Bimap-toTable: Methods for manipulating a Bimap object in a data-frame style
In AnnotationDbi: Manipulation of SQLite-based annotations in Bioconductor

Description Usage Arguments Details Value Author(s) See Also Examples

These methods are part of the Bimap interface (see ?Bimap for a quick overview of the Bimap objects and their interface).

  ## Extract all the columns of the map (links + right attributes)
  toTable(x, ...)
  nrow(x)
  ncol(x)
  #dim(x)
  ## S4 method for signature 'FlatBimap'
head(x, ...)
  ## S4 method for signature 'FlatBimap'
tail(x, ...)

  ## Extract only the links of the map
  links(x)
  count.links(x)
  nhit(x)

  ## Col names and col metanames
  colnames(x, do.NULL=TRUE, prefix="col")
  colmetanames(x)
  Lkeyname(x)
  Rkeyname(x)
  keyname(x)
  tagname(x)
  Rattribnames(x)
  Rattribnames(x) <- value

`x`	A Bimap object (or a list or an environment for `nhit`).
`...`	Further arguments to be passed to or from other methods (see `head` or `tail` for the details).
`do.NULL`	Ignored.
`prefix`	Ignored.
`value`	A character vector containing the names of the new right attributes (must be a subset of the current right attribute names) or NULL.

toTable(x) turns Bimap object x into a data frame (see section "Flat representation of a bimap" in ?Bimap for a short introduction to this concept). For simple maps (i.e. no tags and no right attributes), the resulting data frame has only 2 columns, one for the left keys and one for the right keys, and each row in the data frame represents a link (or edge) between a left and a right key. For maps with tagged links (i.e. a tag is associated to each link), toTable(x) has one additional colmun for the tags and there is still one row per link. For maps with right attributes (i.e. a set of attributes is associated to each right key), toTable(x) has one additional colmun per attribute. So for example if x has tagged links and 2 right attributes, toTable(x) will have 5 columns: one for the left keys, one for the right keys, one for the tags, and one for each right attribute (always the rightmost columns). Note that if at least one of the right attributes is multivalued then more than 1 row can be needed to represent the same link so the number of rows in toTable(x) can be strictly greater than the number of links in the map.

nrow(x) is equivalent to (but more efficient than) nrow(toTable(x)).

ncol(x) is equivalent to (but more efficient than) ncol(toTable(x)).

colnames(x) is equivalent to (but more efficient than) colnames(toTable(x)). Columns are named accordingly to the names of the SQL columns where the data are coming from. An important consequence of this that they are not necessarily unique.

colmetanames(x) returns the metanames for the column of x that are not right attributes. Valid column metanames are "Lkeyname", "Rkeyname" and "tagname".

Lkeyname, Rkeyname, tagname and Rattribnames return the name of the column (or columns) containing the left keys, the right keys, the tags and the right attributes, respectively.

Like toTable(x), links(x) turns x into a data frame but the right attributes (if any) are dropped. Note that dropping the right attributes produces a data frame that has eventually less columns than toTable(x) and also eventually less rows because now exactly 1 row is needed to represent 1 link.

count.links(x) is equivalent to (but more efficient than) nrow(links(x)).

nhit(x) returns a named integer vector indicating the number of "hits" for each key in x i.e. the number of links that start from each key.

A data frame for toTable and links.

A single integer for nrow, ncol and count.links.

A character vector for colnames, colmetanames and Rattribnames.

A character string for Lkeyname, Rkeyname and tagname.

A named integer vector for nhit.

H. Pagès

Bimap, BimapFormatting, Bimap-envirAPI

  library(GO.db)
  x <- GOSYNONYM
  x
  toTable(x)[1:4, ]
  toTable(x["GO:0007322"])
  links(x)[1:4, ]
  links(x["GO:0007322"])

  nrow(x)
  ncol(x)
  dim(x)
  colnames(x)
  colmetanames(x)
  Lkeyname(x)
  Rkeyname(x)
  tagname(x)
  Rattribnames(x)

  links(x)[1:4, ]
  count.links(x)

  y <- GOBPCHILDREN
  nhy <- nhit(y) # 'nhy' is a named integer vector
  identical(names(nhy), keys(y)) # TRUE
  table(nhy)
  sum(nhy == 0) # number of GO IDs with no children
  names(nhy)[nhy == max(nhy)] # the GO ID(s) with the most direct children

  ## Some sanity check
  sum(nhy) == count.links(y) # TRUE

  ## Changing the right attributes of the GOSYNONYM map (advanced
  ## users only)
  class(x) # GOTermsAnnDbBimap
  as.list(x)[1:3]
  colnames(x)
  colmetanames(x)
  tagname(x) # untagged map
  Rattribnames(x)
  Rattribnames(x) <- Rattribnames(x)[3:1]
  colnames(x)
  class(x) # AnnDbBimap
  as.list(x)[1:3]