knn.error.models: Build error models for heterogeneous cell populations, based...

In hms-dbmi/scde: Single Cell Differential Expression

Build error models for heterogeneous cell populations, based on K-nearest neighbor cells.

Description

Builds cell-specific error models assuming that there are multiple subpopulations present among the measured cells. The models for each cell are based on average expression estimates obtained from K closest cells within a given group (if groups = NULL, then within the entire set of measured cells). The method implements fitting of both the original log-fit models (when linear.fit = FALSE), or newer linear-fit models (linear.fit = TRUE, default) with locally fit overdispersion coefficient (local.theta.fit = TRUE, default).

Usage

knn.error.models(counts, groups = NULL, k = round(ncol(counts)/2),
  min.nonfailed = 5, min.count.threshold = 1, save.model.plots = TRUE,
  max.model.plots = 50, n.cores = parallel::detectCores(),
  min.size.entries = 2000, min.fpm = 0, cor.method = "pearson",
  verbose = 0, fpm.estimate.trim = 0.25, linear.fit = TRUE,
  local.theta.fit = linear.fit, theta.fit.range = c(0.01, 100),
  alpha.weight.power = 1/2)

Arguments

counts	count matrix (integer matrix, rows- genes, columns- cells)
groups	optional groups partitioning known subpopulations
k	number of nearest neighbor cells to use during fitting. If k is set sufficiently high, all of the cells within a given group will be used.
min.nonfailed	minimum number of non-failed measurements (within the k nearest neighbor cells) required for a gene to be taken into account during error fitting procedure
min.count.threshold	minimum number of reads required for a measurement to be considered non-failed
save.model.plots	whether model plots should be saved (file names are (group).models.pdf, or cell.models.pdf if no group was supplied)
max.model.plots	maximum number of models to save plots for (saves time when there are too many cells)
n.cores	number of cores to use through the calculations
min.size.entries	minimum number of genes to use for model fitting
min.fpm	optional parameter to restrict model fitting to genes with group-average expression magnitude above a given value
cor.method	correlation measure to be used in determining k nearest cells
verbose	level of verbosity
fpm.estimate.trim	trim fraction to be used in estimating group-average gene expression magnitude for model fitting (0.5 would be median, 0 would turn off trimming)
linear.fit	whether newer linear model fit with zero intercept should be used (T), or the log-fit model published originally (F)
local.theta.fit	whether local theta fitting should be used (only available for the linear fit models)
theta.fit.range	allowed range of the theta values
alpha.weight.power	1/theta weight power used in fitting theta dependency on the expression magnitude

Value

a data frame with parameters of the fit error models (rows- cells, columns- fitted parameters)

Examples

data(pollen)
cd <- clean.counts(pollen)

knn <- knn.error.models(cd, k=ncol(cd)/4, n.cores=10, min.count.threshold=2, min.nonfailed=5, max.model.plots=10)

hms-dbmi/scde documentation built on April 19, 2023, 10:21 p.m.