Seq2science: an end-to-end workflow for functional genomics analysis.

Area of Science:

• Genomics
• Bioinformatics

Background:

• Functional genomics sequencing databases offer vast resources for genome-scale analysis.
• Reanalyzing and integrating public data with project-specific datasets is valuable but challenging due to standardization and reproducibility issues.
• Current genomic experiment technologies enable analysis for numerous species.

Purpose of the Study:

• To present Seq2science, a multi-purpose workflow designed to streamline the analysis of functional genomics sequencing data.
• To facilitate data retrieval from major sequencing databases and genome assembly sources.
• To provide standardized and reproducible analysis pipelines for various genomic experiments.

Main Methods:

• Seq2science automates data downloading from NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE.
• It retrieves genome assemblies from Ensembl, NCBI, and UCSC.
• The workflow utilizes the Snakemake language for compatibility with diverse computing infrastructures and includes ATAC-, RNA-, and ChIP-seq analyses.

Main Results:

• Seq2science covers preprocessing, quality control, visualization, and analysis steps.
• It supports generic and advanced analyses like differential gene expression and motif analysis.
• The workflow has been successfully tested on multiple species, demonstrating its versatility.

Conclusions:

• Seq2science offers a standardized and reproducible solution for functional genomics data analysis.
• It simplifies the integration of public and project-specific data, accelerating research.
• The workflow enhances the accessibility and utility of large-scale genomic datasets.