/SPRING_dev

Primary LanguageJavaScript

Installing Python libraries

To run SPRING Viewer locally, make sure Python 2.7 is installed (and that it's your active version). You will also need the following Python libraries:

scikit-learn
numpy
scipy
matplotlib
h5py
networkx
fa2
python-louvain

We recommend Anaconda to manage your Python libraries. You can download it here (be sure to get the Python 2.7 version): https://conda.io/miniconda.html. Libraries can then be installed using the command conda. To do so, open Terminal (Mac) or Anaconda Prompt (Windows) and enter:

conda install scikit-learn numpy scipy matplotlib h5py

The remaining libraries can be installed using pip. Note that if you're a Windows user, you'll first need to install Microsoft Visual C++ compiler for Python (available from http://aka.ms/vcpython27). Enter the following into Terminal or Anaconda Prompt:

pip install networkx fa2 python-louvain

Setting up a SPRING data directory

See the example notebooks:
Hematopoietic progenitor FACS subpopulations
Mature blood cells (10X Genomics 4k PBMCs)

A SPRING data set consist of a main directory and any number of subdirectories, with each subdirectory corresponding to one SPRING plot (i.e. subplot) that draws on a data matrix stored in the main directory. The main directory should have the following files, as well as one subdirectory for each SPRING plot.

counts_norm.npz
counts_norm_sparse_cells.hdf5
counts_norm_sparse_genes.hdf5
genes.txt

Each subdirectory should contain:

categorical_coloring_data.json
cell_filter.npy
cell_filter.txt
color_data_gene_sets.csv
color_stats.json
coordinates.txt
edges.csv
graph_data.json
run_info.json

Place the main directory somehwere inside folder that contains this README and the other SPRING file. We recommend that you create a special datasets directory. For example, if you have a main data set called human_bone_marrow and another called frog_embryo, you could place them in ./datasets/human_bone_marrow/ and ./datasets/frog_embryo/.

Running SPRING Viewer

  1. Open Terminal (Mac) or Anaconda Prompt (Windows) and change directories (cd) to the directory containing this README file (SPRING_dev/).
  2. Start a local server by entering the following: python -m CGIHTTPServer 8000
  3. Open web browser (preferably Chrome; best to use incognito mode to ensure no cached data is used).
  4. View data set by navigating to corresponding URL: http://localhost:8000/springViewer_1_6_dev.html?path_to/main/subplot. In the example above, if you wanted to view a SPRING plot called HSC in the main directory human_bone_marrow, then you would navigate to http://localhost:8000/springViewer_1_6_dev.html?datasets/human_bone_marrow/HSC