Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2019 Aug 8;10:701. doi: 10.3389/fgene.2019.00701

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

Copyright © 2019 Lima, Auffret, Stewart, Dewhurst, Duthie, Snelling, Walker, Freeman, Watson and Roehe

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

PMC Copyright notice

Correlation network analysis of metagenomic data: Each node represents a vector of relative abundances of each microbial gene in all 42 animals, and the edges represent a correlation between the microbial genes. A minimum correlation threshold of 0.80 was applied to the network. Different colors illustrate different clusters, which were calculated using MCL method (inflation: 2; preinflation: 2; scheme: 6). Clusters identified by numbers were found to be significantly (P < 0.05) enriched for microbial genes identified for the traits whose abbreviations are between brackets (FCR, feed conversion ratio; ADG, average daily gain; RFI, residual feed intake; DFI, daily feed intake; FCR&ADG, set including microbial genes identified for prediction of either FCR and/or ADG; RFI&DFI, set including microbial genes identified for prediction of RFI and/or DFI; FCR+ADG, set including microbial genes simultaneously identified for prediction of both traits FCR and ADG).