Single Cell Poisson Probability Paradigm
A novel data representation based on Poisson probability
Cluster label clean
Cluster size
Differential expression analysis
return Family-Wise Error Rate (FWER) cutoffs
get FWER from idx_hc attribute of shc object
get FWER cutoffs for shc object
get example data
Cluster cells in a recursive way
Linear interpolation for one sample given reference sample
Logit transformation
Louvain clustering using departure as data representation
Random sample generation function to generate sets of samples from the...
A more "continuous" approximation of quantiles of samples with a few i...
A more "continuous" approximation of quantiles from the theoretical Po...
Parameter estimates based on two-way approximation
Paired quantile after interpolation between two samples
Q-Q plot comparing samples with a theoretical Poisson distribution
Q-Q plot comparing two samples with small discrete counts
scpoisson: Single Cell Poisson Probability Paradigm
Generate New scppp object
Significance for first split using sigclust2
Dirk theme ggplots
Useful to visualize the Poissoneity (an independent Poisson statistical framework, where each RNA measurement for each cell comes from its own independent Poisson distribution) of Unique Molecular Identifier (UMI) based single cell RNA sequencing (scRNA-seq) data, and explore cell clustering based on model departure as a novel data representation.