GEO2RNAseq

GEO2RNAseq processes raw RNA-seq data to perform comprehensive pre-processing and differential expression analysis for single-, dual-, and triple-RNA-seq experiments.

Key Features:

• Standardized pre-processing pipeline: Provides a consistent workflow from raw reads to downstream differential expression analysis.
• Support for single, dual, and triple RNA-seq: Handles datasets from one or multiple interacting species for multi-organism transcriptomics.
• GEO integration and FASTQ support: Accepts raw FASTQ files and can incorporate data obtained from the Gene Expression Omnibus (GEO).
• Metadata incorporation: Integrates experimental and computational metadata into the analysis context.
• Implemented in R with a modular design: Built in R with modular components that enable alternative workflows and extensions.
• Pre-processing operations: Performs trimming of raw reads, mapping to reference genomes, and counting reads per gene.
• Comprehensive reporting: Generates tables and figures reporting intermediate and final results, including differentially expressed genes (DEGs).

Scientific Applications:

• Transcriptome profiling: Identification of differentially expressed genes (DEGs) across conditions in single-species studies.
• Multi-species interaction studies: Analysis of expression dynamics in dual- and triple-RNA-seq experiments involving interacting organisms.
• Comparative expression analysis: Comparison of gene expression changes between samples or experimental conditions with integrated metadata.

Methodology:

Pre-processing steps explicitly include trimming raw reads, mapping reads to reference genomes, counting reads per gene, and performing differential expression analysis to identify DEGs.