5 FAsta file input and showing result using nested loop

Question

[mubarakkham2016]

a. Read five different protein sequences from any public repository and store them in five different files in your hard drive.

b. Using nested loop, read each file with following combination and apply global pairwise alignment on sequences. For scoring, use BLOSUM100, BLOSUM62 and BLOSUM45 scoring matrix:

like: file1- file2, file1-3, file1- file4, file1- file5, file2- file3, file2- file4, file2- file5, file3-file4, file3- file5, file4- file5

c. Show histogram of all above scores for each BLOSUM matrix.

[Medhat]

Nice questions. Do you need the people here to answer them instead of you? You could get help If you tried something first. Try to answer them and show what you did, then sure people will help you :).

How To Ask Good Questions On Technical And Scientific Forums

[WouterDeCoster]

This looks a lot like an assignment, and you will learn nothing if someone else solves it for you.

[mubarakkham2016]

It's our past paper. Just trying to solve it for exam prepration

[steve]

This sounds like someone's homework assignment.

[mubarakkham2016]

library("gdata")
library("csv")
library(seqinr)
library("Biostrings")
library(msa)
library(ape)

choosebank("genbank")
a1 <- read.GenBank("JF806202", as.character = TRUE)
a1
write.fasta(sequences = a1, names = names(a1), nbchar = 80, file.out = "a.fasta")
a2 <- read.GenBank("JF806212", as.character = TRUE)
a2
write.fasta(sequences = a2, names = names(a2), nbchar = 80, file.out = "b.fasta")
a3 <- read.GenBank("JF806213", as.character = TRUE)
a3
write.fasta(sequences = a3, names = names(a3), nbchar = 80, file.out = "c.fasta")
a4 <- read.GenBank("JF806214", as.character = TRUE)
a4
write.fasta(sequences = a4, names = names(a4), nbchar = 80, file.out = "d.fasta")
a5 <- read.GenBank("JF806215", as.character = TRUE)
a5
write.fasta(sequences = a5, names = names(a5), nbchar = 80, file.out = "e.fasta")
a1=read.fasta(file = "a.fasta")
a2=read.fasta(file = "b.fasta")
a3=read.fasta(file = "c.fasta")
a4=read.fasta(file = "d.fasta")
a5=read.fasta(file = "e.fasta")
a1 <- as.character(a1[[1]])
a2 <- as.character(a2[[1]])
a3 <- as.character(a3[[1]])
a4 <- as.character(a4[[1]])
a5 <- as.character(a5[[1]])
q<-c2s(a1)
q1<-c2s(a2)
q2<-c2s(a3)
q3<-c2s(a5)
q4<-c2s(a5)
q<-toupper(q)
q1<-toupper(q1)
q2<-toupper(q2)
q3<-toupper(q3)
q4<-toupper(q4)

r<- matrix(c(q,q, 1, 1), nrow=1)  
r1<- matrix(c(q1,q1, 1, 1), nrow=1)
r2<- matrix(c(q2,q2, 1, 1), nrow=1)
r3<- matrix(c(q3,q3, 1, 1), nrow=1)
r4<- matrix(c(q4,q4, 1, 1), nrow=1)
data("BLOSUM62")
for (a in r) {

   a<-matrix(score(pairwiseAlignment(r, r1,substitutionMatrix = "BLOSUM62")))
}