BASiCS_VarThresholdSearchHVG {BASiCS} | R Documentation

## Detection method for highly and lowly variable genes using a grid of variance contribution thresholds

### Description

Detection method for highly and lowly variable genes using a grid of variance contribution thresholds. Only used when HVG/LVG are found based on the variance decomposition.

### Usage

    BASiCS_VarThresholdSearchHVG(Chain, VarThresholdsGrid, EFDR = 0.1,
      Progress = TRUE)

    BASiCS_VarThresholdSearchLVG(Chain, VarThresholdsGrid, EFDR = 0.1,
      Progress = TRUE)

### Arguments

`Chain` | an object of class `BASiCS_Chain`
`VarThresholdsGrid` | Grid of values for the variance contribution threshold (they must be contained in (0,1))
`EFDR` | Target for expected false discovery rate related to HVG/LVG detection. Default: `EFDR = 0.10`.
`Progress` | If `Progress = TRUE`, partial output is printed in the console. Default: `Progress = TRUE`.

### Details

See vignette

### Value

`BASiCS_VarThresholdSearchHVG`

  A table displaying the results of highly variable genes detection for different variance contribution thresholds.

`BASiCS_VarThresholdSearchLVG`

  A table displaying the results of lowly variable genes detection for different variance contribution thresholds.

### Author(s)

Catalina A. Vallejos cnvallej@uc.cl

### References

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

### See Also

`BASiCS_Chain`

### Examples

    data(ChainSC)

    BASiCS_VarThresholdSearchHVG(ChainSC,
                                 VarThresholdsGrid = seq(0.55,0.65,by=0.01),
                                 EFDR = 0.10)
    BASiCS_VarThresholdSearchLVG(ChainSC,
                                 VarThresholdsGrid = seq(0.35,0.45,by=0.01),
                                 EFDR = 0.10)

[Package BASiCS version 1.6.0 Index]