Nothing
AlignSeqs <- function(myXStringSet,
guideTree=NULL,
iterations=2,
refinements=1,
gapOpening=c(-18, -16),
gapExtension=c(-2, -1),
useStructures=TRUE,
structures=NULL,
FUN=AdjustAlignment,
levels=c(0.9, 0.7, 0.7, 0.4, 10, 5, 5, 2),
alphabet=AA_REDUCED[[1]],
processors=1,
verbose=TRUE,
...) {
# error checking
if (is(myXStringSet, "DNAStringSet")) {
type <- 1L
} else if (is(myXStringSet, "RNAStringSet")) {
type <- 2L
} else if (is(myXStringSet, "AAStringSet")) {
type <- 3L
} else {
stop("myXStringSet must be an AAStringSet, DNAStringSet, or RNAStringSet.")
}
l <- length(myXStringSet)
if (l < 2)
stop("At least two sequences are required in myXStringSet.")
if (!is.null(guideTree)) {
if (is(guideTree, "dendrogram")) {
if (attr(guideTree, "height") > 0.501)
stop("Total height of guideTree can be at most 0.5.")
heights <- rapply(guideTree,
function(x)
attr(x, "height"))
if (any(heights > 0.001) || any(heights < -0.001))
stop("All tips of guideTree must have a height of zero.")
labels <- rapply(guideTree,
function(x)
attr(x, "label"))
if (any(duplicated(labels)))
stop("Leaf labels in guideTree must be unique.")
labels <- match(labels, names(myXStringSet))
if (any(is.na(labels)))
stop("Leaf labels in guideTree must match names of myXStringSet.")
guideTree <- rapply(guideTree,
function(x) {
if (is.leaf(x))
x[1] <- match(attr(x, "label"),
names(myXStringSet))
return(x)
},
how="replace")
} else {
stop("guideTree must be a dendrogram object.")
}
}
if (!is.numeric(iterations))
stop("iterations must be a numeric.")
if (iterations != floor(iterations))
stop("iterations must be a whole number.")
if (iterations < 0)
stop("iterations must be at least zero.")
if (!is.numeric(refinements))
stop("refinements must be a numeric.")
if (refinements != floor(refinements))
stop("refinements must be a whole number.")
if (refinements < 0)
stop("refinements must be at least zero.")
if (!is.logical(useStructures))
stop("useStructures must be a logical.")
if (!is.logical(verbose))
stop("verbose must be a logical.")
a <- vcountPattern("-", myXStringSet)
if (any(a > 0))
stop("Gap characters ('-') must be removed before alignment.")
a <- vcountPattern(".", myXStringSet)
if (any(a > 0))
stop("Unknown characters ('.') must be removed before alignment.")
FUN <- match.fun(FUN)
if (!is.numeric(levels))
stop("levels must be a numeric vector.")
if (length(levels) != 8)
stop("levels must be length 8.")
if (levels[1] < 0 || levels[1] > 1)
stop("levels[1] must be between zero and one (inclusive).")
if (levels[2] < 0 || levels[2] > 1)
stop("levels[2] must be between zero and one (inclusive).")
if (levels[3] < 0 || levels[3] > 1)
stop("levels[3] must be between zero and one (inclusive).")
if (levels[4] < 0 || levels[4] > 1)
stop("levels[4] must be between zero and one (inclusive).")
if (levels[5] <= 0 || is.infinite(levels[5]))
stop("levels[5] must be between zero and Inf (exclusive).")
if (levels[5] != floor(levels[5]))
stop("levels[5] must be a whole number.")
if (levels[6] != floor(levels[6]))
stop("levels[6] must be a whole number.")
if (levels[6] < 0)
stop("levels[6] must be at least zero.")
if (levels[7] <= 0)
stop("levels[7] must be at least zero.")
if (levels[8] <= 0)
stop("levels[8] must be at least zero.")
if (any(alphabet==""))
stop("No elements of alphabet can be empty.")
if (!is.null(processors) && !is.numeric(processors))
stop("processors must be a numeric.")
if (!is.null(processors) && floor(processors)!=processors)
stop("processors must be a whole number.")
if (!is.null(processors) && processors < 1)
stop("processors must be at least 1.")
if (is.null(processors)) {
processors <- detectCores()
} else {
processors <- as.integer(processors)
}
args <- list(...)
n <- names(args)
m <- character(length(n))
for (i in seq_along(n)) {
m[i] <- match.arg(n[i],
names(formals(AlignProfiles)))
}
if (length(gapOpening)==2) {
gapOpeningMin <- gapOpening[1]
gapOpeningMax <- gapOpening[2]
} else if (length(gapOpening)==1) {
gapOpeningMin <- gapOpeningMax <- gapOpening
} else {
stop("gapOpening must be a vector of length 1 or 2.")
}
if (length(gapExtension)==2) {
gapExtensionMin <- gapExtension[1]
gapExtensionMax <- gapExtension[2]
} else if (length(gapExtension)==1) {
gapExtensionMin <- gapExtensionMax <- gapExtension
} else {
stop("gapExtension must be a vector of length 1 or 2.")
