# Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

## TL;DR

Co-LncRNA is a web tool that helps researchers explore how combinations of long non-coding RNAs affect biological functions and pathways using RNA-Seq data.

## Contribution

The tool introduces a method to analyze the combinatorial effects of lncRNAs on GO annotations and KEGG pathways through co-expressed genes.

## Key findings

- Co-LncRNA identifies co-expressed protein-coding genes of lncRNAs across 241 RNA-Seq datasets.
- The tool enables enrichment analysis of multiple lncRNAs in user-selected datasets to reveal combinatorial effects.
- It provides visual pathway overviews and network displays between lncRNAs and their co-expressed genes.

## Abstract

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community.

Database URL: http://www.bio-bigdata.com/Co-LncRNA/