CorLevelPlot: Visualise correlation results and test significancies of...

In kevinblighe/CorLevelPlot: Visualise correlation results and test significancies of these

Description

CorLevelPlot provides a quick and colourful way to visualise statistically significant correlations between any combination of categorical and continuous variables. Moreover, the statistical significancies of these correlations are also provided.

Usage

CorLevelPlot(data,
    x,
    y,
    titleX = "",
    cexTitleX = 1.0,
    rotTitleX = 0,
    colTitleX = "black",
    fontTitleX = 2,
    titleY = "",
    cexTitleY = 1.0,
    rotTitleY = 0,
    colTitleY = "black",
    fontTitleY = 2,
    cexLabX = 1.0,
    rotLabX = 0,
    colLabX = "black",
    fontLabX = 2,
    cexLabY = 1.0,
    rotLabY = 0,
    colLabY = "black",
    fontLabY = 2,
    posLab = "bottomleft",
    col = c("blue4", "blue3", "blue2", "blue1", "white",
        "red1", "red2", "red3", "red4"),
    posColKey = "right",
    cexLabColKey = 1.0,
    cexCorval = 1.0,
    colCorval = "black",
    fontCorval = 1,
    scale = TRUE,
    main = "",
    cexMain = 2,
    rotMain = 0,
    colMain = "black",
    fontMain = 2,
    corFUN = "pearson",
    corUSE = "pairwise.complete.obs",
    signifSymbols = c("***", "**", "*", ""),
    signifCutpoints = c(0, 0.001, 0.01, 0.05, 1),
    colFrame = "white",
    plotRsquared = FALSE)

Arguments

data	A data-frame/matrix of test correlates. Can be categorical or continuous variables. REQUIRED.
x	A vector of column names in data - will be converted to numerical values. REQUIRED.
y	A vector of column names in data - will be converted to numerical values. REQUIRED.
titleX	X-axis title. DEFAULT = "". OPTIONAL.
cexTitleX	X-axis title cex. DEFAULT = 1.0. OPTIONAL.
rotTitleX	X-axis title rotation in degrees. DEFAULT = 0. OPTIONAL.
colTitleX	X-axis title colour. DEFAULT = "black". OPTIONAL.
fontTitleX	X-axis title font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.
titleY	Y-axis title. DEFAULT = "". OPTIONAL.
cexTitleY	Y-axis title cex. DEFAULT = 1.0. OPTIONAL.
rotTitleY	Y-axis title rotation in degrees. DEFAULT = 0. OPTIONAL.
colTitleY	Y-axis title colour. DEFAULT = "black". OPTIONAL.
fontTitleY	Y-axis title font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.
cexLabX	X-axis labels cex. DEFAULT = 1.0. OPTIONAL.
rotLabX	X-axis labels rotation in degrees. DEFAULT = 0. OPTIONAL.
colLabX	X-axis labels colour. DEFAULT = "black". OPTIONAL.
fontLabX	X-axis labels font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.
cexLabY	Y-axis labels cex. DEFAULT = 1.0. OPTIONAL.
rotLabY	Y-axis labels rotation in degrees. DEFAULT = 0. OPTIONAL.
colLabY	Y-axis labels colour. DEFAULT = "black". OPTIONAL.
fontLabY	Y-axis labels font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.
posLab	Positioning of the X- and Y-axis labels. "bottomleft", bottom and left; "topright", top and right; "all", bottom / top and left /right; "none", no labels. DEFAULT = "bottomleft". OPTIONAL.
col	Colour shade gradient for RColorBrewer. DEFAULT = c("blue4", "blue3", "blue2", "blue1", "white", "red1", "red2", "red3", "red4"). OPTIONAL.
posColKey	Position of colour key. "bottom", "left", "top", "right". DEFAULT = "right". OPTIONAL.
cexLabColKey	Colour key labels cex. DEFAULT = 1.0. OPTIONAL.
cexCorval	Correlation values cex. DEFAULT = 1.0. OPTIONAL.
colCorval	Correlation values colour. DEFAULT = "black". OPTIONAL.
fontCorval	Correlation values font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 1. OPTIONAL.
scale	Scale the colour range to max and min cor values? DEFAULT = TRUE. OPTIONAL.
main	Plot title. DEFAULT = "". OPTIONAL.
cexMain	Plot title cex. DEFAULT = 2. OPTIONAL.
rotMain	Plot title rotation in degrees. DEFAULT = 0. OPTIONAL.
colMain	Plot title colour. DEFAULT = "black". OPTIONAL.
fontMain	Plot title font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.
corFUN	Correlation method: "pearson", "spearman", or "kendall". DEFAULT = "pearson". OPTIONAL.
corUSE	Method for handling missing values (see documentation for cor function via ?cor). "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs". DEFAULT = "pairwise.complete.obs". OPTIONAL.
signifSymbols	Statistical significance symbols to display beside correlation values. DEFAULT = c("***", "**", "*", ""). OPTIONAL.
signifCutpoints	Cut-points for statistical significance. DEFAULT = c(0, 0.001, 0.01, 0.05, 1). OPTIONAL.
colFrame	Frame colour. DEFAULT = "white". OPTIONAL.
plotRsquared	Plot R-squared values? TRUE / FALSE. DEFAULT = FALSE. OPTIONAL.

