R: Detection method for highly and lowly variable genes

BASiCS_DetectHVG {BASiCS}

R Documentation

Detection method for highly and lowly variable genes

Description

Functions to detect highly and lowly variable genes

Usage

BASiCS_DetectHVG(Chain, VarThreshold, ProbThreshold = NULL, EFDR = 0.1,
  OrderVariable = "Prob", Plot = FALSE, ...)

BASiCS_DetectLVG(Chain, VarThreshold, ProbThreshold = NULL, EFDR = 0.1,
  OrderVariable = "Prob", Plot = FALSE, ...)

Arguments

`Chain`	an object of class `BASiCS_Chain`
`VarThreshold`	Variance contribution threshold (must be a positive value, between 0 and 1)
`ProbThreshold`	Optional parameter. Posterior probability threshold (must be a positive value, between 0 and 1)
`EFDR`	Target for expected false discovery rate related to HVG/LVG detection (default = 0.10)
`OrderVariable`	Ordering variable for output. Possible values: `'GeneIndex'`, `'Mu'`, `'Delta'`, `'Sigma'` and `'Prob'`.
`Plot`	If `Plot = TRUE` error control and expression versus HVG/LVG probability plots are generated
`...`	Graphical parameters (see `par`).

Details

See vignette

Value

BASiCS_DetectHVG returns a list of 4 elements:

Table: Matrix whose columns contain

GeneIndex: Vector of length q.bio. Gene index as in the order present in the analysed SingleCellExperiment
GeneName: Vector of length q.bio. Gene name as in the order present in the analysed SingleCellExperiment
Mu: Vector of length q.bio. For each biological gene, posterior median of gene-specific mean expression parameters μ_i
Delta: Vector of length q.bio. For each biological gene, posterior median of gene-specific biological over-dispersion parameter δ_i
Sigma: Vector of length q.bio. For each biological gene, proportion of the total variability that is due to a biological heterogeneity component.
Prob: Vector of length q.bio. For each biological gene, probability of being highly variable according to the given thresholds.
HVG: Vector of length q.bio. For each biological gene, indicator of being detected as highly variable according to the given thresholds.

ProbThreshold: Posterior probability threshold.
EFDR: Expected false discovery rate for the given thresholds.
EFNR: Expected false negative rate for the given thresholds.

BASiCS_DetectLVG produces a similar output, replacing the column HVG by LVG, an indicator of a gene being detected as lowly variable according to the given thresholds.

Author(s)

Catalina A. Vallejos cnvallej@uc.cl

References

Vallejos, Marioni and Richardson (2015). PLoS Computational Biology.

Examples


# See
help(BASiCS_MCMC)

[Package BASiCS version 1.2.1 Index]