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.
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
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 firstname.lastname@example.org 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
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.
This work is supported by the following NIH grant K99-CA256497
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