Ringo (version 1.36.0)

cher-class: Class "cher" - ChIP-enriched region

Description

An object of class cher (ChIP-enriched region) holds characteristics of an enriched genomic region from ChIP chip data.

Objects from the Class

Objects can be created by calls of the form new("cher", name, chromosome, start, end, cellType, antibody, maxLevel, score, probes, extras, ...).

Slots

name:

character vector of length 1 unequivocally describing the cher, e.g. "Suz12.Nudt2.upstream.cher"

chromosome:

character vector of length one, naming the chromosome of the region, e.g. "9"

start:

integer, region start position on the chromosome, e.g. 34318900

end:

integer, region end position on the chromosome, e.g. 34320100

cellType:

character vector describing the cell type the ChIP chip experiment has been done on, e.g. "HeLa" or "human"

antibody:

character vector describing the antibody or characteristic for which fragments were supposedly enriched in immuno-precipitation step, e.g. "Suz12" for the protein Suz12

maxLevel:

numeric, maximal (smoothed) probe level in the cher, e.g. 2.00

score:

numeric of a cher score, currently we use the sum of smoothed probe levels (log fold changes), e.g. 69.16

probes:

vector of probe identifiers of all probes with match positions in the cher

extras:

list of further elements used to annotate the cher; examples of such that are used in Ringo are:

typeUpstream

optional character vector of features that this cher is located upstream of, e.g. the transcriptional start site of "ENST00000379158". See relateChers for details.

typeInside

optional character vector of features that this cher is located inside of

distMid2TSS

optional named numeric vector of distances of the cher's middle position to features, e.g. TSSs of features upstream and inside; names are the features to which the distances are given; only meaningful in combination with typeUpstream and typeInside; e.g. 55 with name "ENST00000379158"

upSymbol

optional character vector of gene symbols of features the cher is located upstream of; supplements typeUpstream; e.g. "Nudt2"

inSymbol

optional character vector of gene symbols of features the cher is located upstream of; supplements typeInside.

...

further list elements can be added using the update method.

Methods

initialize

create a new cher; see section examples below

plot

calls chipAlongChrom to plot the cher; see plot.cher for more details

update

signature(cher,...); updates elements of the cher object; The further arguments in '...' are interpreted. Arguments corresponding to defined slot names of the cher result in the value by that slot being replaced by the specified value for the argument; argument names that do not correspond to slot names of the object result in list elements of the extras list of the cher being replaced by the given values for these arguments or the values are appended to the current extras list and the argument names make up the list names of the appended arguments. See section examples below for an example how to use this method.

cellType

obtain or replace the description of the cell type, the ChIP-enriched regions was found in with this antibody

probes

obtain the vector of probes involved in a ChIP-enriched region

cherList

A list in which each element is of class cher, is called a cherList. This class, however, is rarely used (yet).

See Also

plot.cher, findChersOnSmoothed, relateChers

Examples

  ## how to create a cher object from scratch
  cherNudt2 <- new("cher", name="nudt2.cher", chromosome=9,
                   start=34318954, end=34319944, antibody="Suz12",
                   maxLevel=2.00, score=69.2, upSymbol="NUDT2")
                   #extras=list(upSymbol="NUDT2"))
  cherNudt2
  str(cherNudt2)

  ## use the update method (note:this update is biologically meaningless)
  cher2 <- update(cherNudt2, cellType="HeLa", downSymbol="P53",
                  probes=c("probe1","probe2"))
  cher2; str(cher2)

  ## plot a cher object
  exDir <- system.file("exData",package="Ringo")
  load(file.path(exDir,"exampleProbeAnno.rda"))
  load(file.path(exDir,"exampleX.rda"))
  smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
       modColumn = "Cy5", allChr = "9", winHalfSize = 400)
  plot(cherNudt2, smoothX, probeAnno=exProbeAnno, gff=exGFF, extent=5000)