ConSemble

ConSemble constructs consensus transcriptome assemblies by integrating overlapping predictions from multiple de novo and genome-guided assemblers to improve assembly accuracy for downstream analyses such as differential expression, co-expression, and metabolic pathway reconstruction.

Key Features:

• Consensus-Based Approach: Integrates overlapping predictions from multiple assembly outputs to generate a consensus transcriptome.
• De novo and Genome-Guided Methods: Supports both de novo and genome-guided strategies, using four distinct de novo assemblers without a reference and four genome-guided assemblies when a reference genome is available.
• Alternative Splicing Handling: Addresses challenges from alternative splicing by preserving correctly assembled isoforms and mitigating assembler-specific errors.
• Benchmarking and Validation: Includes a pipeline to generate benchmark transcriptome datasets and simulated RNAseq data for comparative evaluation of assembly approaches.

Scientific Applications:

• Differential gene expression analysis: Produces accurate transcriptomes to support differential gene expression studies.
• Co-expression analysis: Provides assemblies suitable for co-expression network and systems-level analyses.
• Metabolic pathway reconstruction: Improves transcript representation for metabolic pathway reconstruction.
• Non-model organism transcriptomics: Enables transcriptome assembly for non-model organisms lacking reference genomes via de novo ensemble strategies.

Methodology:

Integrates outputs from multiple assemblers by detecting overlapping predictions; runs four de novo assemblers for reference-free assembly or four genome-guided assemblies when a reference genome is available; identifies and removes incorrectly assembled contigs while preserving correctly assembled contigs; generates benchmark transcriptomes and simulated RNAseq datasets.