Mikado

Mikado reconstructs and selects optimal transcript models by integrating multiple RNA sequencing (RNA-seq) assemblies to produce coherent transcript annotations and is implemented in Python3 and Cython.

Key Features:

• Integration of Multiple Assemblies: Combines outputs from various RNA-seq assemblers to leverage complementary strengths and improve transcript reconstruction accuracy.
• Redundancy Removal: Identifies and eliminates redundant transcript models to streamline annotations.
• Optimal Transcript Model Selection: Selects the best transcript models based on user-specified metrics.
• Artifact Resolution: Detects and resolves common artifacts such as erroneous transcript chimerisms.

Scientific Applications:

• Non-model organism transcript annotation: Improves transcript reconstruction accuracy in studies of non-model organisms where assembler performance varies.
• Complex experimental designs: Enhances reliability of reconstructed transcripts across variable aligner and assembler performance in diverse experimental conditions.
• Genomics and transcriptomics research: Produces coherent annotations for downstream analyses requiring accurate and reproducible RNA-seq-derived transcripts.

Methodology:

Integrates multiple RNA-seq assemblies into a coherent transcript annotation by removing redundancies, selecting optimal transcript models based on user-defined criteria, and resolving artifacts such as erroneous chimerisms.