Partek Flow is a robust software application for analyzing high-throughput next-generation sequencing (NGS) data. Developed by Partek Incorporated, it is aimed at providing researchers with a comprehensive suite of NGS data analysis tools, including modules for bulk and single-cell RNA-seq analysis, ChIP-seq analysis, and more.
The key advantage of Partek Flow is its simplicity to use. The software was created with a user-friendly graphical user interface in mind, making it accessible to researchers without coding experience. This allows users to quickly begin analyzing NGS data without having to spend countless hours learning how to use complex bioinformatics tools via a command line interface. Furthermore, Partek Flow includes a plethora of built-in visualizations and statistical tools that enable researchers to quickly and easily explore their data and identify meaningful patterns.
HSLS has procured several concurrent-user licenses for Partek Flow. This allows researchers affiliated with the University of Pittsburgh to register for the software and get free access to three NGS analysis modules: bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and ChIP/ATAC-seq data analysis.
Researchers studying gene expression patterns in different tissues can use Partek Flow to perform bulk RNA-seq analysis, allowing them to quantify the expression levels of thousands of genes simultaneously. Biologists engaged in uncovering the molecular heterogeneity of complex biological systems at the single-cell resolution would find the scRNA-seq modules useful. Similarly, researchers studying the interactions between DNA and proteins can use Partek Flow’s ChIP-seq analysis tool to identify and quantify the binding sites of DNA-binding proteins.
To further support the use of Partek Flow, HSLS MolBio workshops are held regularly to teach researchers how to use this tool effectively. HSLS MolBio also provides one-on-one consultations on data analysis and result interpretation. For a seasoned bioinformatician or a new researcher, Partek Flow could be a valuable tool in their NGS data analysis arsenal.
~Ansuman Chattopadhyay