knitr::opts_chunk$set(echo = TRUE)

**Analysis report**

Xiaotao Shen, Zhengjiang Zhu

`r format(Sys.Date())`


(1) INTRODUCTION

MetDNA (version 0.99.07) is used for metabolite annotation and dysregulated network analysis of untargeted metabolomics.


(2) PARAMETERS

Table 1_1: The parameter setting of this analysis (Positive mode)

library(knitr)
load("parameter.pos")
colnames(parameter.pos) <- c("Patameter", "Value", "Meaning")
kable(parameter.pos, format = "markdown")

Table 1_2: The parameter setting of this analysis (Negative mode)

library(knitr)
load("parameter.neg")
colnames(parameter.neg) <- c("Patameter", "Value", "Meaning")
kable(parameter.neg, format = "markdown")

(3) SAMPLE INFORMATION

**Figure 1: Peak distribution**


(4) METABOLITE ANNOTATION

The metabolite annotation is based on metabolic reaction network.

**Figure 2: Recursive annotation and redundancy removal (Positive mode)**

**Figure 3: Recursive annotation and redundancy removal (Negative mode)**

Confidence level (from grade 1 to grad 4) is assigned to each metabolie.

**Figure 4: The confidence levles of metabolites (Positive mode)**

**Figure 5: The confidence levles of metabolites (Negative mode)**


(5) DYSREGULATED NETWORK ANALYSIS

**Figure 6: Summary of dysregulated network information**

Table 2: The information of dysregualted networks. The detailed information can be got from dysregulated.network.MSEA.csv in /POS and NEG/Dysregulated_network_analysis_result/pathway_information.

library(knitr)
load("pathway.result")
# temp.idx <- which(dn.result$q.value < 0.05)
# if(length(temp.idx) == 0 & nrow(module.result) > 5){
#   temp.idx <- 1:5
# }else{
#   temp.idx <- temp.idx
# }

name <- pathway.result$pathway.name
pathway.result$Overlap <- pathway.result$Overlap*100/pathway.result$Pathway.length
rownames(pathway.result) <- NULL
pathway.result <-pathway.result[,c(1,2,6,7,8,9,11)]
colnames(pathway.result) <- c("Pathway name", "Pathway ID", "Pathway size",
                              "Overlap (%)", "P value (adjusted by P value)",
                              "P value (adjusted by overlap)", "Detected metabolite")
kable(pathway.result)

Dysregulated peaks (according to pvalues) are used to identify dysregulated modules. The dysregulated modules with p values less than 0.05 are combined as dysregulated network. Metabolite set analysis (MSEA) is used to annotate functions of each module. The MSEA result for each module can be found in /POS and NEG/Dysregulated_network_analysis_result/module_information/Module_MSE analysis.

**Figure 7: Summary of module information**

Table 3: The information of dysregualted modules. The detailed information can be got from module.result.csv in /POS and NEG/Dysregulated_network_analysis_result/module_information

library(knitr)
load("module.result")
# temp.idx <- which(module.result$p.value < 0.05)
# if(length(temp.idx) == 0 & nrow(module.result) > 5){
#   temp.idx <- 1:5
# }else{
#   temp.idx <- temp.idx
# }

overlap <- as.numeric(module.result$`Detected metabolite number`)*100/as.numeric(module.result$`Module size`)
module.result$`Detected metabolite number` <- overlap
colnames(module.result)[5] <- "Overlap (%)"
kable(module.result[,c(1,2,3,4,5,13)])


jaspershen/analysisReport documentation built on May 23, 2019, 9:01 p.m.