Metadata-Version: 2.1
Name: scimap
Version: 0.22.9
Summary: Spatial Single-Cell Analysis Toolkit
Home-page: https://pypi.org/project/scimap/
License: MIT
Keywords: image analysis,multiplex imaging,single cell analysis
Author: Ajit Johnson Nirmal
Author-email: ajitjohnson.n@gmail.com
Requires-Python: >=3.7,<3.11
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
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Project-URL: Documentation, https://scimap.xyz
Project-URL: Repository, https://github.com/labsyspharm/scimap
Description-Content-Type: text/markdown

# Single-Cell Image Analysis Package
<br>

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<br>

<img src="./docs/assets/scimap_logo.jpg" style="max-width:700px;width:100%" >

<br> 

Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the [anndata](https://anndata.readthedocs.io/en/stable/anndata.AnnData.html) framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.

## Installation

We strongly recommend installing `scimap` in a fresh virtual environment.

```
# If you have conda installed
conda create --name scimap python=3.8
conda activate scimap
```

Install `scimap` directly into an activated virtual environment:

```python
$ pip install scimap
```

After installation, the package can be imported as:

```python
$ python
>>> import scimap as sm
```

### Notice for Apple M1 users
Please note that multiple python packages have not yet extended support for M1 users. 
Below is a temporary solution to install scimap in `Apple M1` machines. 
Please follow the instructions in the given order.

```
# create and load a new environment
conda create -y -n scimap -c andfoy python=3.9 pyqt
conda activate scimap

# if you do not have xcode please install it
xcode-select --install

# if you do not have homebrew please install it
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# if you do not have cmake install it
brew install cmake

# install h5py
brew install hdf5@1.12
HDF5_DIR=/opt/homebrew/Cellar/hdf5/ pip install --no-build-isolation h5py

# install llvmlite
conda install llvmlite -y

# install leidenalg
pip install git+https://github.com/vtraag/leidenalg.git

# install scimap
pip install -U scimap

# uninstall 
conda remove llvmlite -y
pip uninstall numba -y
pip uninstall numpy -y

# reinstall this specific version of llvmlite (ignore errors/warning)
pip install -i https://pypi.anaconda.org/numba/label/wheels_experimental_m1/simple llvmlite

# reinstall this specific version of numpy (ignore errors/warning)
pip install numpy==1.22.3

# reinstall this specific version of numba (ignore errors/warning)
pip install -i https://pypi.anaconda.org/numba/label/wheels_experimental_m1/simple numba

```

## Get Started


#### Detailed documentation of `scimap` functions and tutorials are available [here](http://scimap.xyz/).

*SCIMAP* development is led by [Ajit Johnson Nirmal](https://ajitjohnson.com/) at the Laboratory of Systems Pharmacology, Harvard Medical School.

## Funding
This work is supported by the following NIH grant K99-CA256497


