Science Score: 57.0%
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✓DOI references
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○Scientific vocabulary similarity
Low similarity (13.7%) to scientific vocabulary
Repository
Automated morphological analysis for cells
Basic Info
- Host: GitHub
- Owner: swanandlab
- License: gpl-3.0
- Language: Python
- Default Branch: main
- Homepage: https://doi.org/10.1242/jcs.258430
- Size: 38 MB
Statistics
- Stars: 6
- Watchers: 2
- Forks: 3
- Open Issues: 8
- Releases: 2
Metadata Files
README.md
SMorph
This library automates the morphological analysis of cells and classify different subgroups based on the extracted morphometric parameters.
- The notebook singlecellanalysis.ipynb includes the visual analysis to explore various morphological parameters of a single cell.
- And the notebook group_analysis.ipynb includes the group level analysis of cells of the Nervous System using Principal Component Analysis (PCA) which helps to distinguish the differences between different classes of cells based on their morphological parameters.
Published Version
Please note that this is an update to the initial published version. If you prefer to use the published version please redirect to following commit hyperlink.
Published Version
- Follow the instructions there to setup and run the published version.
Git Commit ID: bc8a1cc20d66eca755cb1f0621a4df72ca665bda
Please note that the published version is not packaged as a library.
Latest version usage
Quickstart
The package can be easily used in local and Colaboratory environment.
Colaboratory
Just go to following for:
You'll have to upload you data to Colaboratory environment either directly to session storage or to your Google Drive.
Instructions for linking your Google Drive dataset:
- Either select
Mount Drivefrom sidebarFilesbrowser or manually execute the following code in a cell.
python
from google.colab import drive
drive.mount('/content/drive')
After completing the authorization, paste the authorization code in the input.
After confirmation, refresh the Files sidebar. Your drive would now be visible in it.
Follow the same instructions in the following Usage instructions for organization of your data.
The same notebook can also run on your local environment.
Installation from source
The code has been tested for Python 3.7.11 and above, if you don't have it installed, please download the binaries from here and follow the installation guide.
SMorph uses Poetry package manager. Use the package manager pip to install Poetry. And install the dependencies by typing following in the command line:
sh
pip install -r requirements.txt
poetry install
If the above commands throw errors on windows, please try:
sh
python -m pip install -r requirements.txt
poetry install
Setup for analysis on local environment
To run the notebooks, execute following from command line and locate to the desired notebook using browser.
sh
poetry shell
jupyter notebook
If the above command throw errors on windows, please try:
sh
poetry shell
python -m notebook
Usage
Group analysis
Place your image data folders inside the
Datasetsfolder, with each group's images organized in their respective folders.Run the analysis by replacing the value of
groups_foldersvariable ingroup_analysis.ipynbwith path to each of your cell groups.
Single cell analysis
- Run the analysis by replacing the value of
cell_imagevariable insingle_cell_analysis.ipynbwith path to your cell image.
Help & Support
- If you encounter a previously unreported bug/code issue, please post here (we encourage you to search issues first): https://github.com/swanandlab/SMorph/issues
References
If you use this code and find it useful, we kindly ask that you please cite
Parul Sethi, Garima Virmani, Kushaan Gupta, Surya Chandra Rao Thumu, Narendrakumar Ramanan, Swananda Marathe. Automated morphometric analysis with SMorph software reveals plasticity induced by antidepressant therapy in hippocampal astrocytes. J Cell Sci 15 June 2021; 134 (12): jcs258430 https://doi.org/10.1242/jcs.258430
Owner
- Name: Swanand Lab @ IISc
- Login: swanandlab
- Kind: organization
- Location: India
- Website: https://swanandlab.github.io/
- Twitter: LabSwanand
- Repositories: 2
- Profile: https://github.com/swanandlab
Citation (CITATION.cff)
cff-version: "1.1.0"
message: "If you use this software, please cite it using these metadata."
authors:
-
affiliation: "Centre for Neuroscience, Indian Institute of Science, Bangalore, India 560012"
family-names: Sethi
given-names: Parul
orcid: "https://orcid.org/0000-0003-2913-2261"
-
affiliation: "Centre for Neuroscience, Indian Institute of Science, Bangalore, India 560012"
family-names: Virmani
given-names: Garima
orcid: "https://orcid.org/0000-0002-4225-3132"
-
affiliation: "Centre for Neuroscience, Indian Institute of Science, Bangalore, India 560012"
family-names: Gupta
given-names: Kushaan
orcid: "https://orcid.org/0000-0002-8491-0743"
-
affiliation: "Centre for Neuroscience, Indian Institute of Science, Bangalore, India 560012"
family-names: Thumu
given-names: "S.C.R."
