https://github.com/tynes/plate-reader

https://github.com/tynes/plate-reader

biology

Last synced: 9 days ago
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• Host: GitHub
• URL: https://github.com/tynes/plate-reader
• Owner: tynes
• Created: 2017-04-25T04:35:45.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-05-03T01:13:46.000Z (over 7 years ago)
• Last Synced: 2024-11-06T18:01:09.390Z (about 2 months ago)
• Topics: biology
• Language: Jupyter Notebook
• Size: 146 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 96 Well Plate Analysis

Generate some graphs using Python!

## Requirements

Make sure that these are downloaded before starting:

- [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)

- Docker for [Mac](https://www.docker.com/docker-mac) or [Windows](https://www.docker.com/docker-windows)

## Usage

1. Open up your terminal of choice

   - Try using the `ls` and `pwd` commands

1. If you would like to download the repository to another directory, use the `cd` command and pass it the name of the directory

   - ie `$ cd Documents`

   - **Note: the $ indicates that it is something that you are typing on the command line, you do not need to include the $ when typing a command**

1. Download or clone the repository by using the command `$ git clone https://github.com/Tynes/plate-reader`

1. **C**hange **D**irectories into the newly cloned repository with the command `$ cd plate-reader`

1. Build the Docker image with the command `$ ./build.sh`

   - **Note: you only need to do this once**

1. Start a Docker container (using the image we just built) by running the command `$ ./start.sh`

   - This starts a Jupyter Notebook Server on your machine

1. Using an internet browser, navigate to `localhost:8888` to view the Jupyter Notebook webpage

1. There are 2 directories that correspond with each other inside of the container and outside of the container

   - data

   - Notebooks

     - **Any files you add to these directories will appear in Jupyter Notebook**

1. Add the appropriate files to the data directory on your local machine, ie drag & drop using something like Finder or Windows Explorer

1. Looking at Jupyter Notebook in the web browser, navigate to the Notebooks directory and then click on `reader.ipynb`

   - This will start an interactive Python session

1. Click on the Run Cell button, it looks like a play button (or press shift+enter to speed things up) to run a cell

1. Run each of the cells to generate the graph!

   - Advanced users can scroll down to the bottom, select a cell and then click on the menu item Cell -> Run All Above