}
if (!is.numeric(gapOpeningMax))
stop("gapOpening must be a numeric.")
if (gapOpeningMin > gapOpeningMax)
stop("gapOpening[1] must be less than or equal to gapOpening[2].")
if (!is.numeric(gapExtensionMax))
stop("gapExtension must be a numeric.")
if (gapExtensionMin > gapExtensionMax)
stop("gapExtension[1] must be less than or equal to gapExtension[2].")
gapOpeningSlope <- gapOpeningMax - gapOpeningMin
gapExtensionSlope <- gapExtensionMax - gapExtensionMin
# prepare structures and structure matrix
if (useStructures) {
if (type==3L) {
if (is.null(structures)) {
structures <- PredictHEC(myXStringSet,
type="probabilities")
} else {
if (length(structures) != l)
stop("structures is not the same length as myXStringSet.")
if (typeof(structures) != "list")
stop("structures must be a list.")
}
if (refinements > 0) {
w <- which(m=="structureMatrix")
if (length(w) > 0) {
structureMatrix <- args[[w]]
# assume structures and matrix are ordered the same
if (!is.double(structureMatrix))
stop("structureMatrix must contain numerics.")
if (!is.matrix(structureMatrix))
stop("structureMatrix must be a matrix.")
if (dim(structureMatrix)[1] != dim(structureMatrix)[2])
stop("structureMatrix is not square.")
} else {
structureMatrix <- matrix(c(6, 1, -2, 1, 13, 0, -2, 0, 1),
nrow=3) # order is H, E, C
}
if (dim(structureMatrix)[1] != dim(structures[[1]])[1])
stop("Dimensions of structureMatrix are incompatible with the structures.")
}
} else {
if (!is.null(structures)) {
if (length(structures) != l)
stop("structures is not the same length as myXStringSet.")
if (typeof(structures) != "list")
stop("structures must be a list.")
w <- which(m=="structureMatrix")
if (length(w) > 0) {
structureMatrix <- args[[w]]
# assume structures and matrix are ordered the same
if (!is.double(structureMatrix))
stop("structureMatrix must contain numerics.")
if (!is.matrix(structureMatrix))
stop("structureMatrix must be a matrix.")
if (dim(structureMatrix)[1] != dim(structureMatrix)[2])
stop("structureMatrix is not square.")
} else {
stop("structureMatrix must be specified when structures are provided.")
}
if (dim(structureMatrix)[1] != dim(structures[[1]])[1])
stop("Dimensions of structureMatrix are incompatible with the structures.")
replace <- TRUE
} else if (type==2L) {
w <- which(m=="structureMatrix")
if (length(w) > 0) {
structureMatrix <- args[[w]]
# assume the matrix is in the correct order
if (!is.double(structureMatrix))
stop("structureMatrix must contain numerics.")
if (!is.matrix(structureMatrix))
stop("structureMatrix must be a matrix.")
if (dim(structureMatrix)[1] != dim(structureMatrix)[2])
stop("structureMatrix is not square.")
if (dim(structureMatrix)[1] != 3)
stop("structureMatrix must be 3 x 3 when structures is NULL.")
} else { # use the default structureMatrix
structureMatrix <- matrix(c(6, 0, 0, 0, 30, -6, 0, -6, 30),
nrow=3) # order is ., (, )
}
replace <- FALSE
} else {
structureMatrix <- numeric()
useStructures <- FALSE
}
}
} else {
w <- which(m=="structureMatrix")
if (length(w) > 0)
stop("structureMatrix provided when useStructures is FALSE.")
structureMatrix <- numeric() # needed for colScores
if (!is.null(structures))
stop("structures provided when useStructures is FALSE.")
}
# prepare substitution matrix
if (type==3L) {
r <- strsplit(alphabet, "", fixed=TRUE)
alphabet <- setNames(rep(0L, 20),
AA_STANDARD)
for (i in seq_along(r)) {
w <- which(!(r[[i]] %in% AA_STANDARD))
if (length(w) > 0)
stop("Unrecognized letter(s) found in alphabet: ",
paste(r[[i]][w], collapse=", "),
".")
w <- which(alphabet[r[[i]]] != 0L)
if (length(w) > 0)
stop("Repeated amino acids found in alphabet: ",
paste(r[[i]][w], collapse=", "),
".")
alphabet[r[[i]]] <- i
}
w <- which(alphabet==0L)
if (length(w) > 0)
stop("Standard amino acids missing from alphabet: ",
paste(names(w), collapse=", "),
".")
sizeAA <- max(alphabet)
if (sizeAA==1)
stop("More than one grouping of amino acids is required in the alphabet.")
sizeAA <- as.integer(floor(log(4294967295, sizeAA)))
alphabet <- alphabet - 1L
subM <- TRUE
w <- which(m=="substitutionMatrix")
AAs <- c("A", "R", "N", "D", "C", "Q", "E", "G", "H", "I",
"L", "K", "M", "F", "P", "S", "T", "W", "Y", "V", "*")
if (length(w)==1L) {
sM <- args[[w]]
args[w] <- NULL
if (is.character(sM)) {
if (!(sM %in% c("BLOSUM45", "BLOSUM50", "BLOSUM62", "BLOSUM80", "BLOSUM100", "PAM30", "PAM40", "PAM70", "PAM120", "PAM250", "MIQS")))
stop("Invalid substitutionMatrix.")
