BEAM: Branched expression analysis modeling (BEAM).

In cole-trapnell-lab/monocle-release: Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Description

Identify genes with branch-dependent expression. Branches in single-cell trajectories are generated by cell fate decisions in development and also arise when analyzing genetic, chemical, or environmental perturbations. Branch expression analysis modeling is a statistical approach for finding genes that are regulated in a manner that depends on the branch. Consider a progenitor cell that generates two distinct cell types. A single-cell trajectory that includes progenitor cells and both differentiated cell types will capture the "decision" as a branch point, with progenitors upstream of the branch and the differentiated cells positioned along distinct branches. These branches will be characterized by distinct gene expression programs. BEAM aims to find all genes that differ between the branches. Such "branch-dependent" genes can help identify the mechanism by which the fate decision is made. BEAM() Takes a CellDataSet and either a specified branch point, or a pair of trajectory outcomes (as States). If a branch point is provided, the function returns a dataframe of test results for dependence on that branch. If a pair of outcomes is provided, it returns test results for the branch that unifies those outcomes into a common path to the trajectory's root state. BEAM() compares two models with a likelihood ratio test for branch-dependent expression. The full model is the product of smooth Pseudotime and the Branch a cell is assigned to. The reduced model just includes Pseudotime. You can modify these to include arbitrary additional effects in the full or both models.

Usage

BEAM(cds, fullModelFormulaStr = "~sm.ns(Pseudotime, df = 3)*Branch",
  reducedModelFormulaStr = "~sm.ns(Pseudotime, df = 3)",
  branch_states = NULL, branch_point = 1, relative_expr = TRUE,
  branch_labels = NULL, verbose = FALSE, cores = 1, ...)

Arguments

cds	a CellDataSet object upon which to perform this operation
fullModelFormulaStr	a formula string specifying the full model in differential expression tests (i.e. likelihood ratio tests) for each gene/feature.
reducedModelFormulaStr	a formula string specifying the reduced model in differential expression tests (i.e. likelihood ratio tests) for each gene/feature.
branch_states	ids for the immediate branch branch which obtained from branch construction based on MST
branch_point	The ID of the branch point to analyze. Can only be used when reduceDimension is called with method = "DDRTree".
relative_expr	a logic flag to determine whether or not the relative gene expression should be used
branch_labels	the name for each branch, for example, "AT1" or "AT2"
verbose	Whether to generate verbose output
cores	the number of cores to be used while testing each gene for differential expression
...	additional arguments to be passed to differentialGeneTest

Value

a data frame containing the p values and q-values from the BEAM test, with one row per gene.

cole-trapnell-lab/monocle-release documentation built on May 13, 2019, 8:50 p.m.