LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

BMC Genomics. 2021 Jul 27;22(1):574. doi: 10.1186/s12864-021-07900-y.


Background: Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs.

Results: As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types.

Conclusions: LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA .

Keywords: Cancer transcriptome; GSEA; Long non-coding RNA; Pathway analysis; RNA-seq; TCGA.

MeSH terms

  • Gene Expression Profiling
  • Humans
  • Microarray Analysis
  • Neoplasms* / genetics
  • RNA, Long Noncoding* / genetics
  • Transcriptome


  • RNA, Long Noncoding