-
affiliation: "Centre for Neuroscience, Indian Institute of Science, Bangalore, India 560012"
family-names: Ramanan
given-names: Narendrakumar
orcid: "https://orcid.org/0000-0002-6088-9599"
-
affiliation: "Centre for Neuroscience, Indian Institute of Science, Bangalore, India 560012"
family-names: Marathe
given-names: Swananda
orcid: "https://orcid.org/0000-0002-2539-366X"
title: "Automated morphometric analysis with SMorph software reveals plasticity induced by antidepressant therapy in hippocampal astrocytes"
doi: "10.1242/jcs.258430"
date-released: 2021-06-17
repository-code: "https://github.com/swanandlab/SMorph"
license: "GPL-3.0-only"
GitHub Events
Total
- Issues event: 1
- Issue comment event: 1
- Push event: 4
- Create event: 1
Last Year
- Issues event: 1
- Issue comment event: 1
- Push event: 4
- Create event: 1
Dependencies
- appnope 0.1.2
- argon2-cffi 20.1.0
- attrs 21.4.0
- backcall 0.2.0
- bleach 4.1.0
- certifi 2021.10.8
- cffi 1.15.0
- charset-normalizer 2.0.10
- colorama 0.4.4
- cycler 0.11.0
- debugpy 1.5.1
- decorator 5.1.1
- defusedxml 0.7.1
- entrypoints 0.3
- fonttools 4.29.0
- idna 3.3
- imageio 2.14.1
- importlib-metadata 4.10.1
- importlib-resources 5.4.0
- ipydatawidgets 4.2.0
- ipykernel 6.7.0
- ipython 7.31.1
- ipython-genutils 0.2.0
- ipyvolume 0.5.2
- ipywebrtc 0.6.0
- ipywidgets 7.6.5
- jedi 0.18.1
- jinja2 3.0.3
- joblib 1.1.0
- jsonschema 4.4.0
- jupyter 1.0.0
- jupyter-client 7.1.2
- jupyter-console 6.4.0
- jupyter-core 4.9.1
- jupyterlab-pygments 0.1.2
- jupyterlab-widgets 1.0.2
- kiwisolver 1.3.2
- llvmlite 0.35.0rc3
- markupsafe 2.0.1
- matplotlib 3.5.1
- matplotlib-inline 0.1.3
- mistune 0.8.4
- nbclient 0.5.10
- nbconvert 6.4.0
- nbformat 5.1.3
- nest-asyncio 1.5.4
- networkx 2.6.3
- notebook 6.4.8
- numba 0.51.2
- numpy 1.19.5
- packaging 21.3
- pandas 1.1.2
- pandocfilters 1.5.0
- parso 0.8.3
- pexpect 4.8.0
- pickleshare 0.7.5
- pillow 9.0.0
- prometheus-client 0.13.0
- prompt-toolkit 3.0.24
- ptyprocess 0.7.0
- py 1.11.0
- pycparser 2.21
- pygments 2.11.2
- pyparsing 3.0.7
- pyrsistent 0.18.1
- python-dateutil 2.8.2
- pythreejs 2.3.0
- pytz 2021.3
- pywavelets 1.2.0
- pywin32 303
- pywinpty 2.0.1
- pyzmq 22.3.0
- qtconsole 5.2.2
- qtpy 2.0.0
- requests 2.27.1
- scikit-image 0.19.1
- scikit-learn 1.0.2
- scipy 1.6.0
- seaborn 0.8.1
- send2trash 1.8.0
- setuptools-scm 6.4.2
- six 1.16.0
- skan 0.9
- terminado 0.12.1
- testpath 0.5.0
- threadpoolctl 3.0.0
- tifffile 2021.11.2
- tomli 2.0.0
- tornado 6.1
- traitlets 5.1.1
- traittypes 0.2.1
- typing-extensions 4.0.1
- urllib3 1.26.8
- wcwidth 0.2.5
- webencodings 0.5.1
- widgetsnbextension 3.5.2
- zipp 3.7.0
- argon2-cffi 20.1.0
- ipyvolume ^0.5.2
- jupyter ^1.0.0
- matplotlib ^3.5.1
- networkx ^2.6.3
- numba 0.51.2
- numpy 1.19.5
- pandas 1.1.2
- pip 21.3.1
- python ^3.7.9
- scikit-image ^0.19.1
- scikit-learn ^1.0.2
- scipy 1.6.0
- seaborn 0.8.1
- skan 0.9
- poetry *