Software and Protocol
p-Creode
p-Creode takes continuous single-cell data to generate transition trajectories and then use resampling to quantitatively score the quality and stability of computed results (Herring et al., Cell Systems, 2018)
pyNVR
pyNVR is a faster way to select relevant features as input for p-Creode and other trajectory analysis algorithms, selecting gene (features) based on small local variances (Chen et al., Bioinformatics, 2019)
p-Creode score for comparing graphs of different sizes
An implementation of the p-Creode score that compares graphs with different nodes and edges, but across different samples that may have unbalanced number of nodes (Liu et al., PLoS Biology, 2018)
sc-UniFrac
sc-UniFrac compares single-cell landscape diversity between samples by representing the global and local structure of single-cell data as trees and then performing hierarchical tree comparisons (Liu et al., PLoS Biology, 2018)
DR-Structure
Quantitative comparisons of multi-dimensional data structures when transformed by different dimension reduction techniques (Heiser and Lau, Cell Reports, 2020)
scRNAseqQC
Our pipeline to semi-automatically to filter cells from empty barcodes for downstream analyses
