fticr_statistics_organic.Rmd

---
title: "FTICR-MS:Organic"
output: html_notebook
author: "William Rodriguez"
---

# Load R packages

```{r}
rm(list=ls())
library(ftmsRanalysis)
```


# Sample Data
```{r}
fdata <- read.delim('input/FTICR_metadata.txt')
fdata <- fdata[fdata$Horizon %in% "Organic",]
str(fdata)
```

# FTICR MS Data
```{r}
mydata = read.delim('input/FTICR_data.txt')
```

# Expression Data

```{r}
edata <- subset(mydata,select=c("Mass",fdata$Sample_ID))
str(edata)
```

# Molecular Indentification Data

```{r}
emeta <- subset(mydata,select=c("Mass","C","H","O","N","C13",
                                "S","P","Error_ppm","NeutralMass"))
str(emeta)
```


# PeakData Object

```{r}
peakObj <- as.peakData(e_data = edata,f_data = fdata,e_meta = emeta,
                       edata_cname = "Mass",fdata_cname = "Sample_ID",
                       mass_cname = "Mass",c_cname="C", h_cname="H",
                       o_cname="O", n_cname="N", s_cname="S",
                       p_cname="P", isotopic_cname = "C13",
                       isotopic_notation = "1")
peakObj
```

"Currently, any peaks that are isotopic are removed from the dataset, as available methods (e.g. Van Krevelen plot) are not applicable to these peaks."


## Elements

```{r}
names(peakObj)
```

## Calculated Molecular Formula

```{r}
tail(peakObj$e_meta)
```

## Summary

```{r}
summary(peakObj)
```

## Plotting (Default; presence/absence)

```{r}
plot(peakObj)
```

# Preprocessing

Transforming abundance values to log2

```{r}
peakObj <- edata_transform(peakObj, data_scale="log2")
```

plotting

```{r}
plot(peakObj)
```

# Calculating meta-data

```{r}
peakObj <- compound_calcs(peakObj)
peakObj
```

## Compounds by Elements

```{r}
peakObj <- assign_elemental_composition(peakObj)
table(peakObj$e_meta[,getElCompColName(peakObj)])
```

## Compounds by Class

```{r}
peakObj <- assign_class(peakObj, boundary_set = "bs1")
table(peakObj$e_meta[, getBS1ColName(peakObj)])
```
*Something is going on boundary_set argument when bs2 or bs3 selected.

## Filtering

Before filtering

```{r}
summary(peakObj)
```

After filtering


```{r}
filter_obj <- mass_filter(peakObj)
plot(filter_obj, min_mass=200, max_mass=900)
```


```{r}
peakObj <- applyFilt(filter_obj, peakObj, min_mass = 200,
                  max_mass = 900)
summary(peakObj)
```

```{r}
peakObj
```

Other filters

```{r}
# minimum number to be observed across all samples in order to retain the biomolecule
peakObj <- applyFilt(molecule_filter(peakObj), peakObj, min_num=2)
# remove biomolec without molecular formula; remove=NoFormula)
peakObj <- applyFilt(formula_filter(peakObj), peakObj)
summary(peakObj)
```

## Comparison of Experimental Groups

```{r}
peakObj <- group_designation(peakObj, main_effects=c("Treatment"))
getGroupDF(peakObj)
```
## Group-level Summary per Peak

```{r}
group_summary <- summarizeGroups(peakObj, summary_functions =
                                   c("n_present", "prop_present"))
head(group_summary$e_data)
```

## NOSC Distrubution

```{r,fig.width=10, fig.height=6}
densityPlot(peakObj, samples=FALSE, groups=c("Control","Heated"), variable="NOSC",title="Comparison of NOSC Between Experimental Plots: Organic Horizon")
```
## Compounds Distribution

```{r}
byGroup <- divideByGroupComparisons(peakObj,
                                comparisons = "all")[[1]]$value
```

### Available Summary Options

```{r}
getGroupComparisonSummaryFunctionNames()
```

## Determine Unique and Common Masses/Peaks: g-test

> "Use a g-test to compare two groups and determine which peaks are uniquely expressed in each group based on a p-value threshold."

```{r}
organic_unique <- summarizeGroupComparisons(byGroup,
            summary_functions="uniqueness_gtest",
            summary_function_params=list(
                  uniqueness_gtest=list(pres_fn="nsamps",
                          pres_thresh=1, pvalue_thresh=0.1)))

head(organic_unique$e_data)
```

```{r}
organic_unique
```



### Plotting - Van Krevelen

```{r,fig.width=10, fig.height=6}
vanKrevelenPlot(organic_unique, colorCName = "uniqueness_gtest")
```


Compounds breakdown

```{r}
table(organic_unique$e_data$uniqueness_nsamps)
```



## Determine Unique and Common Masses/Peaks: g-test

> "Use number of samples for which a mass/peak is present to compare two groups and determine which peaks are uniquely expressed in each group."


```{r}
organic_unique <- summarizeGroupComparisons(byGroup,
            summary_functions="uniqueness_nsamps",
            summary_function_params=list(
                  uniqueness_nsamps=list(pres_thresh=1, absn_thresh=0)))

head(organic_unique$e_data)
```

```{r}
organic_unique
```


### Plotting - Van Krevelen

```{r,fig.width=10, fig.height=6}
vanKrevelenPlot(organic_unique, colorCName = "uniqueness_nsamps")
```


Compounds breakdown

```{r}
table(organic_unique$e_data$uniqueness_nsamps)
```