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Updated: Jun 15, 2026

qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes

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Published on: March 6, 2019

The Portable Microhaplotype Object and Tools.

Nicholas J Hathaway¹, Kathryn Murie¹, Maxwell Murphy¹

¹EPPIcenter program, Division of HIV, ID, and Global Medicine, University of California, San Francisco, USA.

Biorxiv : the Preprint Server for Biology

|December 22, 2025

Summary

This summary is machine-generated.

A new standard for targeted sequencing data, the Portable Microhaplotype Object (PMO), enables efficient storage and sharing of microhaplotype data. This promotes data interoperability and accelerates the development of analysis tools for research and public health.

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Area of Science:

Genomics
Bioinformatics
Data Science

Background:

The increasing volume of targeted sequencing data necessitates standardized formats for effective data management.
Current data storage solutions are disparate, hindering data sharing, reuse, and the development of interoperable analysis tools.

Purpose of the Study:

To introduce a standardized, efficient, and lossless format for storing phased targeted sequencing data (microhaplotypes).
To facilitate data sharing, reuse, and the development of harmonized analysis tools in genomics research.

Main Methods:

Development of the Portable Microhaplotype Object (PMO) format, a JSON-based standard for genetic data and metadata.
Creation of pmotools-python, an open-source package for PMO data manipulation.
Development of a web-based application for easy PMO file creation from tabular data.

Main Results:

The PMO format provides efficient, relational storage of microhaplotype data with comprehensive metadata.
The associated software tools and web app simplify PMO data creation and management.
Demonstrated broad applicability across diverse organisms including *Plasmodium*, *Anopheles*, *Escherichia coli*, and *Staphylococcus aureus*.

Conclusions:

The PMO format and associated tools offer a standardized solution for targeted sequencing data.
PMO adoption will streamline data sharing, enhance interoperability, and accelerate genomic research.
The project resources are openly available to promote widespread use and collaboration.