GEMmaker

GEMmaker processes and quantifies large-scale RNA-seq samples to construct Gene Expression Matrices (GEMs) for transcriptome analyses such as differential expression and co-expression network construction.

Key Features:

• Scalability: Processes datasets ranging from small experiments to thousands of RNA-seq samples while managing storage to avoid exceeding available capacities.
• Workflow framework: Implements an nf-core compliant Nextflow workflow to orchestrate complex RNA-seq processing steps.
• Containerized reproducibility and portability: Uses versioned containerized software to ensure reproducibility and to support execution on workstations, compute clusters, Kubernetes, and cloud platforms.
• Support for alignment and quantification tools: Integrates widely used alignment and quantification tools and produces both raw and normalized expression outputs.
• Resource efficiency: Incorporates data-management strategies to handle large datasets within limited storage infrastructures.

Scientific Applications:

• Differential gene expression analysis: Provides quantified expression data suitable for identifying differentially expressed genes across conditions.
• Gene co-expression network construction: Produces gene expression matrices that can be used to build co-expression networks.
• Large-scale transcriptome quantification: Enables comprehensive quantification of gene expression across extensive RNA-seq cohorts.
• Meta-analysis and comparative studies: Facilitates integration of multiple experiments from sequence repositories for meta-analyses and comparative transcriptomics.

Methodology:

Uses an nf-core compliant Nextflow workflow with versioned containerized software, integrates alignment and quantification tools to produce raw and normalized outputs, constructs Gene Expression Matrices, and manages data and computational resource allocation.