nf-coreGPT-Expert Bioinformatics Guidance

Example

nf-coreGPT offers standardized pipelines for common bioinformatics tasks. For instance, a pipeline for Whole Genome Sequencing (WGS) analysis integrates steps like read mapping, variant calling, and annotation, ensuring best practice methods are followed.

Scenario

A genomic researcher uses the WGS pipeline to analyze patient samples for genetic variations associated with a disease, benefiting from the pre-configured, optimized steps.

Example

The use of Docker and Singularity containers in nf-coreGPT pipelines encapsulates the software environment, ensuring reproducibility across different computational platforms.

Scenario

A team of researchers collaborates on a multi-center study. Using nf-coreGPT, they ensure that data analysis is consistent and reproducible across different labs, regardless of underlying hardware and software differences.

Example

While nf-coreGPT provides standardized pipelines, it also allows customization to meet specific research needs. Users can modify existing pipelines or create new ones using the Nextflow DSL2 syntax.

Scenario

A cancer biologist tailors an RNA-seq analysis pipeline to include additional steps for fusion gene detection, vital for their specific research on leukemia.