lncRna

lncRna provides a complete workflow for the identification, analysis, and functional annotation of long non-coding RNAs (lncRNAs) from RNA-Seq data.

Key Features:

• Transcript Filtering: Filters transcripts from GTF files to prepare data for lncRNA analysis.
• Coding Potential Prediction: Evaluates the performance of multiple coding potential prediction tools including CPC2, PLEK, and CPAT.
• Consensus Analysis: Summarizes agreement between tools through systematic performance analysis of individual tools, "at least N" tool consensus, and all possible tool combinations.
• Functional Interaction Analysis: Identifies potential cis- and trans-acting interactions with protein-coding genes.
• Enrichment Analysis: Supports functional analysis through enrichment analysis following interaction identification.
• Visualization: Generates radar plots, clock plots, and interactive Sankey diagrams for results.

Scientific Applications:

• lncRNA Identification: Identifies long non-coding RNAs from RNA-Seq transcriptome data by filtering and coding potential assessment.
• Coding Potential Benchmarking: Systematically evaluates and compares multiple computational tools for predicting transcript coding potential.
• lncRNA Functional Annotation: Annotates lncRNA function through cis- and trans-acting interaction prediction with protein-coding genes and subsequent enrichment analysis.

Methodology:

The workflow filters transcripts from GTF files, evaluates coding potential using CPC2, PLEK, and CPAT with consensus strategies, identifies cis- and trans-acting interactions with protein-coding genes, and performs enrichment analysis.