VCNet: vector-based gene co-expression network construction and its application to RNA-seq data. Results: We develop an algorithm called VCNet to construct GCN from RNA-seq data to overcome this dimensional problem. VCNet performs a new statistical hypothesis test based on the correlation matrix of a gene–gene pair using the Frobenius norm. The asymptotic distribution of the new test is obtained under the null model. Simulation studies demonstrate that VCNet outperforms SpliceNet and RNASeqNet for detecting edges of GCN. We also apply VCNet to two expression datasets from TCGA database: the normal breast tissue and kidney tumour tissue, and the results show that the GCNs constructed by VCNet contain more biologically meaningful interactions than existing methods.

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  1. Tyler Grimes, Somnath Datta: SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data (2021) not zbMATH