}
AAs <- c("A", "R", "N", "D", "C", "Q", "E", "G", "H", "I",
"L", "K", "M", "F", "P", "S", "T", "W", "Y", "V", "*")
if (is.matrix(sM)) {
if (any(!(AAs %in% dimnames(sM)[[1]])) ||
any(!(AAs %in% dimnames(sM)[[2]])))
stop("substitutionMatrix is incomplete.")
} else {
sM <- eval(parse(text=data(list=sM, envir=environment(), package=ifelse(substitutionMatrix=="MIQS", "DECIPHER", "Biostrings"))))
}
sM <- sM[AAs, AAs]
sM <- sM + 0 # convert to numeric matrix
} else {
# use PFASUM50
sM <- matrix(c(4.1181,-1.1516,-1.3187,-1.4135,0.4271,-0.5467,-0.6527,0.1777,-1.6582,-1.1243,-1.1843,-1.0235,-0.5685,-1.9515,-0.6072,0.8284,0.0361,-2.5368,-2.1701,0.0661,-11,-1.1516,6.341,0.0543,-0.6628,-3.2085,1.6006,0.5067,-1.961,0.7706,-3.5053,-3.0357,2.938,-1.9894,-3.7846,-1.3455,-0.4194,-0.5594,-2.1629,-1.7957,-2.9403,-11,-1.3187,0.0543,6.4672,2.3024,-2.5179,0.8192,0.5566,0.1585,1.104,-4.1629,-4.0977,0.8743,-2.6216,-3.805,-1.0904,1.1291,0.3253,-3.7763,-1.874,-3.6076,-11,-1.4135,-0.6628,2.3024,6.8156,-4.358,0.6705,2.582,-0.5667,-0.196,-5.475,-5.1661,0.226,-3.9595,-5.3456,-0.5662,0.4273,-0.5218,-4.7691,-3.4644,-4.5477,-11,0.4271,-3.2085,-2.5179,-4.358,13.5349,-3.3641,-4.3086,-2.1614,-1.8945,-0.7546,-0.9453,-3.8239,-0.5923,-0.8182,-3.6019,-0.3927,-0.801,-1.9317,-1.1607,0.0673,-11,-0.5467,1.6006,0.8192,0.6705,-3.3641,5.5795,2.1372,-1.5923,1.0862,-3.3001,-2.7545,1.872,-1.1216,-3.6631,-1.0426,0.1982,-0.0434,-3.061,-1.9214,-2.6993,-11,-0.6527,0.5067,0.5566,2.582,-4.3086,2.1372,5.5684,-1.6462,-0.2488,-4.1849,-4.0275,1.4821,-2.7964,-4.8311,-0.7028,0.0283,-0.312,-4.1969,-2.9489,-3.281,-11,0.1777,-1.961,0.1585,-0.5667,-2.1614,-1.5923,-1.6462,7.6508,-1.8185,-4.7058,-4.4215,-1.5991,-3.2786,-3.9992,-1.4409,0.184,-1.4823,-3.8328,-3.7343,-3.7264,-11,-1.6582,0.7706,1.104,-0.196,-1.8945,1.0862,-0.2488,-1.8185,9.7543,-3.3812,-2.8685,0.1425,-1.8724,-1.2545,-1.5333,-0.4285,-0.8896,-0.9385,1.6476,-2.8729,-11,-1.1243,-3.5053,-4.1629,-5.475,-0.7546,-3.3001,-4.1849,-4.7058,-3.3812,5.1229,2.5319,-3.5454,1.8309,0.9346,-3.4603,-3.0985,-1.2543,-1.5006,-1.117,3.3961,-11,-1.1843,-3.0357,-4.0977,-5.1661,-0.9453,-2.7545,-4.0275,-4.4215,-2.8685,2.5319,4.7049,-3.4581,2.5303,1.687,-3.365,-3.1578,-1.8626,-0.5308,-0.6881,1.4829,-11,-1.0235,2.938,0.8743,0.226,-3.8239,1.872,1.4821,-1.5991,0.1425,-3.5454,-3.4581,5.5476,-2.164,-4.3516,-0.7583,0.0275,-0.1516,-3.5889,-2.4422,-3.0453,-11,-0.5685,-1.9894,-2.6216,-3.9595,-0.5923,-1.1216,-2.7964,-3.2786,-1.8724