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G20.rmd
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---
title: "IGHV3-30/IGHV3-30-3/IGHV3-30-5/IGHV3-33"
output:
distill::distill_article:
toc: true
toc_float: false
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = F, error=F, message = F)
pacman::p_load('dplyr', 'tidyr', 'htmltools', 'bbplot',
'ggplot2', 'rdrop2', 'shiny', 'BiocManager',
'dendextend', 'data.table', 'Biostrings', 'alakazam', "unikn",
'plotly', 'ggdendro', "RColorBrewer", install = F)
```
```{r}
source("functions.R")
```
```{r, echo=FALSE}
load("data.rda")
chain = "IGH"
func <- data.frame(allele = names(vgerms[[chain]]), functionality = !grepl("(ORF|P)",sapply(seqinr::getAnnot(vgerms_full[[chain]]), function(x) unlist(strsplit(x,"[|]"))[4])), sign = sapply(seqinr::getAnnot(vgerms_full[[chain]]), function(x) unlist(strsplit(x,"[|]"))[4]), stringsAsFactors = F)
mat <- mat_list$IGH$functional$nonsingle$all$`318`
load("data_frac_new2.rda")
data <- setDT(data_frac$IGH$functional$nonsingle$all$`318`$complete$`95`)
data[,v_call:=paste0(v_gene,"*",v_allele)]
load("alleles_dbs.rda")
allele_db <- alleles_dbs$IGH$functional$nonsingle$all$`318`$complete$`95`
allele_db <- allele_db %>% dplyr::rowwise() %>% dplyr::mutate(gene = alakazam::getGene(or_allele, strip_d = F, omit_nl = F), group = strsplit(gsub(gene, "", new_allele),"[*]")[[1]][1], gene_group = alakazam::getGene(new_allele, strip_d = F, omit_nl = F))
load("functional_groups.rda")
func_groups <- functional_groups$IGH$functional$nonsingle$all$`318`$complete$`95`
cols <- c("#FAAB18", "#1380A1","#990000", "#588300")
pal <- cols %>%
newpal(names = c("orangy", "bluish", "redish", "greeny"))
edit_links <- readLines("edit_links.txt")
share_links <- readLines("share_links.txt")
```
```{r,echo=FALSE}
g_group = "IGHV3-30G20"
group = names(func_groups)[func_groups==g_group]
gr <- allele_db %>% filter(gene_group == g_group) %>% pull(group) %>% unique()
g <- allele_db %>% filter(gene_group == g_group) %>% pull(gene) %>% unique()
```
## Allele appearnce
The group of `r group` includes `r sum(grepl(paste0(g,"[*]", collapse = "|"), func$allele))` alleles, `r sum(func$functionality[grepl(paste0(g,"[*]", collapse = "|"), func$allele)])` out of the alleles are functional.
For each allele we counted the number of appearances across the population, any appearance was considered valid.
```{r}
allele_appearance(data, g_group)
```
## Group alignment
Based on the viewd alleles, we calculated the distance between the germline sequences.
```{r, fig.width=18,fig.height=30}
v_calls <- unique(data[grepl(g_group,v_gene),v_call])
seq_align(v_calls, allele_db, vgerms, chain, mat, g_group)
```
## Sequence depth
To examine the potential cutoff we observed the sequence depth for each allele
```{r}
sequence_depth(data, g_group)
```
## 0.5% cutoff
We set an initial cutoff of $0.5\%$ to determine the potential genotype priors. For this cutoff we examined the zygousity state, such as homozygousity, heterozygousity and so on.
