PreprocConfig-class: PreprocConfig class
In dravishays/scandal: A framework for single-cell analysis

Description Usage Arguments Functions Slots Methods Author(s) Examples

An S4 class for storing preprocessing configuration parameters.

PreprocConfig(
  complexityCutoff,
  expressionCutoff,
  housekeepingCutoff,
  logBase,
  scalingFactor,
  pseudoCount,
  typeMatrix
)

NucseqPreprocConfig()

SS2PreprocConfig()

DefaultPreprocConfig()

## S4 method for signature 'PreprocConfig'
complexityCutoff(x, sid = NULL)

## S4 replacement method for signature 'PreprocConfig'
complexityCutoff(x) <- value

## S4 method for signature 'PreprocConfig'
expressionCutoff(x, sid = NULL)

## S4 replacement method for signature 'PreprocConfig'
expressionCutoff(x) <- value

## S4 method for signature 'PreprocConfig'
housekeepingCutoff(x, sid = NULL)

## S4 replacement method for signature 'PreprocConfig'
housekeepingCutoff(x) <- value

## S4 method for signature 'PreprocConfig'
logBase(x)

## S4 replacement method for signature 'PreprocConfig'
logBase(x) <- value

## S4 method for signature 'PreprocConfig'
scalingFactor(x)

## S4 replacement method for signature 'PreprocConfig'
scalingFactor(x) <- value

## S4 method for signature 'PreprocConfig'
pseudoCount(x)

## S4 replacement method for signature 'PreprocConfig'
pseudoCount(x) <- value

## S4 method for signature 'PreprocConfig'
typeMatrix(x)

## S4 replacement method for signature 'PreprocConfig'
typeMatrix(x) <- value

## S4 method for signature 'PreprocConfig'
show(object)

`complexityCutoff`	A numeric vector of length 2 representing the lower and upper bounds of complexity (i.e. the number of detected genes per cell).
`expressionCutoff`	A numeric representing the minimal log2 mean expression per gene below which a gene is considered lowly expressed.
`housekeepingCutoff`	A numeric representing the log2 mean expression of house-keeping genes (i.e. genes that are highly expressed in all cells) per cell below which a cell is considered low quality.
`logBase`	A numeric representing the logarithm base for performing log transformation on the data.
`scalingFactor`	A numeric representing a scaling factor by which to divide each data point before log transformation.
`pseudoCount`	A numeric representing the pseudo count added when performing log transformation to avoid taking the log of zero.
`typeMatrix`	A logical indicating if the dataset should be represented using the S4 Matrix class (instead of base R matrix) to reduce memory overhead using sparse matrix representation.
`x`	a `PreprocConfig` object.
`value`	a value to replace the currently set value.

PreprocConfig: Constructs a new PreprocConfig object.
NucseqPreprocConfig: constructs default preprocessing configuration for data generated from frozen samples using SmartSeq2 protocol (single-nuclei sequencing).
SS2PreprocConfig: constructs default preprocessing configuration for data generated from fresh samples using SmartSeq2 protocol.
DefaultPreprocConfig: constructs default preprocessing configuration (currently trhe selected default configuration is Nucseq).

complexityCutoff: A numeric vector of length 2 representing the lower and upper bounds of complexity (i.e. the number of detected genes per cell).
expressionCutoff: A numeric representing the minimal log2 mean expression per gene below which a gene is considered lowly expressed.
housekeepingCutoff: A numeric representing the log2 mean expression of house-keeping genes (i.e. genes that are highly expressed in all cells) per cell below which a cell is considered low quality.
logBase: A numeric representing the logarithm base for performing log transformation on the data.
scalingFactor: A numeric representing a scaling factor by which to divide each data point before log transformation.
pseudoCount: A numeric representing the pseudo count added when performing log transformation to avoid taking the log of zero.
typeMatrix: A logical indicating if the dataset should be represented using the S4 Matrix class (instead of base R matrix) to reduce memory overhead using sparse matrix representation.

complexityCutoff: Getter/setter for the complexity cutoff
expressionCutoff: Getter/setter for the expression cutoff
housekeepingCutoff: Getter/setter for the housekeeping cutoff
logBase: Getter/setter for the log base
scalingFactor: Getter/setter for the scaling factor
pseudoCount: Getter/setter for the pseudo count
typeMatrix: Getter/setter for the Matrix type

Avishay Spitzer

pc <- PreprocConfig(complexityCutoff = c(0, 10000),
                    expressionCutoff = 5,
                    housekeepingCutoff = 7,
                    logBase = 2,
                    scalingFactor = 10,
                    pseudoCount = 1,
                    typeMatrix = TRUE)

logBase(pc) # Equals 2
logBase(pc) <- 10
logBase(pc) # Equals 10