find_gene_modules: Cluster genes into modules that are co-expressed across...

Description Usage Arguments Value

View source: R/cluster_genes.R

Description

Cluster genes into modules that are co-expressed across cells.

Usage

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find_gene_modules(
  cds,
  reduction_method = c("UMAP"),
  max_components = 2,
  umap.metric = "cosine",
  umap.min_dist = 0.1,
  umap.n_neighbors = 15L,
  umap.fast_sgd = FALSE,
  umap.nn_method = "annoy",
  k = 20,
  leiden_iter = 1,
  partition_qval = 0.05,
  weight = FALSE,
  resolution = NULL,
  random_seed = 0L,
  cores = 1,
  verbose = F,
  ...
)

Arguments

cds

the cell_data_set upon which to perform this operation

reduction_method

The dimensionality reduction method used to generate the lower dimensional space in which genes will be clustered. Currently only UMAP is supported.

max_components

The number of dimensions in which to cluster genes into modules.

umap.metric

Metric used by UMAP for measuring similarity between genes .

umap.min_dist

Minimum distance parameter passed to UMAP.

umap.n_neighbors

Number of nearest neighbors used by UMAP.

umap.fast_sgd

Whether to allow UMAP to perform fast stochastic gradient descent. Defaults to TRUE. Setting FALSE will result in slower, but deterministic behavior (if cores=1).

umap.nn_method

The method used for nearest neighbor network construction during UMAP.

k

number of kNN used in creating the k nearest neighbor graph for Louvain clustering. The number of kNN is related to the resolution of the clustering result, bigger number of kNN gives low resolution and vice versa. Default to be 20

leiden_iter

Integer number of iterations used for Leiden clustering. The clustering result with the largest modularity score is used as the final clustering result. Default to be 1.

partition_qval

Significance threshold used in Louvain community graph partitioning.

weight

A logic argument to determine whether or not we will use Jaccard coefficient for two nearest neighbors (based on the overlapping of their kNN) as the weight used for Louvain clustering. Default to be FALSE.

resolution

Resolution parameter passed to Louvain. Can be a list. If so, this method will evaluate modularity at each resolution and use the one with the highest value.

random_seed

the seed used by the random number generator in Leiden.

cores

number of cores computer should use to execute function

verbose

Whether or not verbose output is printed.

...

Additional arguments passed to UMAP and Louvain analysis.

Value

A dataframe with genes and the modules to which they are assigned.


cole-trapnell-lab/monocle3 documentation built on April 8, 2021, 5:54 a.m.