Details

CorLevelPlot provides a quick and colourful way to visualise statistically significant correlations between any combination of categorical and continuous variables. Moreover, the statistical significancies of these correlations are also provided.

Value

A lattice object.

Author(s)

Kevin Blighe <[e-mail]>

Examples

    # simulate trait-to-eigengene data
    no.obs <- 50
    ESturquoise <- 0; ESbrown <- -0.6; ESgreen <- 0.6; ESyellow <- 0
    ESvector <- c(ESturquoise, ESbrown, ESgreen, ESyellow)
    nGenes1 <- 3000
    simulateProportions1 <- c(0.2, 0.15, 0.08, 0.06, 0.04)
    set.seed(1)
    MEgreen <- rnorm(no.obs)
    scaledy <- MEgreen * ESgreen + sqrt(1 - ESgreen ^ 2) * rnorm(no.obs)
    y <- ifelse( scaledy > median(scaledy), 2, 1)
    MEturquoise <- ESturquoise * scaledy +
        sqrt(1 - ESturquoise ^ 2) * rnorm(no.obs)
    MEblue <- 0.6 * MEturquoise + sqrt(1 - 0.6 ^ 2) * rnorm(no.obs)
    MEbrown <- ESbrown * scaledy + sqrt(1 - ESbrown ^ 2) * rnorm(no.obs)
    MEyellow <- ESyellow * scaledy + sqrt(1 - ESyellow ^ 2) * rnorm(no.obs)
    ModuleEigengeneNetwork1 <- data.frame(y, MEturquoise, MEblue, MEbrown,
        MEgreen, MEyellow)

    CorLevelPlot(data = ModuleEigengeneNetwork1,
        x = c("y", "MEturquoise", "MEblue", "MEbrown", "MEgreen", "MEyellow"),
        y = c("y", "MEturquoise", "MEblue", "MEbrown", "MEgreen", "MEyellow"),
        titleX = "X correlates",
        cexTitleX = 3.0,
        rotTitleX = 0,
        colTitleX = "forestgreen",
        fontTitleX = 2,
        titleY = "Y correlates",
        cexTitleY = 2.0,
        rotTitleY = 100,
        colTitleY = "gold",
        fontTitleY = 4,
        cexLabX = 1.0,
        rotLabX = 45,
        colLabX = "grey20",
        fontLabX = 1,
        cexLabY = 1.0,
        rotLabY = 30,
        colLabY = "royalblue",
        fontLabY = 1,
        posLab = "bottomleft",
        col = c("blue4", "blue3", "blue2", "blue1", "white",
            "red1", "red2", "red3", "red4"),
        posColKey = "right",
        cexLabColKey = 1.0,
        cexCorval = 1.0,
        colCorval = "black",
        fontCorval = 4,
        scale = TRUE,
        main = "WGCNA example",
        cexMain = 2,
        rotMain = 360,
        colMain = "red4",
        fontMain = 4,
        corFUN = "pearson",
        corUSE = "pairwise.complete.obs",
        signifSymbols = c("***", "**", "*", ""),
        signifCutpoints = c(0, 0.001, 0.01, 0.05, 1),
        colFrame = "white",
        plotRsquared = FALSE)

kevinblighe/CorLevelPlot documentation built on Feb. 20, 2020, 2:54 p.m.