GPM (Genomic Project Manager)

GPM (Genomic Project Manager) is a versatile command-line tool designed for managing and automating bioinformatic workflows. Key features include:

• End-to-End Workflow: Seamlessly manage demultiplexing, processing, analysis, interactive reporting, and archiving tasks.
• Customizable: Easily adapt GPM to your environment, computer, web service, institute, or specific author requirements.
• Comprehensive NGS Application Coverage: Covering a wide range of Next-Generation Sequencing (NGS) applications, including RNAseq, tRNAseq, mRNAseq, ChIPseq, ATACseq, CLIPseq, ampliseq, scRNAseq, scVDJseq, scATACseq, miRNAseq, BWGS, WES, 16S, MAG, and more.
• Ideal for Bioinformatics Services: A powerful tool for individuals providing bioinformatic services.

A Short Demo

After installing and configuring GPM on your computer/server, effortlessly complete your project with the following steps:

1. Demultiplexing

Using an RNA-Seq workflow as an example, kick off your NGS project with a BCL folder (BCL_Path):

gpm demultiplex --raw BCL_Path --output FASTQ_output --method bcl2fastq

This command generates essential files for demultiplexing:

• run_bcl2fastq.sh: For running bcl2fastq.
• samplesheet_bcl2fastq.csv: For adding indices.
• project.ini: For storing all project-related information.

2. Processing

With your FASTQ files in hand, initiate the processing step:

gpm init --from-config above/project.ini --fastq path/to/fastqs --name 231231_Chao-Chung_Kuo_UKA_RNAseq --processing nfcore_3mRNAseq

This script generates the following files:

nfcore_3mRNAseq
├── nextflow.config
└── run_nfcore_3mrnaseq.sh

Now, you are ready to run nfcore and process your data.

3. Analysis

Generate the analysis report for the given application:

gpm analysis project.ini --report RNAseq

An Rmd file, Analysis_Report_RNAseq.Rmd, will be added under the analysis folder. Now you can explore available analyses provided by GPM by:

gpm analysis project.ini --list

Now you can select the analysis you want by name and add a set of files for DGEA_RNAseq:

gpm analysis project.ini --add DGEA_RNAseq

Whenever you want to add additional analyses, you can simply repeat the steps above. For example, now we can add GSEA_hallmarkgenes.

gpm analysis project.ini --add GSEA_hallmarkgenes

With its flexibility and scalability, GPM accelerates the template creation process and encourages code reuse.

4. Export

After you finish the analyses and reports, now you want to export all the results either to a web server or another local folder. No files will be copied, instead, they will be soft linked only.

Below command is used for exporting the results to a new folder in a web server:

gpm export --config project.ini --symprefix /mnt/nextgen/ --tar /path/to/web/server/folder/

Or, you can export the results to another folder locally.

gpm export --config project.ini --tar /path/to/a/local/folder/

5. Clean

After you finish the analysis, you might want to clean the temporary files which you don't want to archive. The files for cleaning are defined by regex pattern in gpm.ini, section [CLEAN] and the key PATTERNS,

gpm clean /path/to/the/folder/

6. Archive

When everything is done and you want to archive the scripts and codes to another place, you can use the command below:

gpm archive -v SOURCE_FOLDERS /target/archive/folder/

You can use wild cards to define the source folders, such as:

gpm archive -v 2306* /target/archive/folder/

For additional tutorials and HowTo guides, refer to the documentation site: gpm.readthedocs.io