R: how to write a loop to get a matrix? -

thanks wonderful solution suggested diliop previous question.

how pair-wise "sequence similarity score" ~1000 proteins?

to build upon answer, tried write loop pair-wise "sequence similarity score" 1000 proteins following code.

for (i in 1:1000){ score <- score(pairwisealignment(seqs[[i]]$seq, seqs[[i+1]]$seq, substitutionmatrix=blosum100, gapopening=0, gapextension=-5))} 

however, difficult me convert each score data.frame, list out score automatically?

seq1 seq2 score seq1 seq3 score seq1 seq4 score .... seq1000 seq1000 score 

could expert give me more hints how 1000 x 1000 proteins?

this appears task can expand.grid , apply:

seqs <-c("seq1","seq2","seq3"); dat <- expand.grid(seqs,seqs, stringsasfactors=false) dat apply(dat, 1, function(seq) paste(seq[1], seq[2], sep="--") ) #[1] "seq1--seq1" "seq2--seq1" "seq3--seq1" "seq1--seq2" "seq2--seq2" "seq3--seq2" "seq1--seq3" #[8] "seq2--seq3" "seq3--seq3" 

admittedly there duplication of effort if function returns same value f(seq1,seq2) f(seq2,seq1), if wanted gain efficiency limit first argument apply:

 datr <- dat[dat[,1] > dat[,2] , ] 

so if made such restricted-row-dataframe, datr, perhaps:

datr$score <-  apply(datr, 1 , function(seq) {                      score(pairwisealignment( seq[1], seq[2],                       substitutionmatrix=blosum100, gapopening=0, gapextension=-5)) } 

(not knowing arguments in last line. should learn put in real data in examples , list required packages library or require calls.)