Abstract
Long non-coding RNAs (lncRNAs) have been demonstrated to play essential roles in diverse cellular processes and biological functions. Exploring the functions associated with lncRNAs may help provide insight into their underlying biological mechanisms. The current methods primarily focus on investigating the functions of individual lncRNAs; however, essential biological functions may be affected by the combinatorial effects of multiple lncRNAs. Here, we have developed a novel computational method, LncRNAs2Pathways, to identify the functional pathways influenced by the combinatorial effects of a set of lncRNAs of interest based on a global network propagation algorithm. A new Kolmogorov–Smirnov-like statistical measure weighted by the network propagation score, which considers the expression correlation among lncRNAs and coding genes, was used to evaluate the biological pathways influenced by the lncRNAs of interest. We have described the LncRNAs2Pathways methodology and illustrated its effectiveness by analyzing three lncRNA sets associated with glioma, prostate and pancreatic cancers. We further analyzed the reproducibility and robustness and compared our results with those of two other methods. Based on these analyses, we showed that LncRNAs2Pathways can effectively identify the functional pathways associated with lncRNA sets. Finally, we implemented this method as a freely available R-based tool.
Highlights
Long non-coding RNAs have been demonstrated to play essential roles in diverse cellular processes and biological functions
The main steps consist of (1) constructing the coding gene correlation (CNC) network by integrating RNA-Seq data and protein–protein interaction data, (2) estimating the extent of protein-coding genes influenced by the set of Long non-coding RNAs (lncRNAs) of interest based on a global network propagation algorithm, and (3) calculating pathway enrichment scores (ESs) to evaluate the biological pathways
Our study is the first to predict probable functions regulated by the combinatorial effects of a set of lncRNAs of interest based on a global network propagation strategy
Summary
Long non-coding RNAs (lncRNAs) have been demonstrated to play essential roles in diverse cellular processes and biological functions. We further analyzed the reproducibility and robustness and compared our results with those of two other methods Based on these analyses, we showed that LncRNAs2Pathways can effectively identify the functional pathways associated with lncRNA sets. LncRNA2Function first investigates the expression correlation between lncRNAs and protein-coding genes across the RNA-Seq data of 19 human normal tissues and performs the hypergeometric test to functionally annotate a set of lncRNAs with significantly enriched functional terms among the protein-coding genes co-expressed with the lncRNAs. Zhao et al.[19] introduced Co-LncRNA, a web-based computational tool that provides enrichment analyses of lncRNAs for Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.
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