separating_soft_clips_start_and_end.Rmd

---
title: "separating soft clips at the start and at the end"
output: html_document
date: "2023-04-24"
editor_options: 
  chunk_output_type: console
---

This script is about separating 3' and 5' end with and without soft clips. It starts by taking in the output file of parsing_cigar script as the input. 

loading libraries
```{r warning=FALSE, message=FALSE}
suppressPackageStartupMessages({
  library(tidyverse)
  library(GenomicFeatures)
  library(rtracklayer)
  library(dplyr)
  library(Rsamtools)
  library(glmnet)
  library(ggpubr)
  library(visreg)
  library(DESeq2)
  library(apeglm)
})
```

Finding soft clips only at the 3' end
using subset_final (that has come from parsing_cigar script)

counting number of S in the cigar- it will be either 1 or 2. If 1 then soft clip is present either at the start or at the end.
if 2 then soft clip is present at both the ends. 

Making a new column s_count for the count of S in CIGAR. 
```{r warning=FALSE, message=FALSE}
subset_final$s_count=str_count(subset_final$Cigar, "S")
```

Finding the soft clips at the start and at the end
```{r warning=FALSE, message=FALSE}
soft_clip_both <- subset_final %>% 
  filter(s_count=="2")
```

applying matcher function- no change in the function, its the same as was used for parsing cigar 
```{r warning=FALSE, message=FALSE}
matcher <- function(pattern, x) {
  ind = gregexpr(pattern, x)[[1]]
  start = as.numeric(ind)
  end = start + attr(ind, "match.length") -2
  apply(cbind(start,end), 1, function(y) substr(x, start=y[1], stop=y[2]));
}
```

Doone_start function- this function is finding S at the start (5'end)
```{r warning=FALSE, message=FALSE}
doone_start <- function(c, Cigar) {
  pat <- paste("\\d+", c , sep="")
  as.numeric(matcher(pat, Cigar))[1]
}
```

Cigarsums is finding S 
```{r warning=FALSE, message=FALSE}
cigarsums <- function(Cigar, chars=c("S")) {
  sapply (chars, doone_start, Cigar)
}
```

Soft clip at the start of the CIGAR string
```{r warning=FALSE, message=FALSE}
addcig_start <- soft_clip_both %>%
  rowwise %>% mutate(SoftClipStart = cigarsums(Cigar))
```

This function finding S at the end of the CIGAR string 
```{r warning=FALSE, message=FALSE}
doone_end <- function(c, Cigar) {
  pat <- paste("\\d+", c , sep="")
  as.numeric(matcher(pat, Cigar))[2]
}
```

Cigarsums finding S
```{r warning=FALSE, message=FALSE}
cigarsums <- function(Cigar, chars=c("S")) {
  sapply (chars, doone_end, Cigar)
}
```

Adding column that has soft clip end at the end (3' end)
```{r warning=FALSE, message=FALSE}
addcig_end <- soft_clip_both %>%
  rowwise %>% mutate(SoftClipEnd = cigarsums(Cigar))
```

Merging both the start and end soft clip dataframe
```{r warning=FALSE, message=FALSE}
c <- merge(x=addcig_start, y=addcig_end, all=T)
```

De-selecting the s_count and sequence column as they are not required further. 
```{r warning=FALSE, message=FALSE}
merge_soft_clip_both <- c %>% 
  dplyr::select(-s_count, -Sequence)
```


Soft clip that are either at the start or at the end (s_count=1), we don't know whether its at the start or at the end 

```{r warning=FALSE, message=FALSE}
soft_clip_one <- subset_final %>% 
  filter(s_count == "1")
```

To check if soft clip is at the start we are making another column of called logic which gives output as True or False. 
To filter out the soft clips at either end we have to convert the logic column as an integer. (True = 1 and False = 0)

```{r warning=FALSE, message=FALSE}
soft_clip_one$logic <- grepl("S$", soft_clip_one$Cigar)
soft_clip_one$logic <- as.integer(as.logical(soft_clip_one$logic))
```

Filtering out the soft clips that are present only at the end. 

```{r warning=FALSE, message=FALSE}
soft_clip_one_end <- soft_clip_one %>% 
  filter(logic=="1")
```

calculating the length of the soft clip at the end using original doone function
```{r warning=FALSE, message=FALSE}
doone <- function(c, Cigar) {
  pat <- paste("\\d+", c , sep="")
  sum(as.numeric(matcher(pat, Cigar)), na.rm = T)
}
```

