Jupyter notebook is a useful tool for data analysis. By keeping code and result in a web browser, it keeps research record, facilitates collaboration, and makes good tutorials. Here is a tutorial on Jupyter notebook: https://jupyter.readthedocs.io/en/latest/content-quickstart.html, and a Youtube tutorial. The Jupyter notebook can run kernels on different computer languages.
Click on any of the following link to open the notebook in a new window.
Averaging technical replicates
Preprocessing LC-MS data, taking a raw feature table through QC
Statistical analyses of metabolite features (group comparison)
Clustering of metabolite peaks from LC-MS, using intensity and retention time
Bubble plot, using scatter plot panels to visualize result from pathway analysis
How to generate a metabolic model for mummichog 2
Manhattan plot for metabolome wide association (MWAS)
Perform hierachical clustering and make a heat map using pandas and seaborn
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