ETENLNC

ETENLNC identifies and annotates long non-coding RNAs (lncRNAs) from RNA-Seq data and predicts their regulatory interactions to support studies of gene regulation and genomic integrity.

Key Features:

• Raw RNA-Seq processing: Processes raw RNA-Seq data to generate transcript candidates for downstream analysis.
• Known and novel lncRNA identification: Identifies both annotated (known) and novel long non-coding RNAs (lncRNAs).
• Six-step filtration: Applies six stringent filtration steps to identify novel lncRNAs with high accuracy.
• Differential expression analysis: Performs differential expression analysis for mRNA and lncRNA transcripts.
• Regulatory interaction prediction: Predicts regulatory interactions involving lncRNAs, mRNAs, miRNAs, and proteins.
• Benchmarking: Benchmarked against six existing tools using data from three different species.

Scientific Applications:

• Genome-wide lncRNA discovery: Enables discovery of known and novel lncRNAs from RNA-Seq experiments.
• Differential expression studies: Supports comparative analyses of mRNA and lncRNA expression across conditions or treatments.
• Regulatory network inference: Facilitates inference of molecular networks among lncRNAs, mRNAs, miRNAs, and proteins.
• Cross-species benchmarking: Allows comparative evaluation of lncRNA analysis methods using multi-species datasets.
• Study of gene regulation and genomic integrity: Aids investigation of lncRNA roles in gene regulation and genomic integrity.

Methodology:

Processes raw RNA-Seq data; applies six stringent filtration steps to identify novel lncRNAs; conducts differential expression analysis for mRNA and lncRNA transcripts; predicts interactions among lncRNAs, mRNAs, miRNAs, and proteins; and benchmarks performance against six existing tools using data from three species.