FilterParam-class {VanillaICE} | R Documentation

## Container for the common criteria used to filtering genomic ranges

### Description

The maximum a posteriori estimate of the trio copy number state for each genomic range is represented in a `GRanges`-derived class. Ultimately, these ranges will be filtered based on the trio copy number state (e.g., denovo deletions), size, number of features (SNPs), or chromosome. `FilterParam` is a container for the parameters commmonly used to filter the genomic ranges.

### Usage

    FilterParam(
      probability = 0.99,
      numberFeatures = 10,
      seqnames = paste0("chr", c(1:22, "X", "Y")),
      state = as.character(1:6),
      width = 1L
    )

    ## S4 method for signature 'FilterParam'
    probability(object)

    ## S4 method for signature 'FilterParam'
    state(object)

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

### Arguments

`probability` | minumum probability for the call
`numberFeatures` | minumum number of SNPs/nonpolymorphic features in a region
`seqnames` | the seqnames (character string or `Rle` to keep)
`state` | character: the HMM states to keep
`width` | the minimum widht of a region
`object` | a `FilterParam` object

### Slots

`probability`

  a length-one numeric vector indicating the minimum posterior probability for the called state. Genomic intervals with posterior probabilities below `probability` will be filtered.

`numberFeatures`

  a positive integer indicating the minimum number of features in a segment

`seqnames`

  a character vector of `seqnames` to select (i.e., 'chr1' for only those intervals on chromosome 1)

`width`

  positive integer indicating the minimal width of genomic intervals

`state`

  character string indicating which hidden Markov model states to select

### See Also

`cnvFilter` `cnvSegs` `hmm2`

### Examples

    fp <- FilterParam()
    width(fp)
    numberFeatures(fp)
    seqnames(fp)
    ## To select CNV segments for which
    ## - the CNV call has a 'posterior' probability of at least 0.95
    ## - the number of features is at least 10
    ## - the HMM states are 1 (homozygous deletion) or 2 (hemizygous deletion)
    FilterParam(probability=0.95, numberFeatures=10, state=c("1", "2"))

[Package VanillaICE version 1.52.0 Index]