plotGLM {MORE}R Documentation

Plot MORE results

Description

MORE includes the possibility of studying graphically the relationship of genes and regulators: given a specific gene and regulator, study the regulators for a given gene, analyze which genes are regulated by a specific regulator...

Usage

plotGLM(GLMoutput, gene, regulator = NULL, reguValues = NULL,
plotPerOmic = FALSE, gene.col = 1, regu.col = NULL, order = TRUE,
xlab = "", cont.var = NULL, cond2plot = NULL,...)

Arguments

GLMoutput

It is the name of the object where we have saved the execution of the function getGLM.

gene

ID of the gene to be plotted.

regulator

ID of the regulator to be plotted. If NULL (default value), all the regulators of the gene are plotted.

reguValues

Vector containing the values of a regulator that the user can optionally provide. If NULL (default value), these values are taken from GLMoutput as long as they are available.

plotPerOmic

If TRUE, all the significant regulators of the given gene and the same omic are plotted in the same graph. If FALSE (default value), each regulator is plotted in a separate plot.

gene.col

Color to plot the gene. By default, 1 (black).

regu.col

Color to plot the regulator. If NULL (default), a color will be assigned by the function, that will be different for each regulatory omic.

order

If TRUE (default), the values in X axis are ordered.

xlab

Label for X axis.

cont.var

Vector with length equal to the number of observations in data, which optionally may contain the values of the numerical variable (e.g. time) to be plotted in X axis. By default, NULL.

cond2plot

Vector or factor indicating the experimental group of each value to represent. If NULL (default), the labels are taken from the experimental design matrix.

Author(s)

Sonia Tarazona, Blanca Tomas Riquelme

See Also

GetGLM TestData

Examples

data(TestData)
require(MASS); require(igraph); require(car); require(glmnet); require(psych)

## Omic type
OmicType = c(1, 0, 0)
names(OmicType) = names(TestData$data.omics)

## GetGLM function
SimGLM = GetGLM(GeneExpression = TestData$GeneExpressionDE,
                associations = TestData$associations,
                data.omics = TestData$data.omics,
                edesign = TestData$edesign[,-1, drop = FALSE],
                Res.df = 10,
                epsilon = 0.00001,
                alfa = 0.05,
                MT.adjust = "fdr",
                family = negative.binomial(theta = 10),
                elasticnet = 0.7,
                stepwise = "two.ways.backward",
                interactions.reg = TRUE,
                correlation = 0.8,
                min.variation = 0,
                min.obs = 10,
                omic.type = OmicType)

## Given a gene and regulator
plotGLM(GLMoutput = SimGLM,
          gene = "ENSMUSG00000012535",
          regulator = "6_29609160_29609425",
          plotPerOmic = FALSE,
          gene.col = "red4",
          regu.col = "green4")

## Given a gene
par(mfrow = c(2,2))
plotGLM(GLMoutput = SimGLM,
          gene = "ENSMUSG00000012535",
          regulator = NULL,
          plotPerOmic = FALSE,
          gene.col = "blue4")

## Given a regulator
plotGLM(GLMoutput = SimGLM,
          gene = NULL,
          regulator = "mmu-miR-15a-3p",
          plotPerOmic = FALSE,
          gene.col = "red4",
          regu.col = "green4")

## With cont.var parameter
plotGLM(GLMoutput = SimGLM,
          gene = "ENSMUSG00000026563",
          regulator = "Sp100",
          plotPerOmic = FALSE,
          gene.col = "darkblue",
          regu.col = "green4",
          cont.var = c(1,2,3,4,5,6,7,8),
          xlab = "CondA | CondB")

[Package MORE version 0.1.0 Index]