masters (vs. Query Sample)

score = number of shared alleles / number of query alleles

Calculates the proportion of alleles shared between the reference and query samples relative to the query sample, reflecting reference coverage of the query.

3. Masters (vs. Reference Sample)

score = number of shared alleles / number of reference alleles

Calculates the proportion of alleles shared between the query and reference samples relative to the reference sample, representing query coverage of the reference.

Amelogenin markers are not included in scoring by default. To include them in analysis, use the --score_amel parameter.

User Guide

Quickly master STRprofiler installation and basic usage to start your research analysis

Installing STRprofiler

1 System Requirements

  • Linux or macOS operating system
  • Python 3.6 or higher
  • Git version control tool

2 Clone Repository

git clone https://github.com/example/strprofiler.git

3 Install Dependencies

cd strprofiler
pip install -r requirements.txt

4 Verify Installation

python strprofiler.py --version

If installation is successful, the current STRprofiler version number will be displayed

Complete Documentation

View the full user manual and API documentation to learn more about advanced features and usage tips.

Download Complete Documentation

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