Cell Type Pipes for Single-Cell RNA Sequencing Data
Create DESeq2 object for a given cell type
Classify cells on previously defined rules
Evaluate rule to obtain positive / negative cells
Feature plots: Color gene expression in 2D embeddings
Find approximate k-nearest neighbors
Check if obj$classes looks as expected. is_class returns FALSE for exa...
Check if obj$rules looks as expected.
Refine cell type labels with knn classifier
Call and visualize 'classify' function
Plot the last modified rule or class
Sum up x across neighbors in a nearest neighbor graph.
Form pseudobulks from single cells.
Generate unique IDs to identify your pseudobulks.
Generate code template for cellpype rules
Convert Seurat to cellpypes object.
Add a cell type rule.
Find parent, parent's parent and so on for a class using recursive pro...
Find child, child's child and so on for class(es) using recursive prog...
Finds leaf nodes, i.e. classes without children
Annotate single-cell RNA sequencing data manually based on marker gene thresholds. Find cell type rules (gene+threshold) through exploration, use the popular piping operator '%>%' to reconstruct complex cell type hierarchies. 'cellpypes' models technical noise to find positive and negative cells for a given expression threshold and returns cell type labels or pseudobulks. Cite this package as Frauhammer (2022) <doi:10.5281/zenodo.6555728> and visit <https://github.com/FelixTheStudent/cellpypes> for tutorials and newest features.
Useful links