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
