# tocID <- "./.utilities.R" # # Miscellaneous R code to suppport the project # # Version: 1.4 # Date: 2017-09 - 2020-09 # Author: Boris Steipe # # V 1.4 Maintenance # V 1.3.1 prefix Biostrings:: to subseq() # V 1.3 load msa support functions # V 1.2 update database utilities to support 2017 version of JSON sources # V 1.1 2017 updates for ABC-units # V 1.0 First code # # ToDo: # Notes: # # ============================================================================== #TOC> ========================================================================== #TOC> #TOC> Section Title Line #TOC> ----------------------------------------------------------- #TOC> 1 SCRIPTS TO SOURCE 42 #TOC> 2 SUPPORT FUNCTIONS 49 #TOC> 2.1 objectInfo() 52 #TOC> 2.2 biCode() 80 #TOC> 2.3 pBar() 114 #TOC> 2.4 waitTimer() 136 #TOC> 2.5 fetchMSAmotif() 164 #TOC> 2.6 H() (Shannon entropy) 208 #TOC> 3 DATA 222 #TOC> 3.1 REFspecies 224 #TOC> 4 FUNCTIONS TO CUSTOMIZE ASSIGNMENTS 239 #TOC> 4.1 getMYSPE() 242 #TOC> 4.2 selectPDBrep() 251 #TOC> #TOC> ========================================================================== # = 1 SCRIPTS TO SOURCE =================================================== source("./scripts/ABC-dbUtilities.R") source("./scripts/ABC-writeALN.R") source("./scripts/ABC-writeMFA.R") # = 2 SUPPORT FUNCTIONS =================================================== # == 2.1 objectInfo() ====================================================== objectInfo <- function(x) { # Function to combine various information items about R objects # # Input: an R object # Value: none - prints information as side-effect cat("object contents:") print(x, digits = 22) # print value at maximal precision cat("\nstructure of object:\n") str(x) if (! is.list(x)) { # Don't use cat() if x is a list. cat() can't handle lists. cat("\nmode: ", mode(x), "\n") cat("typeof: ", typeof(x), "\n") cat("class: ", class(x), "\n") } # if the object has attributes, print them too if (! is.null(attributes(x))) { cat("\nattributes:\n") attributes(x) } # Done } # == 2.2 biCode() ========================================================== biCode <- function(s) { # Make a 5 character "biCode" from a binomial name by concatening # the uppercased first three letter of the first word and the first # two letters of the second word. If there is only one word, we take the # first five characters from that. Outputs are padded with "." if necessary. # NAs in input are preserved. # Parameters: # s chr vector of binomial species names # Value: chr vector of biCodes, same length as s, NAs are preserved b <- character(length(s)) s <- gsub("[^a-zA-Z ]", "", as.character(s)) # remove all non-alphabetic # characters except space s <- toupper(s) for (i in seq_along(s)) { x <- unlist(strsplit(s[i], "\\s+")) if (length(x) == 0) { # empty string x <- c("", "") } else if (length(x) == 1) { # only one string x <- c(substr(x, 1, 3), substr(x, 4, 5)) # 3 + 2 with whatever is there } x <- paste0(x[1:2], "...") # pad strings b[i] <- paste0(substr(x[1], 1, 3), substr(x[2], 1, 2)) } b[is.na(s)] <- NA # recover NAs from input return(b) } # == 2.3 pBar() ============================================================ pBar <- function(i, l, nCh = 50) { # Draw a progress bar in the console # i: the current iteration # l: the total number of iterations # nCh: width of the progress bar ticks <- round(seq(1, l-1, length.out = nCh)) if (i < l) { if (any(i == ticks)) { p <- which(i == ticks)[1] # use only first, in case there are ties p1 <- paste(rep("#", p), collapse = "") p2 <- paste(rep("-", nCh - p), collapse = "") cat(sprintf("\r|%s%s|", p1, p2)) flush.console() } } else { # done cat("\n") } } # == 2.4 waitTimer() ======================================================= waitTimer <- function(t, nIntervals = 50) { # pause and wait for t seconds and display a progress bar as # you are waiting t <- as.numeric(t) if (t < 0.1) {return(invisible())} increment <- t / nIntervals bar <- "----:----|" # One module for the progress bar: bar <- rep(bar, ceiling(nIntervals / 10)) # repeat, bar <- unlist(strsplit(bar, "")) # split into single characters, bar <- bar[1:nIntervals] # truncate, bar <- paste(bar, collapse="") # and collapse. cat(sprintf("\nWaiting: |%s\n |", bar)) for (i in 1:(nIntervals - 1)) { Sys.sleep(increment) cat("=") } Sys.sleep(increment) cat("|\n\n") return(invisible()) } # == 2.5 fetchMSAmotif() =================================================== fetchMSAmotif <- function(ali, mot) { # Retrieve a subset from ali that spans the sequence in mot. # Biostrings package must be installed. # Parameters: # ali MsaAAMultipleAlignment object # mot chr substring within ali # Value: AAStringset if (class(ali) != "MsaAAMultipleAlignment" && class(ali) != "MsaDNAMultipleAlignment" && class(ali) != "MsaRNAMultipleAlignment") { stop("ali has to be an msa multiple alignment object.") } if (class(mot) != "character") { stop("mot has to be a character object.") } x <- gsub("-", "", as.character(ali)) # pure sequence, no hyphens idx <- grep(mot, x)[1] # first sequence containing mot. If no match, # idx becomes NA if (is.na(idx)) { stop("mot is not a subsequence in ali.") } # Find the match range m <- regexpr(mot, x[idx]) motifStart <- as.numeric(m) motifEnd <- attr(m, "match.length") + motifStart - 1 # Count characters, skip hyphens ... x <- unlist(strsplit(as.character(ali)[idx], "")) x <- x != "-" x <- as.numeric(x) x <- cumsum(x) return(Biostrings::subseq(ali@unmasked, start = which(x == motifStart)[1], # get the first position end = which(x == motifEnd)[1])) } # == 2.6 H() (Shannon entropy) ============================================= H <- function(x, N) { # calculate the Shannon entropy of the vector x given N possible states # (in bits). # H(x) = - sum_i(P(x_i) * log2(P(x_i)); 0 * log(0) == 0 t <- table(x) if (missing(N)) { N <- length(t) } if (length(t) > N ) { stop("N can't be smaller than observed states.") } h <- sum(- (t / length(x)) * log2(t / length(x))) return(h) } # = 3 DATA ================================================================ # == 3.1 REFspecies ======================================================== # 10 species of fungi for reference analysis. # http://steipe.biochemistry.utoronto.ca/abc/index.php/Reference_species_for_fungi REFspecies <- c("Aspergillus nidulans", "Bipolaris oryzae", "Coprinopsis cinerea", "Cryptococcus neoformans", "Neurospora crassa", "Puccinia graminis", "Saccharomyces cerevisiae", "Schizosaccharomyces pombe", "Ustilago maydis", "Wallemia mellicola") # = 4 FUNCTIONS TO CUSTOMIZE ASSIGNMENTS ================================== # == 4.1 getMYSPE() ======================================================== getMYSPE <- function(x) { dat <- readRDS("./data/sDat.rds") map <- readRDS("./data/MYSPEmap.rds") key <- gsub(".+(....).$", "\\1", x) return(dat$species[map[key, "iMYSPE"]]) } # == 4.2 selectPDBrep() ==================================================== selectPDBrep <- function(n, seed) { # Select n PDB IDs from a list of high-resolution, non-homologous, single # domain, single chain structure files that represent a CATH topology # group. # Parameters: # n num number of IDs to return # seed num a seed for the RNG # # Value: char PDB IDs # # Note: the list is loaded from an .rds file in the "./data" directory. # If you use this function for a course submission, it MUST be invoked as: # # selectPDBrep(n, seed = myStudentNumber) # # ... and myStudentNumber MUST be correctly initialized pdbRep <- readRDS("./data/pdbRep.rds") # loads pdbRep if (n > length(pdbRep)) { stop(sprintf("There are only %d PDB IDs in the table to choose from.", length(pdbRep))) } oldSeed <- .Random.seed set.seed(seed) PDBset <- sample(pdbRep, n) .Random.seed <- oldSeed return(PDBset) } # [END]