index.Rmd

---
title: "Clinical manifestations of primary CoQ deficiencies"
author: "María Alcázar-Fabra, Francisco Rodríguez-Sánchez, Eva Trevisson & Gloria Brea-Calvo"
date: ""
output: 
  html_document: 
    fig_caption: yes
    fig_height: 4
    includes:
      in_header: header.html
    self_contained: no
    theme: cerulean
---

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


```{r}
library(dplyr)
library(assertr)
library(ggplot2)

#source("render_toc.R")
```


```{r}
#render_toc("index.Rmd", base_level = 2, toc_depth = 1)
```



```{r read.data, include=FALSE}

datos <- gsheet::gsheet2tbl("https://docs.google.com/spreadsheets/d/1zCc9r7Uy_6ujOU5qXc7VOXuN4OSvIJg5Tx9iqWw6swY/edit?usp=sharing", sheetid = 1) %>%
  arrange(group)

npatients <- gsheet::gsheet2tbl("https://docs.google.com/spreadsheets/d/1zCc9r7Uy_6ujOU5qXc7VOXuN4OSvIJg5Tx9iqWw6swY/edit?usp=sharing#gid=1452337852") 

datos %>%
 # verify(ncol(.) == 12) %>%
  verify(names(datos)[1:2] == c("group", "symptom")) %>%
  verify(all.equal(names(datos)[3:ncol(datos)], names(npatients)))

npatients <- as.numeric(npatients)

```


```{r percent}
percent <- datos

for (j in 3:ncol(datos)) {
  percent[, j] <- 100*(percent[, j]/npatients[j - 2])
}

```


```{r datos.long}
datos.long <- percent %>%
  tidyr::pivot_longer(cols = 3:ncol(datos), names_to = "gene") %>%
  mutate(gene = factor(gene, levels = names(datos)[3:ncol(datos)]))
```


```{r heatmap.fun}

plotfun <- function(df = datos.long, grupo = NULL, npat = npatients) {
  
  datos.sub <- df %>%
    dplyr::filter(group == grupo) %>%
    mutate(symptom = factor(symptom, 
                            levels = sort(unique(symptom), decreasing = TRUE)))

## Sort rows by prevalence
df2 <- datos.sub %>%
  dplyr::filter(value > 0) %>%
  group_by(symptom) %>%
  summarise(n.site = sum(value)) %>%
  arrange(n.site)

datos.sub$symptom <- factor(datos.sub$symptom, levels = df2$symptom)


patients <- data.frame(gene = unique(df$gene),
                       n.pat = npat)

heatm <- ggplot(datos.sub) +
  aes(x = gene, y = symptom) +
  geom_tile(aes(fill = value), colour = "grey80",
            height = 1, width = 1) +
  #scale_fill_viridis(name = "% patients", option = "magma") +
  scale_fill_distiller(name = "% patients", type = "seq",
                       palette = "YlGnBu", direction = 1,
                       limits = c(0, 100)) +
  coord_equal(clip = "off") +
  scale_x_discrete(position = "top") +
  theme(axis.text.x.top = element_text(angle = 90, hjust = 0, vjust = 0.5)) +
  xlab("") +
  ylab("") +
  theme(plot.margin = unit(c(0, 0, 0.5, 0), "cm")) +
  theme(panel.background = element_blank()) +
  geom_text(data = patients, aes(y = 0, label = n.pat), size = 3)

heatm
  
}

```


-----------------------------------------------------------------


<br>

Primary coenzyme Q (CoQ) deficiencies are clinically heterogeneous and lack a clear genotype-phenotype correlation. With this platform, we aim to gain insight of the most common manifestations associated with the different COQ genes to improve the diagnosis of patients. 

<br>







## {.tabset .tabset-fade .tabset-pills}


### The tool

Here you can search the frequency of clinical manifestations grouped by system for each gene.

Go to table to search the data by involved system, specific manifestation or COQ gene.

### CSN

```{r out.width='100%', fig.height=9}
plotfun(grupo = "CSN")
```


### Heart

```{r out.width='100%'}
plotfun(grupo = "Heart")
```


### Kidney

```{r out.width='100%'}
plotfun(grupo = "Kidney")
```


### Liver

```{r out.width='100%'}
plotfun(grupo = "Liver")
```


### Lung

```{r out.width='100%'}
plotfun(grupo = "Lung")
```


### Muscle

```{r out.width='100%'}
plotfun(grupo = "Muscle")
```


### PNS/Sensory organs

```{r out.width='100%'}
plotfun(grupo = "PNS/sensory organs")
```


### Other

```{r out.width='100%'}
plotfun(grupo = "Other")
```


### Table

In this table you can search by symptom (and link to symptom description). Numbers represent number of patients.

```{r out.width='100%'}
library(DT)
datatable(datos, filter = "top", rownames = FALSE)
```


## {-}



Last update: `r Sys.Date()`