Guidance for RNA-seq co-expression network construction and analysis: safety in numbers
Guidance for RNA-seq co-expression network construction and analysis: safety in numbers
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DOI：
10.1093/bioinformatics/btv118
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发表时间：
2015-07-01
期刊：
影响因子：
5.8
通讯作者：
Gillis, J.
中科院分区：
文献类型：
--
作者：
Ballouz, S.;Verleyen, W.;Gillis, J.
动机：RNA-seq共表达分析尚处于起步阶段，合理的实践仍然定义不清。我们评估了各种RNA-seq表达数据，以确定影响功能连接和拓扑结构的因素，在co-expression networks.Results：我们检查RNA-seq共表达数据产生的1970 RNA-seq样本使用内疚的关联框架，其中基因进行评估的趋势，共表达，以反映共享的功能。获得与微阵列相当的性能的最低实验标准是>20个样品，每个样品读取深度> 10 M。虽然构建的聚合网络显示出良好的性能（接收器操作者特征曲线下的面积类似于0.71），但对所用实验数量的依赖性与微阵列中存在的依赖性几乎相同，这表明需要数千个样品来获得“金标准”共表达。我们发现RNA-seq和微阵列共表达之间的主要拓扑差异是由于每种技术中表达噪声相关性的变化而导致每个网络中枢纽样基因之间的低重叠。
Motivation: RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks.Results: We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are assessed for the tendency of co-expression to reflect shared function. Minimal experimental criteria to obtain performance on par with microarrays were >20 samples with read depth >10M per sample. While the aggregate network constructed shows good performance (area under the receiver operator characteristic curve similar to 0.71), the dependency on number of experiments used is nearly identical to that present in microarrays, suggesting thousands of samples are required to obtain 'gold-standard' co-expression. We find a major topological difference between RNA-seq and microarray co-expression in the form of low overlaps between hub-like genes from each network due to changes in the correlation of expression noise within each technology.