NetSeekR: a network analysis pipeline for RNA-Seq time series data.

Area of Science:

• Bioinformatics
• Systems Biology
• Genomics

Background:

• Advancements in Next-Generation Sequencing (NGS) and network inference tools enable complex genomic analyses.
• Integrating diverse bioinformatics tools into a unified pipeline presents challenges in standardization and usability.
• A programmatic framework is needed to fully leverage the analytical capabilities of various genomic analysis tools.

Purpose of the Study:

• To introduce NetSeekR, an R package designed for network analysis of genomic data.
• To provide a comprehensive software pipeline integrating multiple bioinformatics methods for comparative genomics.
• To facilitate hypothesis generation and functional analysis from large-scale NGS data.

Main Methods:

• NetSeekR analyzes time-series RNA-Seq data, performing correlation and regulatory network inference.
• The pipeline includes read alignment, differential gene expression analysis, and network visualization.
• It supports multiple RNA-Seq read mapping methods for comparative analysis.

Main Results:

• NetSeekR integrates various bioinformatics tools for network inference from genomic data.
• The package enables comparative analysis of results from different bioinformatics methods.
• It facilitates the summarization of comparative genomics study results using network analysis.

Conclusions:

• The NetSeekR methodology enhances the integration of genomics data analysis with network inference.
• This facilitates hypothesis building, functional analysis, and discovery from large-scale NGS data.
• The pipeline supports the development of systems biology methods using extensive genomic datasets.