BASiCS (version 0.7.30)

BASiCS_DetectHVG: Detection method for highly and lowly variable genes

Description

Functions to detect highly and lowly variable genes

Usage

BASiCS_DetectHVG(Data, object, VarThreshold, EviThreshold = NULL,
  OrderVariable = "Prob", Plot = FALSE, ...)
BASiCS_DetectLVG(Data, object, VarThreshold, EviThreshold = NULL,
  OrderVariable = "Prob", Plot = FALSE, ...)

Arguments

Data

an object of class BASiCS_Data-class

object

an object of class BASiCS_Chain-class

VarThreshold

Variance contribution threshold (must be a positive value, between 0 and 1)

EviThreshold

Optional parameter. Evidence threshold (must be a positive value, between 0 and 1)

OrderVariable

Ordering variable for output. Must take values in c("GeneIndex", "Mu", "Delta", "Sigma", "Prob").

Plot

If Plot = T a plot of the gene specific expression level against HVG or LVG is generated.

...

Graphical parameters (see par).

Value

BASiCS_DetectHVG returns a list of 4 elements:

Table

Matrix whose columns contain

Mu

Vector of length q.bio. For each biological gene, posterior median of gene-specific expression levels \(\mu[i]\)

Delta

Vector of length q.bio. For each biological gene, posterior median of gene-specific biological cell-to-cell heterogeneity hyper-parameter \(\delta[i]\)

Sigma

Vector of length q.bio. For each biological gene, proportion of the total variability that is due to a cell-to-cell 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.

EviThreshold

Evidence 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 element HVG by LVG, an indicator of a gene being detected as lowly variable according to the given thresholds.

Details

See vignette

References

Vallejos, Marioni and Richardson (2015). Bayesian Analysis of Single-Cell Sequencing data.

See Also

BASiCS_Chain-class

Examples

# NOT RUN {
# See
help(BASiCS_MCMC)

# }