In recent years, scientific computing has revolutionized the field of genomics. As the availability of genetic and genomic data and analysis tools continues to expand, it becomes increasingly imperative that researchers leverage the available tools in the scientific computing ecosystem. Most biology labs, however, are comprised of individuals with a wide range of technical skill, ranging from experienced bioinformaticians to complete nonprogrammers. Making analysis tools accessible to all members of the lab, regardless of their level of technical skill, both empowers labs to best utilize the latest analysis methods and enables researchers to explore available datasets, without the number of coders presenting a bottleneck.
Thorin Tabor offers an overview of the GenePattern Notebook, which allows Jupyter to communicate with the open source GenePattern environment for integrative genomics analysis. It wraps hundreds of software tools for analyzing omics data types (gene expression, sequence variation, proteomics, genomic networks, etc.), as well as general machine learning methods, and makes them available through a user-friendly interface accessible to both programming and nonprogramming researchers.
The GenePattern Notebook also offers a wider suite of enhancements for the Jupyter Notebook environment. These include a rich-text editor for markdown cells, a Python library for seamlessly interfacing with GenePattern Notebook cells, and the GenePattern Notebook Repository, a freely available JupyterHub server where researchers can develop and publish their own bioinformatics notebooks.
Thorin Tabor is a software engineer at UCSD and a contributing scientist at the Broad Institute. He is the lead developer of the GenePattern Notebook and an open source developer on the integration of bioinformatic tools with Jupyter.
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