PhenoCorr.Rmd

---
title: "PhenoCorr"
author: "Ye Bi"
date: "`r Sys.Date()`"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r}
library(ggplot2)
library(plyr)
library(pheatmap)
library(corrplot)
library(gridGraphics)
library(grid)
```


```{r}
source("../Functions/functions.R")
met_names = met_name_func(mode = 'name')
# met_names = 1:66
```

###########
## heatmap for met.rr phenotypic correlation
###########
```{r}
met.rr.con = read.csv("../../Met/met_rr_control_named.csv")
cor_con = cor(met.rr.con[,-c(1:2)])
met.rr.trt = read.csv("../../Met/met_rr_stress_named.csv")
cor_trt = cor(met.rr.trt[,-c(1:2)])
```

```{r}

p1=corrplot(cor_con, tl.col="black", tl.cex = .5, tl.pos="ld", tl.srt = 10, method="circle", type="lower", cl.ratio=0.1, title = "(A)", mar=c(0,0,1,0))
# grid.echo()
P1 <- grid.grab()
# dev.print(pdf, file=paste0("../temp/heatmap_pheno_corr_control.pdf"), height=6, width=10)
p2=corrplot(cor_trt, tl.col="black", tl.cex = .5, tl.pos="ld", tl.srt = 10, method="circle", type="lower", cl.ratio=0.1, title = "(B)", mar=c(0,0,1,0))
# grid.echo()
P2 <- grid.grab()
# dev.print(pdf, file=paste0("../temp/heatmap_pheno_corr_stress.pdf"), height=6, width=10)

```

```{r}
cor_matrix = cor_con
# Find pairs with correlation values greater than 0.5
high_cor_pairs <- which(cor_matrix >= 0.8 & cor_matrix != 1, arr.ind = T) #arr.ind can show the relative position of each value satisfied condition.

# Print the pairs and their correlation values
for (i in 1:nrow(high_cor_pairs)) {
  row_idx <- high_cor_pairs[i, 1]
  col_idx <- high_cor_pairs[i, 2]
  correlation_value <- cor_matrix[row_idx, col_idx]
  cat("Pair:", rownames(cor_matrix)[row_idx], "-", colnames(cor_matrix)[col_idx], ", Correlation:", correlation_value, "\n")
}
```
```{r}
cor_matrix = cor_trt
# Find pairs with correlation values greater than 0.5
high_cor_pairs <- which(abs(cor_matrix) > 0.80 & cor_matrix != 1, arr.ind = TRUE)

# Print the pairs and their correlation values
for (i in 1:nrow(high_cor_pairs)) {
  row_idx <- high_cor_pairs[i, 1]
  col_idx <- high_cor_pairs[i, 2]
  correlation_value <- cor_matrix[row_idx, col_idx]
  cat("Pair:", rownames(cor_matrix)[row_idx], "-", colnames(cor_matrix)[col_idx], ", Correlation:", correlation_value, "\n")
}
```