,1.8309,2.5303,-2.164,7.0856,1.2339,-3.0823,-1.7587,-0.7402,-0.5841,-0.3946,0.9477,-11,-1.9515,-3.7846,-3.805,-5.3456,-0.8182,-3.6631,-4.8311,-3.9992,-1.2545,0.9346,1.687,-4.3516,1.2339,7.4322,-3.6222,-3.0316,-2.2851,2.6305,3.8302,0.1942,-11,-0.6072,-1.3455,-1.0904,-0.5662,-3.6019,-1.0426,-0.7028,-1.4409,-1.5333,-3.4603,-3.365,-0.7583,-3.0823,-3.6222,9.1796,-0.0652,-0.8587,-3.3634,-3.3006,-2.5443,-11,0.8284,-0.4194,1.1291,0.4273,-0.3927,0.1982,0.0283,0.184,-0.4285,-3.0985,-3.1578,0.0275,-1.7587,-3.0316,-0.0652,4.2366,1.8491,-3.1454,-2.1838,-2.1839,-11,0.0361,-0.5594,0.3253,-0.5218,-0.801,-0.0434,-0.312,-1.4823,-0.8896,-1.2543,-1.8626,-0.1516,-0.7402,-2.2851,-0.8587,1.8491,4.8833,-2.8511,-1.8993,-0.2699,-11,-2.5368,-2.1629,-3.7763,-4.7691,-1.9317,-3.061,-4.1969,-3.8328,-0.9385,-1.5006,-0.5308,-3.5889,-0.5841,2.6305,-3.3634,-3.1454,-2.8511,13.6485,3.3017,-1.851,-11,-2.1701,-1.7957,-1.874,-3.4644,-1.1607,-1.9214,-2.9489,-3.7343,1.6476,-1.117,-0.6881,-2.4422,-0.3946,3.8302,-3.3006,-2.1838,-1.8993,3.3017,8.7568,-1.2438,-11,0.0661,-2.9403,-3.6076,-4.5477,0.0673,-2.6993,-3.281,-3.7264,-2.8729,3.3961,1.4829,-3.0453,0.9477,0.1942,-2.5443,-2.1839,-0.2699,-1.851,-1.2438,4.6928,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,-11,14),
nrow=21,
ncol=21,
dimnames=list(AAs, AAs))
}
} else {
bases <- c("A", "C", "G",
ifelse(type==2L, "U", "T"))
w <- which(m=="substitutionMatrix")
if (length(w) > 0) {
subM <- TRUE
sM <- args[[w]]
args[w] <- NULL
if (is.matrix(sM)) {
if (any(!(bases %in% dimnames(sM)[[1]])) ||
any(!(bases %in% dimnames(sM)[[2]])))
stop("substitutionMatrix is incomplete.")
sM <- sM[bases, bases]
sM <- sM + 0 # convert to numeric matrix
if (type==2L) { # RNAStringSet
sM2 <- sM
dimnames(sM2) <- list(DNA_BASES, DNA_BASES)
}
} else {
stop("substitutionMatrix must be NULL or a matrix.")
}
} else if (type==2L &&
!("misMatch" %in% m) &&
!("perfectMatch" %in% m)) {
subM <- TRUE
sM <- matrix(c(14, 4, 7, 4, 4, 15, 4, 7, 7, 4, 15, 4, 4, 7, 4, 14),
nrow=4,
ncol=4,
dimnames=list(bases, bases))
sM2 <- matrix(c(14, 4, 7, 4, 4, 15, 4, 7, 7, 4, 15, 4, 4, 7, 4, 14),
nrow=4,
ncol=4,
dimnames=list(DNA_BASES, DNA_BASES))
} else {
subM <- FALSE
w <- which(m=="perfectMatch")
if (length(w) > 0) {
PM <- args[[w]]
if (!is.numeric(PM))
stop("perfectMatch must be a numeric.")
} else {
PM <- 5
}
w <- which(m=="misMatch")
if (length(w) > 0) {
MM <- args[[w]]
if (!is.numeric(MM))
stop("misMatch must be a numeric.")
