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For Complete Instructions on useage, visit: GEMmaker documentation

GEMmaker is a Nextflow workflow for large-scale gene expression sample processing, expression-level quantification and Gene Expression Matrix (GEM) construction. Results from GEMmaker are useful for differential gene expression (DGE) and gene co-expression network (GCN) analyses. The GEMmaker workflow currently supports Illumina RNA-seq datasets.

• No bioinformatics software installation required
• Runs on a stand-alone computer or High Performance Compute (HPC) cluster
• Simple configuration file setup
• Resulting data is ready for Differential Gene Expression (DGE) or Gene Co-Expression Network (GCN) analysis
• Full online documentation

• Software versions and computing environment are the same every time an experiment is repeated
• Sharing input data and config files ensures anyone can reproduce exact results

• Uses a variety of bioinformatics tools
• Integrates with iRODs for easy data movement
• Easily retrieves samples from NCBI’s Sequence Read Archive (SRA)
• Can combine local samples with those from SRA
• Runs on many modern HPC systems

• Sample metadata is retrieved from NCBI SRA
• Controlled vocabularies are used to automatically remap SRA annotations
• JSON-format metadata files are created for each sample
• Metadata files can be integrated with data in iRODs for querying

• Useful for small DGE projects with 100s of samples as well as large GCN projects with 1000s of samples
• Cleans up intermediate files once they are no longer needed
• Keeps storage requirements to a minimum

GEMmaker uses the following tools:

• python3 v3.5.1
• nextflow v0.32
• sratoolkit v2.9.2
• aspera v3.8.1
• fastQC v0.11.7
• trimmomatic v0.38
• hisat2 v2.1.0
• kallisto v0.45.0
• salmon v0.12.0
• samtools v1.3.1
• stringTie v1.3.4d
• MultiQC v1.5

For Complete Instructions on useage, visit: GEMmaker documentation

GEMmaker is a collaborative project of the Ficklin and Feltus programs at Washington State University and Clemson University respectively with guidance from RENCI.

GEMmaker is funded by the NSF SciDAS project, award #1659300