plot_bin_permute_best: plot_bin_permute_best

In LyonsZhang/ProgPerm: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries

Usage

plot_bin_permute_best(bestoutputs, top_pm, pvtitle, savepvfile, pvpicdim, estitle, saveesfile, espicdim)

Arguments

bestoutputs
top_pm
pvtitle
savepvfile
pvpicdim
estitle
saveesfile
espicdim

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (bestoutputs, top_pm, pvtitle, savepvfile, pvpicdim, 
    estitle, saveesfile, espicdim) 
{
    worstpermute <- bestoutputs$worst_case
    df1 <- data.frame(matrix(0, top_pm, 4))
    rownames(df1) <- bestoutputs$selname
    colnames(df1) <- c("trueorg", "median", "q1", "q2")
    df1$variable <- factor(rownames(df1), levels = rownames(df1))
    df1$trueorg <- bestoutputs$pvalue0
    df1$median <- as.numeric(as.character(worstpermute$pvdist[, 
        "median"]))
    df1$q1 <- as.numeric(as.character(worstpermute$pvdist[, "q1"]))
    df1$q2 <- as.numeric(as.character(worstpermute$pvdist[, "q2"]))
    df1$coverage <- ifelse((df1$q1 <= df1$trueorg & df1$trueorg <= 
        df1$q2), "inside", "outside")
    ggplot(data = df1, aes(x = variable)) + geom_errorbar(aes(ymax = q2, 
        ymin = q1)) + geom_point(aes(y = median), shape = 1, 
        size = 3) + geom_point(aes(y = trueorg, colour = coverage), 
        shape = 16, size = 3) + ylab("-log10(p-value)") + xlab(paste("Top", 
        top_pm, "significant features with decreasing order", 
        sep = " ")) + coord_flip() + ggtitle(pvtitle) + theme_bw() + 
        theme(plot.title = element_text(size = 24, face = "bold"), 
            legend.title = element_text(size = 20), legend.text = element_text(size = 16)) + 
        theme(axis.line = element_line(colour = "black"), panel.border = element_blank(), 
            panel.background = element_blank(), axis.line.x = element_line(color = "black", 
                size = 1), axis.line.y = element_line(color = "black", 
                size = 1), axis.text = element_text(size = 16, 
                face = "bold"), axis.title = element_text(size = 20, 
                face = "bold"))
    ggsave(filename = savepvfile, width = pvpicdim[1], height = pvpicdim[2])
    df2 <- data.frame(matrix(0, top_pm, 4))
    rownames(df2) <- bestoutputs$selname
    colnames(df2) <- c("trueorg", "median", "q1", "q2")
    df2$variable <- factor(rownames(df2), levels = rownames(df2))
    df2$trueorg <- bestoutputs$effectsize0
    df2$median <- as.numeric(as.character(worstpermute$esdist[, 
        "median"]))
    df2$q1 <- as.numeric(as.character(worstpermute$esdist[, "q1"]))
    df2$q2 <- as.numeric(as.character(worstpermute$esdist[, "q2"]))
    df2$coverage <- ifelse((df2$q1 <= df2$trueorg & df2$trueorg <= 
        df2$q2), "inside", "outside")
    ggplot(data = df2, aes(x = variable)) + geom_errorbar(aes(ymax = q2, 
        ymin = q1)) + geom_point(aes(y = median), shape = 1, 
        size = 3) + geom_point(aes(y = trueorg, colour = coverage), 
        shape = 16, size = 3) + ylab("Effect size") + xlab(paste("Top", 
        top_pm, "significant features with decreasing order", 
        sep = " ")) + coord_flip() + ggtitle(estitle) + theme_bw() + 
        theme(plot.title = element_text(size = 24, face = "bold"), 
            legend.title = element_text(size = 20), legend.text = element_text(size = 16)) + 
        theme(axis.line = element_line(colour = "black"), panel.border = element_blank(), 
            panel.background = element_blank(), axis.line.x = element_line(color = "black", 
                size = 1), axis.line.y = element_line(color = "black", 
                size = 1), axis.text = element_text(size = 16, 
                face = "bold"), axis.title = element_text(size = 20, 
                face = "bold"))
    ggsave(filename = saveesfile, width = espicdim[1], height = espicdim[2])
    return(list(pvtable = df1, estable = df2))
  }

LyonsZhang/ProgPerm documentation built on July 16, 2020, 12:45 a.m.