GeneFriends: a human RNA-seq-based gene and transcript co-expression database.

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• Co-expression networks are crucial for gene function prediction and understanding regulatory networks.
• Genome resequencing and association studies frequently identify novel genes requiring functional inference.
• Existing microarray-based co-expression maps have limitations in capturing the full transcriptome.

Purpose of the Study:

• To expand the GeneFriends database with an RNA-seq-based co-expression map.
• To enhance the identification of co-expressed genes, including non-coding RNAs.
• To facilitate functional annotation and disease-gene association for novel transcripts.

Main Methods:

• Development of an RNA-seq-based co-expression map.
• Integration of over 10,000 non-coding RNAs (ncRNAs) into the database.
• Implementation of a guilt-by-association approach for linking transcripts to diseases and processes.

Main Results:

• The expanded GeneFriends database includes a comprehensive RNA-seq co-expression map.
• Identification of co-expressed partners for genes and transcripts, including splice variants and ncRNAs (e.g., microRNAs, lincRNAs).
• Generation of functional enrichment summaries for co-expressed genes.

Conclusions:

• The updated GeneFriends database provides novel insights into gene function and regulatory networks.
• It serves as a valuable resource for prioritizing candidate genes and transcripts relevant to specific diseases and biological processes.
• The tool facilitates rapid identification and ranking of candidate targets using co-expression data.