lncGSEA

lncGSEA predicts lncRNA-associated pathways by applying Gene Set Enrichment Analysis (GSEA) to large-scale cancer patient transcriptome data to infer potential regulatory roles of long non-coding RNAs (lncRNAs) in cancer.

Key Features:

• Gene Set Enrichment Analysis (GSEA): applies GSEA to gene expression profiles to identify predefined gene sets that are enriched with respect to lncRNA-associated expression patterns.
• Clinical transcriptome data: leverages large-scale cancer patient gene expression profiles derived from clinical datasets to perform pathway inference from patient samples.
• Pathway inference for specific lncRNAs: predicts pathways potentially regulated by individual lncRNAs by associating lncRNA expression with enrichment of gene sets.
• Recapitulation of literature-supported pathways: reproduces known lncRNA-associated pathways that are supported by existing literature and experimental validations across multiple cancer types.
• Inference without perturbation experiments: infers potential regulatory roles of lncRNAs from observational patient transcriptomes without requiring knock-down or overexpression experiments.

Scientific Applications:

• lncRNA prioritization: identify and prioritize lncRNAs with potential regulatory roles in cancer-related pathways based on patient transcriptome associations.
• Hypothesis generation: generate hypotheses about lncRNA functions through inferred pathway associations derived from clinical gene expression data.
• Complementary analysis to experiments: provide bioinformatics-driven insights that complement knock-down, overexpression, and other experimental studies of lncRNA function.

Methodology:

Apply Gene Set Enrichment Analysis (GSEA) to patient-derived cancer gene expression profiles to associate lncRNA expression with enriched gene sets and infer lncRNA-associated pathways.