riboCleaner

riboCleaner identifies and quantifies rRNA-derived reads and misannotated rDNA gene models in RNA-seq data to correct gene expression estimates, primarily in plant genomes.

Key Features:

• Identification of Misannotated Gene Models: Detects false gene models located in rDNA regions that can lead to inflated transcript counts.
• Quantification of rRNA-Derived Reads: Measures the abundance of rRNA-originating reads within RNA-seq datasets to assess contamination levels.
• Applicability Across Plant Genomes: Has been demonstrated on multiple plant genome assemblies to address rDNA-associated annotation errors.
• Containerized Snakemake Workflow: Implemented as a Snakemake workflow packaged in a container to standardize computational execution.
• Correction of Expression Values: Provides adjusted gene expression estimates by accounting for identified rRNA-derived contaminants.

Scientific Applications:

• Refinement of RNA-seq Gene Expression Analysis: Reduces bias from rDNA/rRNA contamination to produce more accurate transcript quantification.
• Improvement of Reference Genomes and Transcriptomes: Identifies misannotated rDNA gene models to inform genome and annotation curation in plant genomics.
• Support for Downstream Genomic Analyses: Enables more reliable differential expression and functional interpretation by correcting contaminant-derived signals.

Methodology:

Detects and quantifies rRNA-derived reads in RNA-seq datasets; analyzes RNA-seq data for potential misannotated gene models within rDNA regions; quantifies the extent of rRNA-derived read contamination; provides corrected expression values accounting for identified contaminants; implemented as a containerized Snakemake workflow.