### R code from vignette source 'ArtOfAlignmentInR.Rnw' ################################################### ### code chunk number 1: ArtOfAlignmentInR.Rnw:52-54 ################################################### options(continue=" ") options(width=80) ################################################### ### code chunk number 2: expr0 ################################################### library(DECIPHER) n_points <- 10 N0 <- ceiling(2^seq(5, 13, length.out=n_points)) N1 <- ceiling(2^seq(5, 12, length.out=n_points)) N2 <- ceiling(2^seq(5, 13, length.out=n_points)) N3 <- ceiling(2^seq(5, 16, length.out=n_points)) timings0 <- setNames(rep(0, length(N0)), N0) timings1 <- setNames(rep(0, length(N1)), N1) timings2 <- setNames(rep(0, length(N2)), N2) timings3 <- setNames(rep(0, length(N3)), N3) for (i in seq_len(length(N0))) { for (j in 0:3) { N <- eval(parse(text=paste("N", j, sep=""))) # simulate sequences with 15% distance string1 <- DNAStringSet(paste(sample(DNA_ALPHABET[1:4], N[i], replace = TRUE), collapse = "")) string2 <- replaceAt(string1, at=IRanges(sample(N[i], ceiling(N[i]/5)), width=1), sample(c(DNA_ALPHABET[1:4], ""), ceiling(N[i]/5), replace = TRUE)) # align the sequences using two methods if (j==0) { timings0[i] <- system.time(pairwiseAlignment(string1, string2))[["user.self"]] } else if (j==1) { timings1[i] <- system.time(AlignProfiles(string1, string2, restrict=-Inf, anchor=NA, processors=1))[["user.self"]] } else if (j==2) { timings2[i] <- system.time(AlignProfiles(string1, string2, anchor=NA, processors=1))[["user.self"]] } else { # j == 3 timings3[i] <- system.time(AlignProfiles(string1, string2, processors=1))[["user.self"]] } } } c0 <- lm(timings0 ~ N0 + I(N0^2)) c1 <- lm(timings1 ~ N1 + I(N1^2)) c2 <- lm(timings2 ~ N2) c3 <- lm(timings3 ~ N3) N <- seq(1, 46340, length.out=1000) # prediction range plot(N0, timings0, xlab = "Sequence length (nucleotides)", ylab = "Elapsed Time (sec.)", main = "", ylim=c(range(timings0, timings1, timings2, timings3)), xlim=c(0, max(N3))) points(N, predict(c0, data.frame(N0 = N)), type="l", lty=3) points(N1, timings1, col="blue", pch=0) points(N, predict(c1, data.frame(N1 = N)), type="l", lty=3, col="blue") points(N2, timings2, col="red", pch=5) points(N, predict(c2, data.frame(N2 = N)), type="l", lty=3, col="red") N <- seq(1, max(N3), length.out=1000) # prediction range points(N3, timings3, col="green", pch=2) points(N, predict(c3, data.frame(N3 = N)), type="l", lty=3, col="green") legend("bottomright", c("Biostrings::pairwiseAlignment", "AlignProfiles (unrestricted, unanchored)", "AlignProfiles (restricted, unanchored)", "AlignProfiles (restricted, anchored)"), pch=c(1, 0, 5, 2), lty=3, col=c("black", "blue", "red", "green"), bg="white") ################################################### ### code chunk number 3: expr1 ################################################### library(DECIPHER) # specify the path to your sequence file: fas <- "<>" # OR find the example sequence file used in this tutorial: fas <- system.file("extdata", "50S_ribosomal_protein_L2.fas", package="DECIPHER") dna <- readDNAStringSet(fas) dna # the unaligned sequences ################################################### ### code chunk number 4: expr2 (eval = FALSE) ################################################### ## AA <- AlignTranslation(dna, asAAStringSet=TRUE) # align the translation ## BrowseSeqs(AA, highlight=1) # view the alignment ## ## DNA <- AlignTranslation(dna) # align the translation then reverse translate ## DNA <- AlignSeqs(dna) # align the sequences directly without translation ## ## # write the aligned sequences to a FASTA file ## writeXStringSet(DNA, file="<>") ################################################### ### code chunk number 5: expr5 (eval = FALSE) ################################################### ## # form a chained guide tree ## gT <- data.frame(seq_along(dna)) ## ## # use the guide tree as input for alignment ## DNA <- AlignTranslation(dna, guideTree=gT) # align by translation ################################################### ### code chunk number 6: expr6 (eval = FALSE) ################################################### ## half <- floor(length(dna)/2) ## dna1 <- dna[1:half] # first half ## dna2 <- dna[(half + 1):length(dna)] # second half ## ## AA1 <- AlignTranslation(dna1, asAAStringSet=TRUE) ## AA2 <- AlignTranslation(dna2, asAAStringSet=TRUE) ## AA <- AlignProfiles(AA1, AA2) ################################################### ### code chunk number 7: expr7 (eval = FALSE) ################################################### ## # Align DNA sequences stored in separate tables: ## dbConn <- dbConnect(SQLite(), ":memory:") ## Seqs2DB(AA1, "DNAStringSet", dbConn, "AA1", tblName="AA1") ## Seqs2DB(AA2, "DNAStringSet", dbConn, "AA2", tblName="AA2") ## AlignDB(dbConn, tblName=c("AA1", "AA2"), add2tbl="AA", ## type="AAStringSet") ## AA <- SearchDB(dbConn, tblName="AA", type="AAStringSet") ## BrowseDB(dbConn, tblName="AA") ## dbDisconnect(dbConn) ################################################### ### code chunk number 8: expr8 (eval = FALSE) ################################################### ## BrowseSeqs(DNA, highlight=0) ################################################### ### code chunk number 9: expr9 (eval = FALSE) ################################################### ## DNA_adjusted <- AdjustAlignment(DNA) ################################################### ### code chunk number 10: expr10 (eval = FALSE) ################################################### ## DNA_staggered <- StaggerAlignment(DNA) ################################################### ### code chunk number 11: sessinfo ################################################### toLatex(sessionInfo(), locale=FALSE)