Statistical Analysis and Comprehension of the Human Cell Atlas in R / Bioconductor: Access and Scalable Infrastructure
Focus
Bioconductor
Project Goal
To provide R / Bioconductor software to provide coherent programmatic interface to the HCA, and to enable scalable interactive statistical analysis of single-cell data.
Results & Resources
The Hansen lab began work on co-expression analysis for single-cell RNA data. They developed an R package, spqn, for normalizing local distributions in a correlation matrix. Their results show that spatial quantile normalization removes the mean-correlation relationship and corrects the expression bias in network reconstructions, as described in their preprint.
Investigators
Lead Investigator
Kasper Hansen