cycle_npreg_insample: Obtain cyclic trend estimates from the training data

In peco: A Supervised Approach for **P**r**e**dicting **c**ell Cycle Pr**o**gression using scRNA-seq data

Description

Estimates cyclic trends of gene expression levels using training data.

Usage

cycle_npreg_insample(Y, theta, ncores = 2, polyorder = 2,
  method.trend = c("trendfilter", "loess", "bspline"))

Arguments

Y	A matrix of normalized and transformed gene expression values. Gene by sample.
theta	A vector of angles.
ncores	We use doParallel package for parallel computing.
polyorder	We estimate cyclic trends of gene expression levels using nonparamtric trend filtering. The default fits second degree polynomials.
method.trend	Varous methods that can be applied to estimate cyclic trend of gene expression levels.

Value

A list with four elements:

Y	Gene expression marix.
theta	Vector of angles or cell cycle phases.
sigma_est	Estimated standard error of the cyclic trend for each gene.
funs_est	A list of functions for approximating the cyclic trends of gene express levels for each gene.

Author(s)

Joyce Hsiao

See Also

cycle_npreg_mstep for estimating cyclic functions given inferred phases from cycle_npreg_loglik, cycle_npreg_outsample for predicting cell cycle phase using parameters learned from cycle_npreg_insample

Other peco classifier functions: cycle_npreg_loglik, cycle_npreg_mstep, cycle_npreg_outsample, initialize_grids

Examples

# see \code{\link{cycle_npreg_insample}}

peco documentation built on Nov. 8, 2020, 8:16 p.m.