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TSUMUGI: a platform for phenotype-driven gene network identification from comprehensive knockout mouse phenotyping data

Akihiro KunoiD, Kinari MatsumotoiD, Taito TakiiD, Satoru TakahashiiD, Seiya MizunoiD

Abstract

SummaryDeciphering complex organismal phenotypes requires elucidation of coordinated functions among multiple genes, yet this remains a fundamental challenge in functional genetics. The International Mouse Phenotyping Consortium (IMPC) has recently established a comprehensive phenotypic atlas based on systematic single-gene knockout mouse lines, providing an unprecedented resource for gene-phenotype associations in mammals. However, extracting phenotype-associated multiple gene relationships remains challenging. Here, we present TSUMUGI, a platform that identifies a phenotype-driven gene network by leveraging gene-phenotype associations from the IMPC. TSUMUGI enables users to initiate analyses from a user-specified phenotype or gene list and interactively explore a gene network. In addition, TSUMUGI highlights human disease-associated genes, supports flexible network filtering, and allows seamless export of a gene network for downstream analyses. By linking shared phenotypic signatures to putative functional gene modules, TSUMUGI provides a framework for systematic interpretation and hypothesis generation of complex organismal phenotypes. Availability and implementationThe web application is available online at https://larc-tsukuba.github.io/tsumugi/. The command-line tools are distributed via PyPI (https://pypi.org/project/TSUMUGI) and Bioconda (https://bioconda.github.io/recipes/tsumugi/README.html). Source code and documentation are hosted at GitHub (https://github.com/akikuno/TSUMUGI-dev) and archived on Zenodo (https://doi.org/10.5281/zenodo.18464478) under the MIT license.

PDFDOICode

02 /Specification & Classification

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