Grouper

Grouper improves de novo transcriptome analysis by graph-based clustering of contigs and annotation transfer from related genomes to produce more complete and accurate transcriptome representations from RNA-seq assemblies.

Key Features:

• Contig Clustering: Clusters contigs derived from de novo assemblies that are likely part of the same transcripts or genes.
• Annotation Transfer: Transfers annotations from a genome of a closely related organism to contigs of the de novo assembly to augment functional context.
• Improved Read Mapping: Maps reads against contigs with reported increases in read mapping efficiency of more than 10% relative to existing methods, improving downstream analyses such as differential expression.
• Efficient Annotation Labeling: Labels contigs by transferring annotations from an annotated genome of a related species to enrich functional interpretation of clustered contigs.

Scientific Applications:

• Non-model organism transcriptomics: Improves assembly completeness and representation for RNA-seq studies in species lacking reference genomes.
• Differential expression analysis: Provides more accurate contig groupings and higher read mapping rates to support differential expression workflows.
• Gene function annotation: Facilitates transfer of functional annotations to de novo contigs to aid gene annotation and functional inference.
• Comparative genomics and evolutionary studies: Enables annotation-aware grouping of transcripts across related species to support comparative and evolutionary analyses in ecology and systems biology.

Methodology:

Uses a graph-based approach to cluster contigs and integrates information from related genomes to transfer annotations and label contigs, with read mapping against contigs used to evaluate performance.