} else {
MM <- 0
}
sM <- matrix(as.numeric(MM),
nrow=4,
ncol=4,
dimnames=list(bases, bases))
diag(sM) <- PM
}
}
if (length(args)==0)
args <- NULL
if (verbose)
time.1 <- Sys.time()
w.x <- width(myXStringSet)
if (type==3L) {
wordSize <- ceiling(log(100*quantile(w.x, 0.99),
.Call("alphabetSizeReducedAA",
myXStringSet,
alphabet,
PACKAGE="DECIPHER")))
if (wordSize > sizeAA)
wordSize <- sizeAA
if (wordSize < 1)
wordSize <- 1
} else {
wordSize <- ceiling(log(100*quantile(w.x, 0.99),
.Call("alphabetSize",
myXStringSet,
PACKAGE="DECIPHER")))
if (wordSize > 15)
wordSize <- 15
if (wordSize < 2)
wordSize <- 2
}
if (is.null(guideTree)) {
if (verbose) {
cat("Determining distance matrix based on shared ",
wordSize,
"-mers:\n",
sep="")
flush.console()
pBar <- txtProgressBar(max=100, style=ifelse(interactive(), 3, 1))
} else {
pBar <- NULL
}
if (type==3L) {
v <- .Call("enumerateSequenceReducedAA",
myXStringSet,
wordSize,
alphabet,
PACKAGE="DECIPHER")
} else { # DNAStringSet or RNAStringSet
v <- .Call("enumerateSequence",
myXStringSet,
wordSize,
PACKAGE="DECIPHER")
}
d <- .Call("matchOrder",
v,
verbose,
pBar,
processors,
PACKAGE="DECIPHER")
attr(d, "Size") <- l
attr(d, "Diag") <- TRUE
attr(d, "Upper") <- TRUE
class(d) <- "dist"
if (verbose) {
setTxtProgressBar(pBar, 100)
close(pBar)
cat("\n")
time.2 <- Sys.time()
print(round(difftime(time.2,
time.1,
units='secs'),
digits=2))
}
if (verbose) {
cat("\nClustering into groups by similarity:\n")
flush.console()
}
dimnames(d) <- NULL
suppressWarnings(guideTree <- IdClusters(d,
method="single",
type="dendrogram",
verbose=verbose,
processors=processors))
}
if (verbose) {
time.1 <- Sys.time()
cat("Aligning Sequences:\n")
flush.console()
pBar <- txtProgressBar(style=ifelse(interactive(), 3, 1), max=100)
before <- steps <- 0L
nsteps <- l - 1L
}
.align <- function(guideTree) { # iteratively align sequences
# initialize a stack of maximum length (l)
stack <- vector("list", l)
visit <- logical(l) # node already visited
parent <- integer(l) # index of parent node
index <- integer(l) # index in parent node
pos <- 1L # current position in the stack
stack[[pos]] <- guideTree
while (pos > 0L) { # more nodes to visit
if (visit[pos]) { # ascending tree
visit[pos] <- FALSE # reset visit
dend <- stack[[pos]]
# align subtrees
treeLengths <- numeric(length(dend))
inherit <- attr(dend, "inherit")
if (!is.null(inherit)) {
if (inherit) {
u <- unlist(dend)
seqs <<- .replace(seqs,
.Call("removeCommonGaps",
.subset(seqs_prev, u),
type,
processors,
PACKAGE="DECIPHER"),
u)
if (verbose) {
steps <<- steps + 1L
percentComplete <- as.integer(100L*steps/nsteps)
if (percentComplete > before) {
setTxtProgressBar(pBar, percentComplete)
before <<- percentComplete
}
}
}
if (length(dend) > 1) {
for (i in seq_len(length(dend))) {
h <- attr(dend[[i]], "treeLength")
if (!is.null(h))
treeLengths[i] <- h
}
h <- attr(dend, "height")
for (i in seq_len(length(dend))) {
m <- unlist(dend[i])
treeLengths[i] <- treeLengths[i] + h - heights[m[1]]
weights[m] <<- weights[m] + (h - heights[m])/length(m)
heights[m] <<- h
}
} else if (is.leaf(dend)) {
heights[unlist(dend)] <- attr(dend, "height")
} else { # inherit from subtree
treeLengths[1] <- attr(dend[[1]], "treeLength")
}
} else if (length(dend) > 1) {
for (i in seq_len(length(dend))) {
h <- attr(dend[[i]], "treeLength")
if (!is.null(h))
treeLengths[i] <- h
}
h <- attr(dend, "height")
members <- vector("list", length(dend))
for (i in seq_len(length(dend))) {
m <- unlist(dend[i])
treeLengths[i] <- treeLengths[i] + h - heights[m[1]]
weights[m] <<- weights[m] + (h - heights[m])/length(m)
heights[m] <<- h
members[[i]] <- m
}
h <- h*2 # total length of sub-tree
GO <- h*gapOpeningSlope + gapOpeningMin
GE <- h*gapExtensionSlope + gapExtensionMin
for (i in 2:length(dend)) {
x <- unlist(members[1:(i - 1)])
y <- members[[i]]
combo <- c(x, y)
p.weight <- weights[x]
w <- which(p.weight <= 0)
if (length(w) > 0)
p.weight[w] <- 1
p.weight <- p.weight/mean(p.weight)
s.weight <- weights[y]
w <- which(s.weight <= 0)
if (length(w) > 0)
s.weight[w] <- 1
s.weight <- s.weight/mean(s.weight)
pattern <- .subset(seqs, x)
subject <- .subset(seqs, y)
if (subM) {
if (useStructures) {
if (is.null(structures)) {
if (type==2L && h < LEVEL) {
