# conservation Draw a conservative curve, calculate the conservative score ```r conservation() ``` ## Details The tool ennable visualization of amino acid changes at the protein level,The scale of a protein domain and the position of a functional motif/site will be precisely defined. The features available includeting conservation, conservation score ## Returns The returned value is a conservative score ## References https://cran.r-project.org/doc/manuals/R-exts.html ## Author(s) Xiaoyu Zhang ## See Also `help` ## Examples ```r ##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function () { protein = read.table("Protein.txt", sep = "\t", stringsAsFactors = F) domain = read.table("Domain.txt", sep = "\t", stringsAsFactors = F) length = read.table("Length.txt", sep = "\t", stringsAsFactors = F) site = read.table("Site.txt", sep = "\t", stringsAsFactors = F) muta = read.table("Mutagenesis.txt", sep = "\t", stringsAsFactors = F) option = read.table("Option.txt", sep = "\t", stringsAsFactors = F) zoomin = read.table("ZoomIn.txt", sep = "\t", stringsAsFactors = F) nameOfYourQuery = option[2, 1] additionalOptions = option[2, 2] showReferenceSequence = option[2, 3] showConservationScore = option[2, 4] showGridlinesAtTicks = option[2, 5] conservation = option[2, 6] zoomIn = zoomin[2, 1] zoomStart = zoomin[2, 2] zoomEnd = zoomin[2, 3] tickSize = as.numeric(zoomin[2, 4]) referenceSequencePositionInFile = option[2, 7] option = read.table("Option.txt", sep = "\t", stringsAsFactors = F) a <- read.fasta(file = "alignmentFile.fasta") seq <- list() for (i in 1:length(a)) { seq[[i]] <- a[[i]][1:length(a[[i]])] } numberOfSeq <- length(seq) mat <- matrix(0, nrow = length(a), ncol = length(a[[1]])) for (i in 1:length(seq)) { mat[i, ] <- seq[[i]] } df <- as.data.frame(mat) tdf <- t(df) referenceSequencePositionInFile = option[2, 7] referenceSeq <- tdf[which(tdf[, as.numeric(referenceSequencePositionInFile)] != "-"), ] referenceSeq <- as.data.frame(referenceSeq) write.table(referenceSeq, file = "alignment_table", sep = "\t", quote = F, row.names = F, col.names = F) counter <- rep(0, nrow(referenceSeq)) a <- read.table("alignment_table", sep = "\t") a <- data.frame(lapply(a, as.character), stringsAsFactors = FALSE) for (i in 1:nrow(a)) { a[i, "consensus"] <- paste(as.character(a[i, ]), collapse = "") } countBases <- function(string) { table(strsplit(string, "")[[1]]) } c <- as.character(a[, "consensus"]) tab <- list() for (i in 1:length(c)) { tab[[i]] <- countBases(c[i]) } score <- rep(0, nrow(a)) for (i in 1:length(tab)) { for (j in 1:length(tab[[i]])) { if ((names(tab[[i]][j])) == a[i, ][as.numeric(referenceSequencePositionInFile)]) score[i] <- tab[[i]][j] } } scorePlot <- -(((score/numberOfSeq))) a <- read.fasta(file = "alignmentFile.fasta") seqForPlot <- a[[as.numeric(referenceSequencePositionInFile)]][ which(a[[as.numeric(referenceSequencePositionInFile)]] != "-")] if (additionalOptions == "yes") { if (conservation == "yes") { lines(scorePlot, col = "purple3") } } if (additionalOptions == "yes") { if (showReferenceSequence == "yes") { rect(0, -4.75, length(scorePlot), -5.05, col = "white", border = NA) for (i in 1:length(seqForPlot)) { text(i, -4.9, toupper(seqForPlot[i]), font = 2, cex = 1) } } } if (additionalOptions == "yes") { if (showConservationScore == "yes") { rect(0, 0.3, length(scorePlot), 0.7, col = "white", border = NA) for (i in 1:length(seqForPlot)) { text(i, 0.5, toupper(abs(round(scorePlot[i], 1))), font = 2, cex = 0.8, srt = 90, col = "purple3") } } } } ```

conservation function