FitGeneK: Build mixture models of gene expression

In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description

Models the imputed gene expression values as a mixture of gaussian distributions. For a two-state model, estimates the probability that a given cell is in the 'on' or 'off' state for any gene. Followed by a greedy k-means step where cells are allowed to flip states based on the overall structure of the data (see Manuscript for details)

Usage

FitGeneK(object, gene, do.k = 2, num.iter = 1, do.plot = FALSE,
  genes.use = NULL, start.pct = NULL)

Arguments

object	Seurat object
gene	Gene to fit
do.k	Number of modes for the mixture model (default is 2)
num.iter	Number of 'greedy k-means' iterations (default is 1)
do.plot	Plot mixture model results
genes.use	Genes to use in the greedy k-means step (See manuscript for details)
start.pct	Initial estimates of the percentage of cells in the 'on' state (usually estimated from the in situ map)

Value

A Seurat object, where the posterior of each cell being in the 'on' or 'off' state for each gene is stored in [e-mail]

nukappa/seurat_v2 documentation built on May 24, 2019, 9:57 a.m.