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novoSpaRc - de novo Spatial Reconstruction of Single-Cell Gene Expression

novoSpaRc predicts locations of single cells in space by solely using single-cell RNA sequencing data. An existing reference database of marker genes is not required, but significantly enhances performance if available.

novoSpaRc accompanies the following publications:

Gene Expression Cartography
M Nitzan*, N Karaiskos*, N Friedman†, N Rajewsky†

Version 0.4.4 11 October 2021

Fixed a bug regarding the distance metric usage in cost calculation.

Version 0.4.3 20 April 2021

Fixed bugs. Added self consistency analysis and updated tutorials.

Version 0.4.2 03 April 2021

Improved package structure, fixed minor performace issues, and fixed bugs. Added two new tutorials (corti & osteosarcoma) and updated the previous tutorials with validation analyses.

Version 0.4.1 24 August 2020

Changed the package structure and run flow of the scripts. Added anndata and scanpy support. Updated tutorials and implemented basic target geometries.

Version 0.3.11 27 April 2020

Moran’s I algorithm for spatially informative genes is implemented and removed pysal dependency.

Version 0.3.10 07 February 2020

Added Moran’s I algorithm to detect spatially informative genes.

Version 0.3.7 29 October 2019

Updated computation of shortest paths that singificantly reduces running time.

Version 0.3.5 13 June 2019

Fixed a bug that was prone to produce infinities during reconstruction. Improved plotting functions and added new ones for plotting mapped cells.

Version 0.3.4 27 February 2019

novoSpaRc reconstructs single-cell gene expression without relying on existing reference markers and makes great use of such information if available.