Corset

Corset clusters de novo assembled transcript contigs and summarizes read counts to produce gene-level expression estimates for differential expression analysis, especially in studies lacking a reference genome.

Key Features:

• De Novo Transcriptome Assembly: Processes RNA-seq data to generate contigs representing transcript fragments from de novo assembly outputs.
• Hierarchical Clustering: Employs hierarchical clustering of contigs based on shared reads and expression patterns to group transcripts into putative genes.
• Gene-Level Summarization: Aggregates read counts at the cluster (gene) level to produce gene-centric count matrices.
• Compatibility with Count-Based Tools: Produces cluster-level counts formatted for use with count-based differential expression tools such as edgeR and DESeq.

Scientific Applications:

• Non-model organism transcriptomics: Enables gene-level expression analysis when no reference genome is available by clustering de novo assembled contigs.
• Differential expression analysis: Provides gene-level count matrices suitable for statistical testing of differential expression across conditions.

Methodology:

Performs de novo transcriptome assembly to generate contigs, then hierarchically clusters contigs using shared reads and expression patterns and summarizes read counts at the cluster level.