4-fticr_markdown.Rmd

---
title: "fticr_markdown"
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo=FALSE,message=FALSE,warning=FALSE,
                      collapse = TRUE,
                      comment = "#>", 
                      fig.path = "images/fticr_markdown/"
                      )
```

```{r}
source("0-packages.R")

fticr_data = read.csv(FTICR_LONG)
fticr_meta = read.csv(FTICR_META)
meta_hcoc = read.csv(FTICR_META_HCOC)

relabund_cores = read.csv(FTICR_RELABUND_CORES)
relabund_trt = read.csv(FTICR_RELABUND_TRT)
relabund_summary = read.csv(FTICR_RELABUND_SUMMARY)

```

## VAN KREVELEN DOMAINS

```{r vk_domains, fig.height=5, fig.width=5}
gg_vankrev(fticr_meta, aes(x = OC, y = HC, color = Class))+
  scale_color_viridis_d(option = "inferno")+
  theme_kp()
```


## VAN KREVELEN PLOTS {.tabset}
### simple VK plots
```{r vk, fig.height=6, fig.width=16}
fticr_hcoc = 
  fticr_data %>% 
  left_join(meta_hcoc, by = "formula")

gg_vankrev(fticr_hcoc, aes(x = OC, y = HC, color = sat_level))+
  facet_grid(.~sat_level)+
  theme_kp()
```

### VK plots with marginal plots
```{r vk_marginal, fig.height = 6, fig.width=6}

gg_fm = gg_vankrev(fticr_hcoc, aes(x = OC, y = HC, color = sat_level))+
  stat_ellipse()+
  annotate("text", label = "aliphatic", x = 1.2, y = 1.9, hjust="right")+
  annotate("text", label = "polyphenolic", x = 1.2, y = 1.2, hjust="right")+
  annotate("text", label = "condensed \n aromatic", x = 1.2, y = 0.2, hjust="right")+
  theme_kp()

ggMarginal(gg_fm,groupColour = TRUE,groupFill = TRUE)

```


## RELATIVE ABUNDANCE FIGURES

```{r relabund_bar}
relabund_trt %>%  
dplyr::mutate(Class = factor(Class, levels = 
                          c("AminoSugar", "Carb","Lipid","Protein","UnsatHC",
                            "ConHC","Lignin","Tannin","Other"))) %>% 
  ggplot(aes(x = sat_level, y = rel_abund, fill = Class))+
  geom_bar(stat = "identity")+
  scale_fill_viridis_d(option = "inferno")+
  labs(x = "percent saturation",
       y = "relative abundance (%)")+
  theme_kp()
```


## RELATIVE ABUNDANCE TABLES
Different letters denote significant differences among saturation levels at alpha = 0.05.

```{r}
relabund_summary %>% 
  dplyr::select(sat_level, Class, relative_abundance) %>% 
  dplyr::mutate(Class = factor(Class, levels = 
                          c("AminoSugar", "Carb","Lipid","Protein","UnsatHC",
                            "ConHC","Lignin","Tannin","Other"))) %>% 
  spread(sat_level, relative_abundance) %>% 
  knitr::kable(align = "c")
```