PAGA: PAGA

In milescsmith/ReductionWrappers: Wrapper exposing several Python dimensional reduction tools

PAGA

Description

Use scanpy.tl.paga() to produce a partition-based graph abstraction for a Seurat object and use that to initialize a UMAP. Additionally, runs cluster determination via the 'leiden' or 'louvain' algorithms.

If dimensional reduction has already been performed (PCA, ICA, or harmony), that is used to find neighbors, otherwise PCA is run.

Parameters are prefixed by the step to which they correspond (i.e. "neighbors_" are passed to scanpy.pp.neighbors())

Heavily based on the fantastic walk through found at https://romanhaa.github.io/blog/paga_to_r/

Usage

PAGA(
  object,
  assay = "RNA",
  slim = FALSE,
  seurat_grouping = NULL,
  set_ident = TRUE,
  clustering_algorithm = "leiden",
  reduction_name = "umap",
  reduction_key = "umap_",
  edge_filter_weight = 0.1,
  neighbors_n_neighbors = 15,
  neighbors_n_pcs = NULL,
  neighbors_use_rep = "pca",
  neighbors_knn = TRUE,
  neighbors_random_state = 0,
  neighbors_method = "umap",
  neighbors_metric = "euclidean",
  clustering_resolution = 1,
  clustering_restrict_to = NULL,
  clustering_random_state = 0,
  clustering_key_added = NULL,
  clustering_adjacency = NULL,
  clustering_directed = TRUE,
  clustering_use_weights = TRUE,
  clustering_n_iterations = -1,
  clustering_partition_type = NULL,
  paga_show = FALSE,
  paga_plot = FALSE,
  paga_add_pos = TRUE,
  paga_threshold = 0.01,
  paga_layout = NULL,
  paga_init_pos = NULL,
  paga_root = 0,
  paga_single_component = NULL,
  paga_random_state = 0,
  umap_min_dist = 0.5,
  umap_spread = 1,
  umap_n_components = 3,
  umap_alpha = 1,
  umap_gamma = 1,
  umap_negative_sample_rate = 5,
  umap_init_pos = "spectral"
)

Arguments

assay	Seurat object assay to use when converting to Scanpy object
slim	Temporarily discard all unnecessary data from the Seurat object (i.e. keep only the normalized data for the assay and reduction used for neighborhood calculation). May help when performing PAGA on large objects. (Default: FALSE)
seurat_grouping	Force PAGA to use this metadata grouping variable. (Default: NULL)
set_ident	Set the cluster identity for each cell when returning the object? (Default: TRUE)
clustering_algorithm	Whether to use the "louvain" or "leiden" algorithms (Default: "leiden")
reduction_name	dimensional reduction name, 'umap' by default
reduction_key	dimensional reduction key, specifies the string before the number for the dimension names. 'umap' by default
edge_filter_weight	Set edges with a weight below this threshold to NA (Default: 0.1)
clustering_resolution	Resolution to pass to the clustering algorith (Default: 1.0)
umap_init_pos

milescsmith/ReductionWrappers documentation built on March 25, 2023, 11:58 a.m.