LncRNAs2Pathways – Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method

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, researchers from Harbin Medical University 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. The researchers have described the LncRNAs2Pathways methodology and illustrated its effectiveness by analyzing three lncRNA sets associated with glioma, prostate and pancreatic cancers. They further analyzed the reproducibility and robustness and compared their results with those of two other methods. Based on these analyses, they showed that LncRNAs2Pathways can effectively identify the functional pathways associated with lncRNA sets.

Flow diagram of LncRNAs2Pathways

lncRNA

Step 1. RNA-Seq data and protein–protein interaction data are integrated to construct a CNC network. Step 2. A set of lncRNAs of interest are mapped to the gene correlation network, and the global network propagation algorithm is used to calculate the propagation scores of protein-coding genes, which reflect the extent of the genes influenced by the lncRNAs. A ranked protein-coding gene list is constructed according to the propagation scores. Step 3. Protein-coding genes in a given pathway are mapped to the ranked protein-coding gene list, and the ES(P) is calculated by walking down the list. The permutation test is performed to identify the statistically significant pathways.

Availability – LncRNAs2Pathways is freely available as an R-based tool: https://cran.r-project.org/web/packages/LncPath/

Han J, Liu S, Sun Z, Zhang Y, Zhang F, Zhang C, Shang D, Yang H, Su F, Xu Y, Li C, Ren H, Li X. (2017) LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method. Sci Rep 7:46566. [article]

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