RunLSI: Run Latent Semantic Indexing on binary count matrix

In gcday/seurat_fresh: Tools for Single Cell Genomics

Description

For details about stored LSI calculation parameters, see PrintLSIParams.

Usage

RunLSI(object, ...)

## Default S3 method:
RunLSI(object, assay = NULL, n = 50,
  reduction.key = "LSI_", scale.max = NULL, seed.use = 42,
  verbose = TRUE, ...)

## S3 method for class 'Assay'
RunLSI(object, assay = NULL, features = NULL, n = 50,
  reduction.key = "LSI_", scale.max = NULL, verbose = TRUE, ...)

## S3 method for class 'Seurat'
RunLSI(object, assay = NULL, features = NULL,
  n = 50, reduction.key = "LSI_", reduction.name = "lsi",
  scale.max = NULL, verbose = TRUE, ...)

Arguments

object	Seurat object
...	Arguments passed to other methods
assay	Which assay to use. If NULL, use the default assay
n	Number of singular values to compute
reduction.key	Key for dimension reduction object
scale.max	Clipping value for cell embeddings. Default (NULL) is no clipping.
seed.use	Set a random seed. By default, sets the seed to 42. Setting NULL will not set a seed.
verbose	Print messages
features	Which features to use. If NULL, use variable features
reduction.name	Name for stored dimension reduction object. Default 'lsi'

Examples

lsi <- RunLSI(object = pbmc_small, n = 5)

gcday/seurat_fresh documentation built on June 23, 2019, 12:02 a.m.