Part 1: FASTA Imports

The FASTA file was stored as a list to show the different types of information in separate element.

The list has 1 sequence.

The data is stored in the binary/raw format which keeps the data in bytes versus regular text.

FASTA <- read.FASTA("~/Desktop/BIN521L/Unit1-KG/MT103168.fasta")
head(FASTA)
## 1 DNA sequence in binary format stored in a list.
## 
## Sequence length: 1560 
## 
## Label:
## MT103168.1 Bifidobacterium longum strain BB536 cell division...
## 
## Base composition:
##     a     c     g     t 
## 0.156 0.319 0.289 0.236 
## (Total: 1.56 kb)
str(FASTA)
## List of 1
##  $ MT103168.1 Bifidobacterium longum strain BB536 cell division protein FtsW (rodA) gene, complete cds: raw [1:1560] 88 18 48 88 ...
##  - attr(*, "class")= chr "DNAbin"

Part 2: FastQ Imports

The FASTQ file was stored as a list similar to above, because FASTQ files contain different pieces of information based on the sequencing.

This file has 3 elements.

The data is stored in the binary/raw format. Using the list format allows for the sequencing information to be kept together and the reads as individual.

FASTQ <- read.fastq('~/Desktop/BIN521L/Unit1-KG/ERR1072710.fastq')
head(FASTQ)
## 3 DNA sequences in binary format stored in a list.
## 
## Mean sequence length: 183.667 
##    Shortest sequence: 146 
##     Longest sequence: 259 
## 
## Labels:
## ERR1072710.1 10317.000001315_0 length=151
## ERR1072710.2 10317.000001315_1 length=116
## ERR1072710.4 10317.000001315_3 length=151
## 
## Base composition:
##     a     c     g     t 
## 0.318 0.208 0.254 0.219 
## (Total: 551 bases)
str(FASTQ)
## List of 3
##  $ ERR1072710.1 10317.000001315_0 length=151: raw [1:146] 18 18 88 88 ...
##  $ ERR1072710.2 10317.000001315_1 length=116: raw [1:259] 18 28 18 28 ...
##  $ ERR1072710.4 10317.000001315_3 length=151: raw [1:146] 28 28 88 28 ...
##  - attr(*, "class")= chr "DNAbin"
##  - attr(*, "QUAL")=List of 7
##   ..$ ERR1072710.1 10317.000001315_0 length=151: num [1:11] 32 38 51 34 32 34 32 34 32 38 ...
##   ..$ ERR1072710.2 10317.000001315_1 length=116: num [1:11] 30 30 30 30 30 30 30 30 30 30 ...
##   ..$ ERR1072710.4 10317.000001315_3 length=151: num [1:42] 10 36 49 49 16 15 22 17 22 16 ...
##   ..$ NA                                       : num [1:70] 51 32 34 38 38 32 38 38 38 51 ...
##   ..$ NA                                       : num [1:67] 30 30 30 30 30 30 30 30 30 30 ...
##   ..$ NA                                       : num [1:11] 32 51 51 32 38 32 38 34 34 51 ...
##   ..$ NA                                       : num [1:11] 30 30 30 30 30 30 30 30 30 30 ...

Part 3: vcf Imports

The VCF file was stored as a data frame so the information is organized into rows and columns. Each row represents a variant, and each column contains different information about each variant.

A data frame contains multiple data types in different columns.

VCF <- read.table('~/Desktop/BIN521L/Unit1-KG/TwoVariants.vcf')
mylines <- read.csv('~/Desktop/BIN521L/Unit1-KG/TwoVariants.vcf',sep = "\n")
names(VCF)
##  [1] "V1"  "V2"  "V3"  "V4"  "V5"  "V6"  "V7"  "V8"  "V9"  "V10"
head(VCF)
##                  V1  V2 V3 V4 V5 V6 V7                   V8             V9
## 1 NZ_BCYL01000006.1  29  .  A  G  .  .  AC=84;AF=1.0;SB=0.0 GT:AC:AF:SB:NC
## 2 NZ_BCYL01000006.1 145  .  A  G  .  . AC=114;AF=1.0;SB=0.0 GT:AC:AF:SB:NC
##                          V10
## 1  1:84:1.0:0.0:+G=37,-G=47,
## 2 1:114:1.0:0.0:+G=42,-G=72,
str(VCF)
## 'data.frame':    2 obs. of  10 variables:
##  $ V1 : chr  "NZ_BCYL01000006.1" "NZ_BCYL01000006.1"
##  $ V2 : int  29 145
##  $ V3 : chr  "." "."
##  $ V4 : chr  "A" "A"
##  $ V5 : chr  "G" "G"
##  $ V6 : chr  "." "."
##  $ V7 : chr  "." "."
##  $ V8 : chr  "AC=84;AF=1.0;SB=0.0" "AC=114;AF=1.0;SB=0.0"
##  $ V9 : chr  "GT:AC:AF:SB:NC" "GT:AC:AF:SB:NC"
##  $ V10: chr  "1:84:1.0:0.0:+G=37,-G=47," "1:114:1.0:0.0:+G=42,-G=72,"