https://github.com/derthorsten/spatial
spatial genomics
https://github.com/derthorsten/spatial
Last synced: about 1 year ago
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spatial genomics
- Host: GitHub
- URL: https://github.com/derthorsten/spatial
- Owner: DerThorsten
- License: mit
- Created: 2019-07-12T10:06:14.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-08-01T14:17:10.000Z (almost 7 years ago)
- Last Synced: 2025-02-14T18:49:06.761Z (over 1 year ago)
- Language: Python
- Size: 111 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- Contributing: CONTRIBUTING.rst
Awesome Lists containing this project
README
=================================================
Integrative analysis of single cell imaging mass citometry data of breast cancer patients
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.. image:: https://readthedocs.org/projects/spatial/badge/?version=latest
:target: http://spatial.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://circleci.com/gh/DerThorsten/spatial/tree/master.svg?style=svg
:target: https://circleci.com/gh/DerThorsten/spatial/tree/master
:alt: CircleCI Status
Current features include:
* modern C++ 14
* build system with modernish CMake
Running a first exploratory data analysis
================
First, install the dependencies with
``conda env create -f spatial-dev-requirements.yml``
and activate the corresponding conda environment
``conda activate spatial-dev``
Currently, there is a problem in the DFKZ cluster which prevents Snakemake to be installed automatically from the ``.yml`` file, so in any machine you also need to run (from within the spatial-dev environment) the following:
``conda install -c bioconda snakemake``
=======
If this still does not work, you need to run the script manually instead that with Snakemake.
Now, if you are in DKFZ cluster the data is already present (in ``/icgc/dkfzlsdf/analysis/B260/projects/spatial_zurich/data``) so, if you have been able to install Snakemake, you can run the exploratory data analysis simply with the command
=======
Now, if you are in DKFZ cluster the data is already present (in ``/icgc/dkfzlsdf/analysis/B260/projects/spatial_zurich/data``) so you can run the exploratory data analysis simply with the command
>>>>>>> c269ac8d28bf8a4b3417ffcbabd34b50ff875ea6
=======
``snakemake``
If you are not in the cluster you first need to update the code in ``folders.py`` by inserting the path of the root folder of the data in your machine. In the root folder the data must be organized into this directory tree:
::
/
├── csv/
│ ├── Basel_PatientMetadata.csv
│ ├── Basel_Zuri_SingleCell.csv
│ ├── Basel_Zuri_StainingPanel.csv
│ ├── Basel_Zuri_WholeImage.csv
│ └── Zuri_PatientMetadata.csv
├── Basel_Zuri_masks/
│ └── *.tiff (746 files)
└── ome/
└── *.tiff (746 files)
The Data
====
The data, from the B. Bodenmiller lab, is a collection of images acquired with Imaging Mass Citometry of breast cancer cells of different patients and under different conditions [1]_.
Each ``.tiff`` file in the ``ome`` folder is uniquely paired with a ``.tiff`` mask. Each mask tells which are the cells.
FAQ
====
Q: Is the data showing 2D sections of 3D bodies?
A: No
----
.. [1] Schulz D, Zanotelli VRT, Bodenmiller B. et al. *Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry.* Cell Syst. 2018 Jan 24