# align as DNAStringSet (faster because no pairs matrix)
temp <- .switch(do.call(AlignProfiles,
args=c(list(pattern=.switch(pattern),
subject=.switch(subject),
p.weight=p.weight,
s.weight=s.weight,
substitutionMatrix=sM2,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args)))
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
substitutionMatrix=sM,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args))
}
} else {
if (type==2L && h < LEVEL) {
# align as DNAStringSet (faster because no pairs matrix)
temp <- .switch(do.call(AlignProfiles,
args=c(list(pattern=.switch(pattern),
subject=.switch(subject),
p.weight=p.weight,
s.weight=s.weight,
p.struct=structures[x],
s.struct=structures[y],
substitutionMatrix=sM2,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args)))
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
p.struct=structures[x],
s.struct=structures[y],
substitutionMatrix=sM,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args))
}
}
} else {
if (type==2L && h < LEVEL) {
# align as DNAStringSet (faster because no pairs matrix)
temp <- .switch(do.call(AlignProfiles,
args=c(list(pattern=.switch(pattern),
subject=.switch(subject),
p.weight=p.weight,
s.weight=s.weight,
substitutionMatrix=sM2,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args)))
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
substitutionMatrix=sM,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args))
}
}
} else {
if (useStructures) {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
p.struct=structures[x],
s.struct=structures[y],
processors=processors,
gapOpening=GO,
gapExtension=GE),
args))
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
processors=processors,
gapOpening=GO,
gapExtension=GE),
args))
}
}
if (h > LEVEL &&
length(temp) >= levels[6]) {
weight <- weights[combo]
w <- which(weight <= 0)
if (length(w) > 0)
weight[w] <- 1
weight <- weight/mean(weight)
if (subM) {
temp <- FUN(temp,
substitutionMatrix=sM,
weight=weight,
processors=processors)
} else {
temp <- FUN(temp,
weight=weight,
processors=processors)
}
}
seqs <<- .replace(seqs,
temp,
combo)
if (verbose) {
steps <<- steps + 1L
percentComplete <- as.integer(100L*steps/nsteps)
if (percentComplete > before) {
setTxtProgressBar(pBar, percentComplete)
before <<- percentComplete
}
}
}
} else if (is.leaf(dend)) {
heights[unlist(dend)] <- attr(dend, "height")
} else { # inherit from subtree
treeLengths[1] <- attr(dend[[1]], "treeLength")
}
attr(stack[[pos]], "treeLength") <- sum(treeLengths)
# replace self in parent
if (parent[pos] > 0)
stack[[parent[pos]]][[index[pos]]] <- stack[[pos]]
pos <- pos - 1L # pop off of stack
} else { # descending tree
visit[pos] <- TRUE
p <- pos
for (i in seq_along(stack[[p]])) {
if (!is.leaf(stack[[p]][[i]])) {
# push subtree onto stack
pos <- pos + 1L
stack[[pos]] <- stack[[p]][[i]]
parent[[pos]] <- p
index[[pos]] <- i
}
}
}
}
return(attr(stack[[1]], "treeLength"))
}
.reorder <- function(dend) {
# initialize a stack of maximum length (l)
stack <- vector("list", l)
visit <- logical(l) # node already visited
parent <- integer(l) # index of parent node
index <- integer(l) # index in parent node
pos <- 1L # current position in the stack
stack[[pos]] <- dend
while (pos > 0L) { # more nodes to visit
if (visit[pos]) { # ascending tree
visit[pos] <- FALSE # reset visit
# sort tree by descending width
members <- lapply(stack[[pos]], unlist)
o <- order(sapply(members,
function(x)
max(w.x[x])),
lengths(members),
sapply(members, min),
decreasing=TRUE)
stack[[pos]][] <- stack[[pos]][o]
# replace self in parent
if (parent[pos] > 0)
stack[[parent[pos]]][[index[pos]]] <- stack[[pos]]
pos <- pos - 1L # pop off of stack
} else { # descending tree
visit[pos] <- TRUE
p <- pos
for (i in seq_along(stack[[p]])) {
if (!is.leaf(stack[[p]][[i]])) {
# push subtree onto stack
pos <- pos + 1L
stack[[pos]] <- stack[[p]][[i]]
parent[[pos]] <- p
index[[pos]] <- i
}
}
}
}
return(stack[[1L]])
}
guideTree <- .reorder(guideTree)
ns <- names(myXStringSet)
seqs <- myXStringSet
weights <- heights <- numeric(l)
if (type==3L) {
LEVEL <- levels[1]
} else {
LEVEL <- levels[3]
}
treeLength <- .align(guideTree)
if (refinements==0 && iterations==0) {
if (verbose) {
setTxtProgressBar(pBar, 100)
close(pBar)
cat("\n")
time.2 <- Sys.time()
