# ggcor
**Repository Path**: Genuts/ggcor
## Basic Information
- **Project Name**: ggcor
- **Description**: Extended tools for correlation analysis and visualization.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 2
- **Forks**: 2
- **Created**: 2021-04-06
- **Last Updated**: 2022-05-20
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# ggcor
[](https://www.tidyverse.org/lifecycle/#experimental)
The goal of `ggcor` is to to provide a set of functions that be used to
visualize simply and directly a correlation matrix based on ‘ggplot2’.
## Installation
Now `ggcor` is not on cran, You can install the development version of
ggcor from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("houyunhuang/ggcor")
```
## Draw correlation plot quickly
This is a basic example which shows you how to draw correlation plot
quickly:
``` r
library(ggplot2)
library(ggcor)
quickcor(mtcars) + geom_colour()
```
``` r
quickcor(mtcars, type = "upper") + geom_circle2()
```
``` r
quickcor(mtcars, cor.test = TRUE) +
geom_square(data = get_data(type = "lower", show.diag = FALSE)) +
geom_mark(data = get_data(type = "upper", show.diag = FALSE), size = 2.5) +
geom_abline(slope = -1, intercept = 12)
```
## Mantel test plot
``` r
library(vegan)
library(dplyr)
data("varechem")
data("varespec")
set.seed(20191224)
sam_grp <- sample(paste0("sample", 1:3), 24, replace = TRUE)
mantel01 <- fortify_mantel(varespec, varechem, group = sam_grp,
spec.select = list(spec01 = 1:5,
spec02 = 6:12,
spec03 = 7:18,
spec04 = 20:29,
spec05 = 30:44),
mantel.fun = "mantel.randtest")
quickcor(mantel01, legend.title = "Mantel's r") +
geom_colour() + geom_cross() + facet_grid(rows = vars(.group))
```
``` r
mantel02 <- fortify_mantel(varespec, varechem,
spec.select = list(1:10, 5:14, 7:22, 9:32)) %>%
mutate(r = cut(r, breaks = c(-Inf, 0.25, 0.5, Inf),
labels = c("<0.25", "0.25-0.5", ">=0.5"),
right = FALSE),
p.value = cut(p.value, breaks = c(-Inf, 0.001, 0.01, 0.05, Inf),
labels = c("<0.001", "0.001-0.01", "0.01-0.05", ">=0.05"),
right = FALSE))
quickcor(varechem, type = "upper") + geom_square() +
add_link(mantel02, mapping = aes(colour = p.value, size = r),
diag.label = TRUE) +
scale_size_manual(values = c(0.5, 1.5, 3)) +
add_diag_label() + remove_axis("x")
#> Warning: `add_diag_label()` is deprecated. Use `geom_diag_label()` instead.
```
# network
``` r
library(tidygraph)
library(ggraph)
net <- fast_correlate(varespec) %>%
as_tbl_graph(r.thres = 0.5, p.thres = 0.05) %>%
mutate(degree = tidygraph::centrality_degree(mode = "all"))
ggraph(net, "circle") +
geom_edge_fan(aes(edge_width = r, edge_linetype = r < 0),
edge_colour = "grey80", show.legend = FALSE) +
geom_node_point(aes(size = degree, colour = name),
show.legend = FALSE) +
geom_node_text(aes(x = x * 1.08, y = y * 1.08,
angle = -((-node_angle(x, y) + 90) %% 180) + 90,
label = name), size = 4, hjust= "outward",
show.legend = FALSE) +
scale_edge_color_gradientn(colours = c("blue", "red")) +
scale_edge_width_continuous(range = c(0.1, 1)) +
coord_fixed(xlim = c(-1.5, 1.5), ylim = c(-1.5, 1.5)) +
theme_graph()
```
# general heatmap
``` r
mat <- matrix(rnorm(120), nrow = 15)
cor_tbl(extra.mat = list(mat = mat)) %>%
quickcor(mapping = aes(fill = mat)) + geom_colour()
```
# upper and lower with different geom
``` r
d <- dist(t(mtcars))
correlate(mtcars, cor.test = TRUE) %>%
as_cor_tbl(extra.mat = list(dist = d)) %>%
quickcor() +
geom_upper_square(aes(upper_fill = r, upper_r0 = r)) +
geom_lower_colour(aes(lower_fill = dist)) +
geom_diag_label() +
remove_all_axis()
```
