croparray
Authors: Tim Stasevich and Luis Aguilera.
Description
This module is intended for creating and manipulating an array of crops (or regions of interest) that were generated from a multicolor TIF video obtained from single-molecule microscopy.
<img src= https://github.com/Colorado-State-University-Stasevich-Lab/croparray/raw/main/docs/images/Fig1-CropArrayConceptV4.png alt="drawing" width="600"/>
Documentation
Colab implementation
- Implementation in Google Colab
<img src= https://github.com/Colorado-State-University-Stasevich-Lab/croparray/raw/main/docs/images/Croparray.gif alt="drawing" width="1000"/>
Local installation from the Github repository
git clone https://github.com/Colorado-State-University-Stasevich-Lab/croparray.git
- To create a virtual environment navigate to your local repository and use:
conda create -n croparray_env python=3.8 -y
source activate croparray_env
- To install the rest of requirements use:
pip install -r requirements.txt
python -m pip install "napari[all]"
Local installation using PIP
- To create a virtual environment using:
conda create -n croparray_env python=3.8 -y
source activate croparray_env
- Open the terminal and use pip for the installation:
pip install croparray
python -m pip install "napari[all]"
Deactivating and removing the environment
- To deactivate or remove the environment from your computer use:
conda deactivate
- To remove the environment use:
conda env remove -n croparray_env
- To unistall croparray use
pip uninstall croparray
additional troubleshooting information
- If you cannot see the package installed on your computer, try using
pip3
. For example:
pip3 install croparray
Installing from yml env
- To creating an environment file (yml) use:
source activate croparray_env
conda env export > croparray_env.yml
- ToCreate an environment from this yml file.
conda env create -f croparray_env.yml
Usage
- Organizes crops and measurements of spots of interest from tif images in a convenient x-array format for reduced filesize and more open and reproducible analyses.
- Visualizes crops of detected spots from super-resolution microscope images.
- Calculates the best maximum projection for each crop containing a detected spot.
- Measures intensity of detected spots within crops.
- Calculates the correlation between two equal-length, 1D signals.
- Saves the crop array as a netcdf file at output_direction/output_filename.
- Integrates with Napari for fast and convenient review of crops of detected spots.
Licenses for dependencies
-
License for Napari: BSD-3-Clause License. Copyright (c) 2018, Napari. All rights reserved.
-
License for xarray: Apache License. Version 2.0, January 2004. Copyright 2014-2019, xarray Developers