print(round(difftime(time.2,
time.1,
units='secs'),
digits=2))
flush.console()
cat("\n")
}
names(seqs) <- ns
return(seqs)
}
.RNAStructures <- function(seqs, weights) {
w <- which(weights <= 0)
if (length(w) > 0)
weights[w] <- 1
weights <- weights/mean(weights)
if (replace) {
structureMatrix <- matrix(c(6, 0, 0, 0, 30, -6, 0, -6, 30),
nrow=3) # order is ., (, )
replace <- FALSE
}
PredictDBN(seqs,
type="search",
weight=weights,
processors=processors,
verbose=verbose)
}
minTreeLength <- levels[7]
if (iterations > 0) {
if (type==3L) {
LEVEL <- levels[2]
} else {
LEVEL <- levels[4]
}
.order <- function(dend) {
# initialize a stack of maximum length (l)
stack <- vector("list", l)
visit <- logical(l) # node already visited
pos <- 1L # current position in the stack
stack[[pos]] <- dend
while (pos > 0L) { # more nodes to visit
if (visit[pos]) { # ascending tree
visit[pos] <- FALSE # reset visit
j <<- j + 1L
orders[[j]] <<- unlist(stack[[pos]])
pos <- pos - 1L # pop off of stack
} else { # descending tree
visit[pos] <- TRUE
p <- pos
for (i in seq_along(stack[[p]])) {
if (!is.leaf(stack[[p]][[i]])) {
# push subtree onto stack
pos <- pos + 1L
stack[[pos]] <- stack[[p]][[i]]
}
}
}
}
}
# record the alignment order in the original tree
j <- 0L
orders <- vector("list", l - 1L)
.order(guideTree)
.compare <- function(dend) {
# initialize a stack of maximum length (l)
stack <- vector("list", l)
visit <- logical(l) # node already visited
parent <- integer(l) # index of parent node
index <- integer(l) # index in parent node
found <- logical(l) # exact subtree found
pos <- 1L # current position in the stack
stack[[pos]] <- dend
while (pos > 0L) { # more nodes to visit
if (visit[pos]) { # ascending tree
visit[pos] <- FALSE # reset visit
# replace self in parent
if (parent[pos] > 0)
stack[[parent[pos]]][[index[pos]]] <- stack[[pos]]
pos <- pos - 1L # pop off of stack
} else { # descending tree
if (found[pos]) {
attr(stack[[pos]], "inherit") <- FALSE
if (verbose)
nsteps <<- nsteps - 1L
} else {
o <- unlist(stack[[pos]])
j <<- j + 1L
orders[[j]] <<- o
w <- which(ls==length(o))
for (i in seq_along(w)) {
if (all(orders_prev[[w[i]]]==o)) {
found[pos] <- TRUE
break
}
}
if (found[pos])
attr(stack[[pos]], "inherit") <- TRUE
}
visit[pos] <- TRUE
p <- pos
for (i in seq_along(stack[[p]])) {
if (!is.leaf(stack[[p]][[i]])) {
# push subtree onto stack
pos <- pos + 1L
stack[[pos]] <- stack[[p]][[i]]
parent[[pos]] <- p
index[[pos]] <- i
found[pos] <- found[p]
}
}
}
}
return(stack[[1L]])
}
}
for (it in seq_len(iterations)) {
seqs_prev <- seqs
ls <- lengths(orders)
orders_prev <- orders
if (verbose) {
setTxtProgressBar(pBar, 100)
close(pBar)
cat("\n")
time.2 <- Sys.time()
print(round(difftime(time.2,
time.1,
units='secs'),
digits=2))
if (iterations > 1)
cat("\nIteration ",
it,
" of ",
iterations,
":\n",
sep="")
}
if (type==2L &&
treeLength >= minTreeLength &&
useStructures) {
structures <- .RNAStructures(seqs, weights)
} else if (verbose) {
cat("\n")
}
minTreeLength <- levels[8]
if (verbose) {
cat("Determining distance matrix based on alignment:\n")
flush.console()
}
d <- DistanceMatrix(seqs,
type="dist",
verbose=verbose,
processors=processors,
includeTerminalGaps=TRUE)
if (verbose) {
cat("Reclustering into groups by similarity:\n")
flush.console()
}
orgTree <- guideTree
dimnames(d) <- NULL
suppressWarnings(guideTree <- IdClusters(d,
method="UPGMA",
type="dendrogram",
collapse=0,
verbose=verbose,
processors=processors))
if (verbose) {
time.1 <- Sys.time()
cat("Realigning Sequences:\n")
flush.console()
pBar <- txtProgressBar(style=ifelse(interactive(), 3, 1), max=100)
before <- steps <- 0L
nsteps <- l - 1L
}
j <- 0L
orders <- vector("list", l - 1L)
guideTree <- .reorder(guideTree)
guideTree <- .compare(guideTree)
seqs <- myXStringSet
weights <- heights <- numeric(l)
treeLength <- .align(guideTree)
if (it < iterations && all(seqs==seqs_prev))
break
}
myXStringSet <- seqs
w <- which(weights <= 0)
if (length(w) > 0)
weights[w] <- 1
weights <- weights/mean(weights)
if (verbose) {
setTxtProgressBar(pBar, 100)
close(pBar)
cat("\n")
time.2 <- Sys.time()
print(round(difftime(time.2,
time.1,
units='secs'),
digits=2))
if (iterations > 0 && it < iterations) {
cat("\nAlignment converged - skipping remaining",
ifelse(iterations - it > 1,
