Rating: Very Good
Strong Points: Extensive documentation, notebooks are easy to find and download
Weak Points: Many notebooks available, but more are being added, so some users may not find what they need
One of the biggest hurdles when starting data analysis is being faced with a blank code document. Writing code that’s clean and processes your data exactly how you want it to is
time-consuming and frustrating, even if you know it’ll save you time down the road. However, if you’re processing genomic data, you might be able to skip that initial step entirely. GenePattern Notebook contains dozens of open-source coding documents that let you skip the trouble of writing the code yourself and get right to the data analysis instead. The available notebooks include several common methods for analysis, including k-nearest neighbors clustering, single-cell RNAseq clustering, and examination of microarray data. In addition to the notebooks, the website provides extensive documentation, including a quick start guide for new users, best practices for using the notebooks, and a cheat sheet for getting started. GenePattern Notebook is a great tool for researchers with large molecular datasets and makes it easy to get started on your data analysis.