work_combine-gtfs_processed-pa-ncRNA_part-0.Rmd

---
title: "work_combine-gtfs_processed-pa-ncRNA_part-0.Rmd"
author: "KA"
email: "kalavatt@fredhutch.org"
output:
    html_notebook:
        toc: yes
        toc_float: true
---

## Get situated
### Code
<details>
<summary><i>Code: Get situated</i></summary>

```{r Get situated, results='hide', message=FALSE, warning=FALSE}
#!/usr/bin/env Rscript

library(GenomicRanges)
library(IRanges)
library(plyr)
library(readxl)
library(rtracklayer)
library(tidyverse)

options(scipen = 999)
options(ggrepel.max.overlaps = Inf)

if(base::isTRUE(stringr::str_detect(getwd(), "kalavattam"))) {
    p_local <- "/Users/kalavattam/Dropbox/FHCC"
} else {
    p_local <- "/Users/kalavatt/projects-etc"
}
p_wd <- "2022-2023_RRP6-NAB3/results/2023-0215"

setwd(paste(p_local, p_wd, sep = "/"))
getwd()

rm(p_local, p_wd)
```
</details>
<br />
<br />

## Load and combine `gtf`s
### Load `gtf` files [derived/"processed" from R64-1-1](./work_assess-process_R64-1-1_gff3_part-1.Rmd)
#### Code
<details>
<summary><i>Code: Load `gtf` files derived/"processed" from R64-1-1</i></summary>

```{r Load gtf files derived/processed from R64-1-1, results='hide', message=FALSE, warning=FALSE}
#!/usr/bin/env Rscript

read_processed_gtf <- function(file) {
    tbl <- file %>%
        rtracklayer::import() %>%
        tibble::as_tibble() %>%
        dplyr::select(-c(width, score, phase)) %>%
        dplyr::rename(feature =  type.1) %>%
        dplyr::arrange(seqnames, start)
    tbl[tbl == "NA"] <- NA_character_
    
    return(tbl)
}


p_processed <- "./outfiles_gtf-gff3/comprehensive/S288C_reference_genome_R64-1-1_20110203"
f_gene <- "processed_gene_sense.gtf"
f_PG <- "processed_PG_sense.gtf"
f_snRNA <- "processed_snRNA_sense.gtf"
f_snoRNA <- "processed_snoRNA_sense.gtf"
f_TE <- "processed_TE_sense.gtf"

t_gene <- paste(p_processed, f_gene, sep = "/") %>% read_processed_gtf()
t_PG <- paste(p_processed, f_PG, sep = "/") %>% read_processed_gtf()
t_snRNA <- paste(p_processed, f_snRNA, sep = "/") %>% read_processed_gtf()
t_snoRNA <- paste(p_processed, f_snoRNA, sep = "/") %>% read_processed_gtf()
t_TE <- paste(p_processed, f_TE, sep = "/") %>% read_processed_gtf()

t_processed <- dplyr::bind_rows(t_gene, t_PG, t_snRNA, t_snoRNA, t_TE) %>%
    dplyr::arrange(seqnames, start)

rm(p_processed, f_gene, f_PG, f_snRNA, f_snoRNA, f_TE)
rm(t_gene, t_PG, t_snRNA, t_snoRNA, t_TE)
```
</details>
<br />

### Load [pa-ncRNA `gtf` file](./work_representative-non-coding-transcriptome_part-4.Rmd)
#### Code
<details>
<summary><i>Code: Load pa-ncRNA `gtf` file</i></summary>

```{r}
#!/usr/bin/env Rscript

read_pa_ncRNA_gtf <- function(file) {
    tbl <- file %>%
        rtracklayer::import() %>%
        tibble::as_tibble() %>%
        dplyr::select(-c(
            width, score, phase, details_type_alpha, details_type, details_id,
            details_all, n_types, n_features, n_types_features, length
        )) %>%
        dplyr::mutate(
            feature = "pancRNA",
            orf_classification = NA_character_,
            source_id = NA_character_
        ) %>%
        dplyr::arrange(seqnames, start)
    
    return(tbl)
}

p_pa_ncRNA <- "./outfiles_gtf-gff3/representation"
f_pa_ncRNA <- "Greenlaw-et-al_representative-non-coding-transcriptome.gtf"

t_pa_ncRNA <- paste(p_pa_ncRNA, f_pa_ncRNA, sep = "/") %>% read_pa_ncRNA_gtf()

rm(p_pa_ncRNA, f_pa_ncRNA)
```
</details>
<br />

### Row-bind the "processed" and pa-ncRNA `gtf`s
<details>
<summary><i>Code: Row-bind the "processed" and pa-ncRNA `gtf`s</i></summary>

```{r}
#!/usr/bin/env Rscript

t_bound <- dplyr::bind_rows(t_processed, t_pa_ncRNA) %>%
    dplyr::arrange(seqnames, start)
```
</details>
<br />
<br />

## Write out combined "processed" and pa-ncRNA `gtf`
### Code
<details>
<summary><i>Code: Row-bind the "processed" and pa-ncRNA `gtf`s</i></summary>

```{r}
#!/usr/bin/env Rscript

write_gtf <- function(x, y) {
    # ...
    # :param x: tibble
    # :param y: outfile
    # :return: NA
    readr::write_tsv(
        x,
        y,
        col_names = FALSE,
        quote = "none",
        escape = "none"
    )
}


p_gtf <- "./outfiles_gtf-gff3/representation"
f_gtf <- "Greenlaw-et-al_representative-coding-pa-ncRNA-transcriptome.gtf"
t_gtf <- t_bound %>%
    dplyr::mutate(score = ".", frame = ".") %>%
    dplyr::relocate(c("seqnames", "source", "type"), .before = "start") %>%
    dplyr::relocate(c("score", "strand", "frame"), .after = "end") %>%
    dplyr::mutate(
        attribute = paste(
            paste0("gene_id \"", gene_id, "\""),
            paste0("transcript_id \"", transcript_id, "\""),
            paste0("type \"", feature, "\""),
            paste0("orf_classification \"", orf_classification, "\""),
            paste0("source_id \"", source_id, "\""),
            sep = "; "
        )
    ) %>%
    dplyr::select(
        -c(gene_id, transcript_id, feature, orf_classification, source_id)
    )

write_gtf(t_gtf, paste(p_gtf, f_gtf, sep = "/"))
```
</details>
<br />