"iterations.\n",
"iteration.\n"))
}
}
if (refinements > 0) {
if (type==3L) {
functionCall <- "colScoresAA"
} else {
functionCall <- "colScores"
}
GO <- gapOpeningMax/2 # applied at both ends
colScores <- function(seqs, structs, weights) {
scores <- .Call(functionCall,
seqs,
sM,
GO,
gapExtensionMax,
weights,
structs,
structureMatrix)
return(sum(scores))
}
# define trustworthy groups
if (type==3L) { # AAStringSet
cutoff <- ifelse(iterations > 0,
levels[2]/2, # (fraction identical)/2
levels[1]/2) # (fraction ordered k-mers)/2
} else { # DNAStringSet or RNAStringSet
cutoff <- ifelse(iterations > 0,
levels[4]/2, # (fraction identical)/2
levels[3]/2) # (fraction ordered k-mers)/2
}
guideTree <- cut(guideTree, cutoff)$lower
# refinement
n <- length(guideTree)
if (n > 2) { # more than 2 groups
if (type==2L &&
treeLength >= minTreeLength &&
(iterations==0 || (iterations > 0 && !all(seqs==seqs_prev))) &&
useStructures) {
structures <- .RNAStructures(seqs, weights)
} else if (verbose) {
cat("\n")
}
if (verbose) {
time.1 <- Sys.time()
cat("Refining the alignment:\n")
flush.console()
pBar <- txtProgressBar(style=ifelse(interactive(), 3, 1))
}
score <- colScores(myXStringSet, structures, weights)
vec <- seq_along(myXStringSet)
for (ref in seq_len(refinements)) {
org_score <- score
count <- 0L
for (i in seq_len(n)) {
x <- unlist(guideTree[[i]])
y <- vec[-x]
o <- c(x, y)
pattern <- .subset(myXStringSet, x)
pattern <- .Call("removeCommonGaps",
pattern,
type,
processors,
PACKAGE="DECIPHER")
subject <- .subset(myXStringSet, y)
subject <- .Call("removeCommonGaps",
subject,
type,
processors,
PACKAGE="DECIPHER")
p.weight <- weights[x]
p.weight <- p.weight/mean(p.weight)
s.weight <- weights[y]
s.weight <- s.weight/mean(s.weight)
if (subM) {
if (useStructures) {
if (is.null(structures)) {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
substitutionMatrix=sM,
processors=processors,
gapOpening=gapOpeningMax,
gapExtension=gapExtensionMax),
args))
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
p.struct=structures[x],
s.struct=structures[y],
substitutionMatrix=sM,
processors=processors,
gapOpening=gapOpeningMax,
gapExtension=gapExtensionMax),
args))
}
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
substitutionMatrix=sM,
processors=processors,
gapOpening=gapOpeningMax,
gapExtension=gapExtensionMax),
args))
}
} else {
if (useStructures) {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
p.struct=structures[x],
s.struct=structures[y],
processors=processors,
gapOpening=gapOpeningMax,
gapExtension=gapExtensionMax),
args))
} else {
temp <- do.call(AlignProfiles,
args=c(list(pattern=pattern,
subject=subject,
p.weight=p.weight,
s.weight=s.weight,
processors=processors,
gapOpening=gapOpeningMax,
gapExtension=gapExtensionMax),
args))
}
}
if (useStructures) {
temp_score <- colScores(temp, structures[o], weights[o])
} else {
temp_score <- colScores(temp, NULL, weights[o])
}
if (temp_score > score) {
score <- temp_score
myXStringSet <- .subset(temp, order(o))
count <- count + 1L
if (count %% levels[5] ||
l < levels[6])
next # refine every nth change
if (subM) {
temp <- FUN(myXStringSet,
substitutionMatrix=sM,
weight=weights,
processors=processors)
} else {
temp <- FUN(myXStringSet,
weight=weights,
processors=processors)
}
temp_score <- colScores(temp, structures, weights)
if (temp_score > score) {
score <- temp_score
myXStringSet <- temp
}
}
if (verbose)
setTxtProgressBar(pBar,
(i + n*(ref - 1))/(n*refinements))
}
if (org_score==score) # no changes
break
}
if (verbose) {
setTxtProgressBar(pBar, 1)
close(pBar)
cat("\n")
time.2 <- Sys.time()
print(round(difftime(time.2,
time.1,
units='secs'),
digits=2))
cat("\n")
if (refinements > 0 && ref < refinements)
cat("Alignment converged - skipping remaining",
ifelse(refinements - ref > 1,
"refinements.\n\n",
"refinement.\n\n"))
}
} else if (verbose) {
cat("\n")
}
} else if (verbose) {
cat("\n")
}
if (l >= levels[6]) {
# apply a final adjustment
if (subM) {
myXStringSet <- FUN(myXStringSet,
substitutionMatrix=sM,
weight=weights,
processors=processors)
} else {
myXStringSet <- FUN(myXStringSet,
weight=weights,
processors=processors)
}
}
names(myXStringSet) <- ns
return(myXStringSet)
}
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