GOChord {GOplot}

Displays the relationship between genes and terms.

Description

The GOChord function generates a circularly composited overview of selected/specific genes and their assigned processes or terms. More generally, it joins genes and processes via ribbons in an intersection-like graph. The input can be generated with the chord_dat function.

Usage

GOChord(data, title, space, gene.order, gene.size, gene.space, nlfc = 1,
  lfc.col, lfc.min, lfc.max, ribbon.col, border.size, process.label, limit)

Arguments

data

The matrix represents the binary relation (1= is related to, 0= is not related to) between a set of genes (rows) and processes (columns); a column for the logFC of the genes is optional

title

The title (on top) of the plot

space

The space between the chord segments of the plot

gene.order

A character vector defining the order of the displayed gene labels

gene.size

The size of the gene labels

gene.space

The space between the gene labels and the segement of the logFC

nlfc

Defines the number of logFC columns (default=1)

lfc.col

The fill color for the logFC specified in the following form: c(color for low values, color for the mid point, color for the high values)

lfc.min

Specifies the minimium value of the logFC scale (default = -3)

lfc.max

Specifies the maximum value of the logFC scale (default = 3)

ribbon.col

The background color of the ribbons

border.size

Defines the size of the ribbon borders

process.label

The size of the legend entries

limit

A vector with two cutoff values (default= c(0,0)). The first value defines the minimum number of terms a gene has to be assigned to. The second the minimum number of genes assigned to a selected term.

Details

The gene.order argument has three possible options: "logFC", "alphabetical", "none", which are quite self- explanatory.

Maybe the most important argument of the function is nlfc.If your data does not contain a column of logFC values you have to set nlfc = 0. Differential expression analysis can be performed for multiple conditions and/or batches. Therefore, the data frame might contain more than one logFC value per gene. To adjust to this situation the nlfc argument is used as well. It is a numeric value and it defines the number of logFC columns of your data. The default is "1" assuming that most of the time only one contrast is considered.

To represent the data more useful it might be necessary to reduce the dimension of data. This can be achieved with limit. The first value of the vector defines the threshold for the minimum number of terms a gene has to be assigned to in order to be represented in the plot. Most of the time it is more meaningful to represent genes with various functions. A value of 3 excludes all genes with less than three term assignments. Whereas the second value of the parameter restricts the number of terms according to the number of assigned genes. All terms with a count smaller or equal to the threshold are excluded.

See Also

chord_dat

Examples

## Not run: 
# Load the included dataset
data(EC)

# Generating the binary matrix
chord<-chord_dat(circ,EC$genes,EC$process)

# Creating the chord plot
GOChord(chord)

# Excluding process with less than 5 assigned genes
GOChord(chord, limit = c(0,5))

# Creating the chord plot genes ordered by logFC and a different logFC color scale
GOChord(chord,space=0.02,gene.order='logFC',lfc.col=c('red','black','cyan'))

## End(Not run)