```{r}
tmp_allele_db <-
allele_db %>% dplyr::filter(grepl(as.character(g_group), new_allele)) %>%
dplyr::group_by(new_allele) %>% dplyr::summarise(or_allele = paste0(or_allele, collapse = "/"))
or_allele <-
setNames(gsub(chain, "", as.character(tmp_allele_db$or_allele)), as.character(gsub(
paste0(g_group, "[*]"),
"",
tmp_allele_db$new_allele
)))
allele_thresh = 0.5
tmp <- data_cutoff(data, func_g_groups, g_group, allele_thresh, or_allele)
```
With the selected cutoff we saw that there are `r length(unique(tmp %>% arrange(zygousity_state) %>% pull(zygousity_state)))` zygousity states.
```{r, warning = F, error=F, message = F}
p_list <- c()
for(i in as.character(unique(tmp %>% dplyr::arrange(zygousity_state) %>% dplyr::pull(zygousity_state)))){
p_list[[i]] <- plot_zygousity(tmp, i, allele_thresh, g_group) %>% config(edits = list(shapePosition = TRUE),
scrollZoom = FALSE) %>% layout(title = paste0("state ", i))
#
}
tagList(p_list)
```
## Observations
This section is editable by clicking on the edit button below. To refresh the section click on the refresh button
You can access the file also from [here](`r edit_links[grep(g_group,edit_links)]`)
```{r, message=F, echo=F, warning=F}
knitr::include_url(paste0("https://peresay.shinyapps.io/G2_group/?group=",g_group))
# # Authenticate and save token for later use2
# token <- drop_auth(rdstoken = "dropbox_token.rds")
#
# # Retrieveing your file is as simple as
# drop_download("public/conclusions/IGHV1-2.docx", local_path = "docs/IGHV1-2.docx",
# overwrite = TRUE, verbose = FALSE, progress = FALSE)
# drop_df <- textreadr::read_docx("docs/IGHV1-2.docx")
# invisible(rmarkdown::pandoc_convert(input = "IGHV1-2.docx", to = "markdown", output = "IGHV1-2_docx.md", options = c("--wrap=none","--reference-links","--metadata-file=metadata.yaml","--standalone"), wd = "docs", verbose = FALSE))
#
# ui <- fluidPage(
#
# # Application title
# mainPanel(
# shiny::actionButton(inputId='ab1', label="Edit text",
# icon = icon("edit"),
# onclick ="window.open('https://www.dropbox.com/scl/fi/crphl3u49fmkw8wnb5v71/IGHV1-2.docx?dl=0&rlkey=l54oqhrlxx8wyp6bywr224sx0')"),
#
# shiny::actionButton(inputId='ab2', label="Reload text",
# icon = icon("sync-alt")),
#
# #htmlOutput("df_output"),
# uiOutput('markdown')
# )
# )
#
# server <- function(input, output) {
#
# observeEvent(input$ab2, {
# drop_download("public/conclusions/IGHV1-2.docx", local_path = "docs/IGHV1-2.docx",
# overwrite = TRUE, verbose = F)
# #drop_df <- textreadr::read_docx("docs/IGHV1-2.docx")
#
# rmarkdown::pandoc_convert(input = "IGHV1-2.docx", to = "markdown", output = "IGHV1-2_docx.md", options = c("--wrap=none","--reference-links","--metadata-file=metadata.yaml","--standalone"), wd = "docs", verbose = F)
# output$markdown <- renderUI({
# #withMathJax(includeMarkdown(knitr::knit('IGHV1-2_docx.md', quiet = TRUE)))
# HTML(markdown::markdownToHTML(knitr::knit('docs/IGHV1-2_docx.md', quiet = TRUE)))
# })
#
# })
#
# # output$df_output <- renderUI({
# # if(input$ab2) return()
# # HTML(paste(drop_df, collapse = "<br/><br/>"))
# # })
#
# output$markdown <- renderUI({
# #withMathJax(includeMarkdown(knitr::knit('docs/IGHV1-2_docx.md', quiet = TRUE)))
# HTML(markdown::markdownToHTML(knitr::knit('docs/IGHV1-2_docx.md', quiet = TRUE)))
# })
# }
#
# shinyApp(ui = ui, server = server)
```
## Conclusions