看到了一篇利用公共转录组数据构建基因共表达网络的论文，研究的物种是桃子
Exploring large-scale gene coexpression networks in peach (Prunus persica L.): a new tool for predicting gene function
https://academic.oup.com/hr/article/11/2/uhad294/7505277?login=false
这篇论文里提到了一篇参考论文
Aggregated gene co-expression networks for predicting transcription factor regulatory landscapes in a non-model plant species
这篇论文里研究的是葡萄的基因共表达网络，用到的也是公共的转录组数据，这篇论文里提供了构建共表达网络的代码
https://github.com/Tomsbiolab/agg_WGCN
用的并不是WGCNA，具体的方法我还没有看明白，有一部分是评估共表达网络的表现，在论文的方法部分写到
Network functional connectivity (i.e., performance) across all genes was assessed by neighbor-voting, a machine learning algorithm based on the guilt-by-association principle, which states that genes sharing common functions are often coordinately regulated across multiple experiments (Verleyen et al., 2015). The evaluation was performed using the EGAD R package
提到的R包的githu主页
https://github.com/sarbal/EGAD
这个R包对应的论文
EGAD: ultra-fast functional analysis of gene networks
https://academic.oup.com/bioinformatics/article/33/4/612/2664343?login=false
对应的github主页上有对应的示例代码，用到的是人类的数据，如何将自己的数据准备成能用于分析的格式，暂时没有想明白
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