scimap 0.20.13

Spatial Single-Cell Analysis Toolkit

Single-Cell Image Analysis Package

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 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:

$ pip install scimap

After installation, the package can be imported as:

$ 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.

SCIMAP development is led by Ajit Johnson Nirmal at the Laboratory of Systems Pharmacology, Harvard Medical School.

Funding

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