Finding S in the CIGAR string
```{r warning=FALSE, message=FALSE}
cigarsums <- function(Cigar, chars=c("S")) {
  sapply (chars, doone, Cigar)
}
```

Making a separate column for Soft clip at the end and deselecting the s_count, logic and sequence. 
```{r warning=FALSE, message=FALSE}
addcig_one_end <- soft_clip_one_end %>%
  rowwise %>% mutate(SoftClipEnd = cigarsums(Cigar)) %>%
  dplyr::select(-s_count, -logic, -Sequence)
```

Filtering out soft clips present at the start

```{r warning=FALSE, message=FALSE}
soft_clip_one_start <- soft_clip_one %>% 
  filter(logic=="0")
```

calculating the length of the soft clip at the start by applying the original doone function
```{r warning=FALSE, message=FALSE}
doone <- function(c, Cigar) {
  pat <- paste("\\d+", c , sep="")
  sum(as.numeric(matcher(pat, Cigar)), na.rm = T)
}
```

Cigarsums is fincing S in the Cigar string
```{r warning=FALSE, message=FALSE}
cigarsums <- function(Cigar, chars=c("S")) {
  sapply (chars, doone, Cigar)
}
```

Making a separate column for the length of soft clip at the start and deselecting the sequence, s_count and logic columns
```{r warning=FALSE, message=FALSE}
addcig_one_start <- soft_clip_one_start %>%
  rowwise %>% mutate(SoftClipStart = cigarsums(Cigar)) %>%
  dplyr::select(-Sequence, -s_count, -logic)
```

After separating the Soft clips of both the ends, there are few reads that have no soft clips

Reads that do not have soft clip
```{r warning=FALSE, message=FALSE}
soft_clip_zero <- subset_final %>% 
  filter(s_count=="0")
zero <- soft_clip_zero %>% 
  dplyr::select(-s_count, -Sequence)
```

Merging the heavily degraded dataset with all the columns of calculations combined. 
```{r warning=FALSE, message=FALSE}
heavily_degraded_1 <- merge(x=addcig_one_end, y=addcig_one_start, all=T)
b <- merge(x=heavily_degraded_1, y=zero, all=T)
heavily_degraded_rep_2 <- merge(merge_soft_clip_both, y=b, all=T)
```

Merging undegraded dataset with all the columns of calculations combined. 
```{r warning=FALSE, message=FALSE}
undegraded_1 <- merge(x=addcig_one_end, y=addcig_one_start, all=T)
b <- merge(x=undegraded_1, y=zero, all=T)
undegraded_rep_2 <- merge(x=merge_soft_clip_both, y=b, all=T)
```

Merging mildly degraded dataset with all the columns of the calculations combined. 
```{r warning= FALSE, message=FALSE}
mildly_degraded_1 <- merge(x=addcig_one_end, y=addcig_one_start, all=T)
b <- merge(x=mildly_degraded_1, y=zero, all=T)
mildly_degraded_rep_2 <- merge(x=merge_soft_clip_both, y=b, all=T)
```


Summation of 3' with no soft clip with soft clip end to get 3' end with soft clip column for all three conditions. 
```{r warning=FALSE, message=FALSE}
heavily_degraded_rep_2$end_with_sc <- heavily_degraded_rep_2$end_without_sc + heavily_degraded_rep_2$SoftClipEnd

undegraded_rep_2$end_with_sc <- undegraded_rep_2$end_without_sc + undegraded_rep_2$SoftClipEnd

mildly_degraded_rep_2$end_with_sc <- mildly_degraded_rep_2$end_without_sc + mildly_degraded_rep_2$SoftClipEnd
```

StartCoord column has 5' end with soft clip. 

Removing soft clip from the start coord to get start without sc for all three conditions. 
```{r warning=FALSE, message=FALSE}
heavily_degraded_rep_2$start_without_sc <- heavily_degraded_rep_2$StartCoord - heavily_degraded_rep_2$SoftClipStart

undegraded_rep_2$start_without_sc <- undegraded_rep_2$StartCoord - undegraded_rep_2$SoftClipStart

mildly_degraded_rep_2$start_without_sc <- mildly_degraded_rep_2$StartCoord - mildly_degraded_rep_2$SoftClipStart
```

The output of the script is all the columns added to the data with and without soft clips at both the ends.