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Showing content from https://npyc-toolbox.readthedocs.io/en/latest/tutorial.html below:

Installation and Tutorials — nPYc Toolbox 1.2.7 documentation

Opening a Jupyter Notebook

Jupyter can be opened from the Anaconda navigator (recommended) or from the command line.

• Using the Anaconda Navigator, launch a Jupyter Notebook session by clicking on the ‘Jupyter Notebook’ icon
• Alternatively, from the command (Windows) or terminal (macOS) window, launch Jupyter by typing ‘jupyter notebook’, for more details see Running Jupyter
• Either of the options above will result in an instance of the Jupyter Notebooks opening in a browser window

Running the nPYc-toolbox-tutorials

• Open a Jupyter Notebook session (as described above)
• Click on the ‘File’ tab and navigate to the location where the nPYc-toolbox-tutorials are saved
• Jupyter notebooks save with the file extension ‘ipynb’
• Click on the required Jupyter notebook example (MS, NMR and targeted NMR examples available, as described below) to open in a new browser window
• To run the notebook, click through the cells using the ‘Run’ button
• Notebooks can be reset and restarted using ‘Kernal > Restart & Clear Output’
• Notebooks can be saved using ‘File > Save and Checkpoint’ (notebooks can then be shared, and others will be able to view their contents)
• Full details on using the Jupyter Notebooks can be found here Jupyter Read the Docs

Running your own notebook

• Open the required the nPYc-toolbox-tutorials (as described above)
• Select ‘File > Make a copy..’ to make a copy of the notebook
• Select ‘File > Rename..’ to rename the copied notebook
• Replace the file paths in the document with your own data path files
• Run the notebook!

Exemplar data, as part of the nPYc-toolbox-tutorials, can be downloaded from the nPYc-toolbox-tutorial GitHub repository. This repository contains all the data and files required to run the tutorials (as described below). Data (including all raw LC-MS data files) is also available from the Metabolights repository under accession number MTBLS694.

The dataset used in these tutorials (DevSet) is comprised of three distinct pooled samples of human urine, with three additional samples generated by pairwise mixing of each primary sample, resulting in a sample set of six:

• DevSet1
• DevSet2
• DevSet3
• DevSet1v2
• DevSet1v3
• DevSet2v3

The samples were then split into 13 equivalent aliquots, and each independently prepared and measured by ultra-performance liquid chromatography coupled to reversed-phase positive ionisation mode spectrometry (LC-MS, RPOS) and 1H nuclear magnetic resonance (NMR) spectroscopy according to Phenome Centre protocols (LC-MS: Lewis et al [1], NMR: Dona et al [2]). As per these protocols, a pooled QC Study Reference sample and independent external reference (Long-Term Reference) of a comparable matrix was also acquired to assist in assessing analytical precision.

Urine samples used for generating of the exemplar matrices were collected with informed written consent and ethical approval from the Imperial College Healthcare Tissue Bank (12/WA/0196, project R13053).

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