cluster_wrapper: A wrapper for Seurat's clustering functions.

In maehrlab/thymusatlastools: Tools for analysis of single-cell transcriptomic data

Description

A wrapper for Seurat's clustering functions.

Usage

cluster_wrapper(dge, results_path, test_mode, pc.use = NULL,
  method = c("DBSCAN"), granularities_as_string = "6", merge_small = F)

Arguments

method	is either "DBSCAN" or "SNN".
granularities_as_string	should be numbers separated by commas and whitespace. The number of clusterings performed is the length of (the split and cleaned version of) 'granularities_as_string'. The granularity number is used as the neighborhood radius in DBSCAN or the "resolution" in SNN.

Details

For more information on density-based clustering (DBSCAN), look at the KDD-96 paper by Ester, Kriegel, Sander, and Xu. "A density-based algorithm for discovering clusters in large spatial databases with noise." For more information on the SNN-based clustering, look at (the parameter gamma in) "A unified approach to mapping and clustering of bibliometric networks", Ludo Waltman, Nees Jan van Eck, and Ed C.M. Noyons

maehrlab/thymusatlastools documentation built on May 28, 2019, 2:32 a.m.