STGlocalMarkers: STG local markers Run STG to find a set of genes that...

In KlugerLab/DAseq: Detecting regions of differential abundance between scRNA-seq datasets

Description

STG local markers Run STG to find a set of genes that separate a given DA region from a local subset of cells.

Usage

STGlocalMarkers(X, da.regions, da.region.to.run, cell.label.info,
  cell.label.to.run, ...)

Arguments

X	matrix, normalized expression matrix of all cells in the dataset, genes are in rows, rownames must be gene names
da.regions	output from the function getDAregion()
da.region.to.run	numeric, which (single) DA region to find local markers for
cell.label.info	vector, cell labeling information to select the local subset of cells to compare with input DA region
cell.label.to.run	cell label(s) to select from cell.label.info that represent the local neiborhood for the input DA region
lambda	numeric, regularization parameter that weights the number of selected genes, a larger lambda leads to fewer genes, default 1.5
n.runs	integer, number of runs to run the model, default 5
python.use	character string, the Python to use, default "/usr/bin/python"
return.model	a logical value to indicate whether to return the actual model of STG
GPU	which GPU to use, default ”, using CPU

Value

a list of results:

markers

a list of data.frame with markers for each DA region

accuracy

a numeric vector showing mean accuracy for each DA region

model

a list of model for each DA region, each model contains:

model

the model of STG of the final run

features

features used to train the model

selected.features

the selected features of the final run

pred

the linear prediction value for each cell from the model

KlugerLab/DAseq documentation built on April 13, 2021, 9:02 p.m.