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.
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
# 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 email@example.com
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
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
SCIMAP development is led by Ajit Johnson Nirmal at the Laboratory of Systems Pharmacology, Harvard Medical School.
This work is supported by the following NIH grant K99-CA256497