---
title: "Salmon_feeding study"
author: "Y.Wang"
date: "December, 2018"


```{r, warning=FALSE, message=FALSE,Cache=TRUE,echo=FALSE}

# Note: salmon_CSIA_complete_AA11a has two labels, this is the difference from salmon_CSIA_complete_AA11
#######################################################################
library(readxl)
library(dplyr)
####################################################################### 
```

```{r}
# MANOVA test among diet and fish for palmaria and control experiment
AA_offset<-read.csv("salmon_muscle_all.csv") #read the file, this file can be extracted from the supplement data 

df1<-AA_offset%>%select(Thr,Lys,His, Ile, Met, Val, Phe, Leu) # extract EAA files
df2<-AA_offset%>%select(Ser,Gly,Ala, Glx,Asx, Pro,Tyr)        # extract NEAA files
ANI.manova<-manova(as.matrix(df1)~as.matrix(AA_offset$Diet))  # Manova test
summary(ANI.manova,test="Pillai")
print(ANI.manova)
library(stats)
summary.aov(ANI.manova) # check which ones are signicantly different between the palamaria & control expriment
p<-c(0.4373, 0.006234, 0.0009938, 0.9517, 5.031e-06, 0.2018, 0.6262, 0.8196)
p.adjust(p,"fdr")

# Manova test among  NEAAs
NEAA.manova<-manova(as.matrix(df2)~as.matrix(AA_offset$Diet)) # Manova test
summary(NEAA.manova,test="Pillai")
print(NEAA.manova)
library(stats)
summary.aov(NEAA.manova)
p1<-c(0.000555, 1.959e-05, 0.0008238, 0.0238, 0.1314,  0.2497, 0.001578)
p.adjust(p1,"fdr") # calculated p-adjusted values using methods "fdr" (see main text-Methods section)

##make one-sample t-test to see if mean value of all EAAs is significantly difference from zero for both treatments

fish_AA<-read.csv("fish_diet_diff_R.csv") #read the file, this file can be extracted from the attached supplementary data

t.test(fish_AA$P15_Add_EAA, mu=0, conf.level = 0.99) # t-test for Palamaria group
t.test(fish_AA$controlP_EAA, mu=0, conf.level = 0.99) # t-test for control group



```