consensus_trait_cor {BioNERO} | R Documentation

## Correlate set-specific modules and consensus modules to sample information

### Description

Correlate set-specific modules and consensus modules to sample information

### Usage

    consensus_trait_cor(
      consensus,
      cor_method = "spearman",
      continuous_trait = FALSE,
      palette = "RdYlBu",
      cex.lab.x = 0.6,
      cex.lab.y = 0.6,
      cex.text = 0.6,
      transpose = FALSE
    )

### Arguments

`consensus` | Consensus network returned by `consensus_modules`.
`cor_method` | Correlation method to be used. One of 'spearman' or 'pearson'. Default is 'spearman'.
`continuous_trait` | Logical indicating if trait is a continuous variable. Default is FALSE.
`palette` | RColorBrewer's color palette to use. Default is "RdYlBu", a palette ranging from blue to red.
`cex.lab.x` | Font size for x axis labels. Default: 0.6.
`cex.lab.y` | Font size for y axis labels. Default: 0.6.
`cex.text` | Font size for numbers inside matrix. Default: 0.6.
`transpose` | Logical indicating whether to transpose the heatmap of not. Default is FALSE.

### Details

Significance levels: 1 asterisk: significant at alpha = 0.05. 2 asterisks: significant at alpha = 0.01. 3 asterisks: significant at alpha = 0.001. no asterisk: not significant.

### Value

Data frame of consensus module-trait correlations and p-values.

### See Also

`corPvalueFisher`,`labels2colors`,`labeledHeatmap`,`blueWhiteRed`

### Examples

    set.seed(12)
    data(zma.se)
    filt.zma <- filter_by_variance(zma.se, n=500)
    zma.set1 <- filt.zma[, sample(colnames(filt.zma), size=20, replace=FALSE)]
    zma.set2 <- filt.zma[, sample(colnames(filt.zma), size=20, replace=FALSE)]
    list.sets <- list(zma.set1, zma.set2)
    # SFT power previously identified with consensus_SFT_fit()
    consensus <- consensus_modules(list.sets, power = c(11, 13),
                                   cor_method = "pearson")
    consensus_trait <- consensus_trait_cor(consensus, cor_method = "pearson")

[Package BioNERO version 1.0.4 Index]