# Cell Type Pipes for Single-Cell RNA Sequencing Data

## Documentation for package ‘cellpypes’ version 0.3.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

classify | Classify cells on previously defined rules
class_to_deseq2 | Create DESeq2 object for a given cell type
feat | Feature plots: Color gene expression in 2D embeddings
find_knn | Find approximate k-nearest neighbors
is_classes | Check if obj$classes looks as expected. is_class returns FALSE for example in these cases: is_classes(NULL) is_classes(data.frame()) is_classes(data.frame(class=c("T","T"), parent=c("..root..","..root..")))
is_rules | Check if obj$rules looks as expected.
knn_refine | Refine cell type labels with knn classifier
plot_classes | Call and visualize 'classify' function
plot_last | Plot the last modified rule or class
pool_across_neighbors | Sum up x across neighbors in a nearest neighbor graph.
pseudobulk | Form pseudobulks from single cells.
pseudobulk_id | Generate unique IDs to identify your pseudobulks.
pype_code_template | Generate code template for cellpype rules
pype_from_seurat | Convert Seurat to cellpypes object.
rule | Add a cell type rule.
simulated_umis | Simulated scRNAseq data