Finalizing part A: GenBank sequences and multiple fasta files

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Noah L. Schrick 2022-11-18 15:11:56 -06:00
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# Lab 10 for the University of Tulsa's CS-6643 Bioinformatics Course
# Phylogenetic Analysis
# Professor: Dr. McKinney, Fall 2022
# Noah L. Schrick - 1492657
## Set Working Directory to file directory - RStudio approach
setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
#### Part A: GenBank sequences and a multiple fasta file
if (!require("ape")) install.packages("ape")
library(ape) # needed for read.GenBank
# fetch the mtDNA sequences
mtDNA.MultiSeqs.list<-read.GenBank(c("AF011222","AF254446","X90314","AF089820",
"AF176766","AF451972", "AY079510",
"AF050738","AF176722","AF315498",
"AF176731","AF451964"), as.character=TRUE)
# look at species names
mtDNA.Species<-attr(mtDNA.MultiSeqs.list,"species")
# use species as name instead of genbank id
names(mtDNA.MultiSeqs.list)<-mtDNA.Species
# need to fix some names
names(mtDNA.MultiSeqs.list)[1] <- paste("German_Neanderthal",sep="")
names(mtDNA.MultiSeqs.list)[2] <- paste("Russian_Neanderthal",sep="")
names(mtDNA.MultiSeqs.list)[3] <- paste("Human")
names(mtDNA.MultiSeqs.list)[6] <- paste("Puti_Orangutan",sep="")
names(mtDNA.MultiSeqs.list)[12] <- paste("Jari_Orangutan",sep="")
length(mtDNA.MultiSeqs.list$Human)
# look at one of the sequences using $
mtDNA.MultiSeqs.list$Human
## Convert to Biostrings object for the sequences
if (!require("BiocManager")) install.packages("BiocManager")
library(BiocManager)
if (!require("Biostrings")) BiocManager::install("Biostrings")
library(Biostrings)
# loop through the list to create vector of strings for Biostrings input
Names.vec <- c() # initialize speices names string vector
Seqs.vec <- c() # initialize sequence string vector
for (mtDNA.name in names(mtDNA.MultiSeqs.list))
{
Names.vec <- c(Names.vec,mtDNA.name) # concatenate vector
Seqs.vec <-c(Seqs.vec,paste(mtDNA.MultiSeqs.list[[mtDNA.name]],collapse=""))
}
mtDNA.multSeqs.bstr <- DNAStringSet(Seqs.vec) # convert to Biostring
# name the Biostring sequences and compute stats
names(mtDNA.multSeqs.bstr) <- Names.vec # count nucs and sequence lengths
# num.nts <- alphabetFrequency(mtDNA.multSeqs.bstr)[,1:4]
mtDNA.lengths <- rowSums(num.nts)
proportion.nts <- num.nts/mtDNA.lengths
# Obtain name and length of species with longest sequence
nlengthnames <- cbind(mtDNA.lengths, Names.vec)
idx <- which.max(nlengthnames[,1])
nlengthnames[idx,]

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