sce_int_clustering_df_fn: Compute a quick graph-based clustering for each integration...

In bioinfocz/scdrake: A pipeline for droplet-based single-cell RNA-seq data secondary analysis implemented in the drake Make-like toolkit for R language

Compute a quick graph-based clustering for each integration method.

Description

For Harmony integration, the "harmony" reduced dims are used as an input to scran::buildSNNGraph(); otherwise PCA is used.

Usage

sce_int_clustering_df_fn(
  sce_int_pca_df,
  snn_k = 10,
  snn_type = "rank",
  snn_clustering_method = c("walktrap", "louvain"),
  BPPARAM = BiocParallel::SerialParam()
)

Arguments

sce_int_pca_df	(input target) A tibble.
snn_k, snn_type, snn_clustering_method	See sce_int_raw_snn_clustering_fn().
BPPARAM	A BiocParallel::BiocParallelParam object.

Value

A modified sce_int_pca_df with appended SingleCellExperiment object with computed clustering. Output target: sce_int_clustering_df

The following items of metadata() of each integrated SingleCellExperiment object are added or modified:

• int_cluster_snn_k, int_cluster_snn_type, int_cluster_snn_method: taken from parameters of the integration method.

bioinfocz/scdrake documentation built on Jan. 29, 2024, 10:24 a.m.