ncFANs v2.0

ncFANs v2.0 provides integrative computational functional annotation of non-coding RNAs (ncRNAs) by combining network-based inference, enhancer-derived long non-coding RNA (lncRNA) identification from de novo assembled transcriptomes, and microarray-based analyses to characterize ncRNA regulatory roles.

Key Features:

• ncFANs-NET: Performs data-free functional annotation using four pre-built networks: co-expression, co-methylation, lncRNA-centric regulatory, and a random forest-based network to infer potential functions and interactions of ncRNAs.
• ncFANs-eLnc: Identifies enhancer-derived lncRNAs from de novo assembled transcriptomes using either user-defined or pre-annotated enhancers.
• ncFANs-CHIP: Conducts microarray data-based functional annotation and supports a broader range of chip types for analysis across diverse datasets.

Scientific Applications:

• ncRNA functional characterization: Infers potential biological functions and interaction partners of ncRNAs through network-based analysis.
• Enhancer-derived lncRNA discovery: Detects and annotates lncRNAs originating from enhancer regions using transcriptome assemblies and enhancer annotations.
• Microarray-based ncRNA analysis: Enables functional analysis of ncRNAs from microarray experiments across multiple chip types.

Methodology:

Uses pre-built co-expression, co-methylation, lncRNA-centric regulatory and random forest-based networks, applies network-based approaches and data integration, identifies enhancer-derived lncRNAs from de novo assembled transcriptomes using user-defined or pre-annotated enhancers, and performs microarray-based functional annotation across multiple chip types.