The example visualization using the biotextgraph package. (A) The overview of the workflow using the package. (B) The summarization using a correlation network obtained using the queries of interested gene identifiers (symbol) and RefSeq summary obtained by analyzing RNA-seq dataset of BKPyV infection in RPTEC, with the candidate genes related to high-frequent words. The result was compared to the other network derived from analyzing the other cells. (C) Bayesian network of gene clusters obtained from the RNA-seq dataset of bladder cancer was annotated using the package and exported to interactive visualization with Cytoscape.js. Wordclouds inside the nodes correspond to textual information in the cluster, and edge width corresponds to the strength of interaction. The dendrogram representing how the words are distributed across branches, which can be used not only for the gene identifiers but for microbial taxa.