extract_outputs: Extract annotation of genes, zones, outstanding zones, and...
In GenomicOZone: Delineate outstanding genomic zones of differential gene activity

Description Usage Arguments Details Value References See Also Examples

Extract informtation from the output of GenomicOZone function, including a gene annotation object, a zone annotation object, an outstanding zone annotation object, or a zone activity matrix, respectively. The activity of genes without annotation is appended at the bottom of the zone activity matrix.

  extract_genes(GOZ.ds)

  extract_zones(GOZ.ds)

  extract_outstanding_zones(
                GOZ.ds,
                alpha = 0.05,
                min.effect.size = 0.8)

  extract_zone_expression(GOZ.ds)

`GOZ.ds`	a object returned from the `GenomicOZone` function.
`alpha`	a cutoff for adjusted `p`-values. Default to 0.05.
`min.effect.size`	the minimum effect size required for an outstanding zone. The effect size for ANOVA ranging from 0 to 1 is calculated by R package sjstats \insertCitesjstats2019GenomicOZone. Default to 0.8.

These functions take the input of an object created by GOZDataSet and processed by GenomicOZone. The functions access the object and fetch the results. The function extract_zone_expression offers the zone activity matrix. The activity of a zone is the total activity of genes within the zone for each sample. The activity of genes without annotation is included as last rows in the zone activity matrix.

The first three functions return an object of GRanges class \insertCitelawrence2013grangesGenomicOZone for all genes, all zones and outstanding genomic zones only. The gene GRanges object includes genome annotation and the zones where the genes belong. The zone GRanges object includes zone positions and p-values of differential zone analysis. Outstanding genomic zones are a subset of all zones that satisfy required p-value and effect size.

\insertAllCited

See GOZDataSet for how to create the input object before outstanding genomic zone analysis. The object must contain information obtained from outstanding zone analysis function GenomicOZone.

  # Create an object of GOZ.ds
  data <- matrix(c(1,5,2,6,5,1,6,2), ncol = 2, byrow = TRUE)
  rownames(data) <- paste("Gene", 1:4, sep='')
  colnames(data) <- paste("Sample", c(1:2), sep='')

  colData <- data.frame(Sample_name = paste("Sample", c(1:2), sep=''),
                        Condition = c("Cancer", "Normal"))

  design <- ~ Condition

  rowData.GRanges <- GRanges(seqnames = Rle(rep("chr1", 4)),
                             ranges = IRanges(start = c(1,2,3,4), end = c(5,6,7,8)))
  names(rowData.GRanges) <- paste("Gene", 1:4, sep='')

  ks <- c(2)
  names(ks) <- "chr1"

  GOZ.ds <- GOZDataSet(data, colData, design,
                       rowData.GRanges = rowData.GRanges,
                       ks = ks)
  ####

  # Run outstanding zone analysis
  GOZ.ds <- GenomicOZone(GOZ.ds)
  ####

  # Extract output in various formats
  Gene.GRanges <- extract_genes(GOZ.ds)
  head(Gene.GRanges)

  Zone.GRanges <- extract_zones(GOZ.ds)
  head(Zone.GRanges)

  OZone.GRanges <- extract_outstanding_zones(
                                GOZ.ds,
                                alpha = 0.05,
                                min.effect.size = 0.8)
  head(OZone.GRanges)

  Zone.exp.mat <- extract_zone_expression(GOZ.ds)
  head(Zone.exp.mat)