An atlas of evidence-based phenotypic associations across the mouse phenome.

Scientific Reports
Nobuhiko Tanaka, Hiroshi Masuya

Abstract

To date, reliable relationships between mammalian phenotypes, based on diagnostic test measurements, have not been reported on a large scale. The purpose of this study was to present a large mouse phenotype-phenotype relationships dataset as a reference resource, alongside detailed evaluation of the resource. We used bias-minimized comprehensive mouse phenotype data and applied association rule mining to a dataset consisting of only binary (normal and abnormal phenotypes) data to determine relationships among phenotypes. We present 3,686 evidence-based significant associations, comprising 345 phenotypes covering 60 biological systems (functions), and evaluate their characteristics in detail. To evaluate the relationships, we defined a set of phenotype-phenotype association pairs (PPAPs) as a module of phenotypic expression for each of the 345 phenotypes. By analyzing each PPAP, we identified phenotype sub-networks consisting of the largest numbers of phenotypes and distinct biological systems. Furthermore, using hierarchical clustering based on phenotype similarities among the 345 PPAPs, we identified seven community types within a putative phenome-wide association network. Moreover, to promote leverage of these data, we develo...Continue Reading

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Citations

Jan 19, 2021·Laboratory animal research·Hiroshi MasuyaTatsuya Kushida
Sep 6, 2021·Mammalian Genome : Official Journal of the International Mammalian Genome Society·Hsian-Jean ChinChi-Kuang Leo Wang

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Methods Mentioned

BETA
gene knock-out

Software Mentioned

R package dendextend
R package cp4p
R
R package PerformanceAnalytics
VisNetwork
R package gplots
R package pvclust
shiny
arules
cd

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