Notebooks for analysis from "Mapping the gene space at single-cell resolution with gene signal pattern analysis"

Gene Signal Pattern Analysis is a Python package for mapping the gene space from single-cell data. For a detailed explanation of GSPA and potential downstream application, see:

Mapping the gene space at single-cell resolution with Gene Signal Pattern Analysis. Aarthi Venkat, Sam Leone, Scott E. Youlten, Eric Fagerberg, John Attanasio, Nikhil S. Joshi, Michael Perlmutter, Smita Krishnaswamy.

By considering gene expression values as signals on the cell-cell graph, GSPA enables complex analyses of gene-gene relationships, including gene cluster analysis, cell-cell communication, and patient manifold learning from gene-gene graphs.

See the following directories to generate results:

1. analysis_batch_correction for Extended Data Figure 1
2. analysis_wavelets for Extended Data Figure 3, 4
3. analysis_coexpression for Figure 2, Extended Data Figure 5, 6, 7, 10, Extended Data Table 1
4. analysis_localization for Figure 3, Extended Data Figure 9, 10, Extended Data Table 1
5. analysis_tcells for Figure 4, Extended Data Figure 11, 12, Extended Data Table 2
6. analysis_cellcomm for Figure 5, Extended Data Figure 13, 14, Extended Data Table 3
7. analysis_spatial for Figure 6, Extended Data Figure 15, Extended Data Table 4
8. analysis_patient for Figure 7, Extened Data Table 5