R/cds2rbh.R
In kullrich/CRBHits: Conditional reciprocal best hits (CRBHits) in R
Defines functions
cds2rbh
Documented in
cds2rbh
#' @title cds2rbh
#' @name cds2rbh
#' @description This function calculates (conditional-)reciprocal best hit
#' (CRBHit) pairs from two CDS \code{DNAStringSet}'s.
#' CRBHit pairs were introduced by \emph{Aubry S, Kelly S et al. (2014)}.
#' Sequence searches are performed with \bold{last}
#' \emph{Kiełbasa, SM et al. (2011)} [default]
#' or with \bold{mmseqs2}
#' \emph{Steinegger, M and Soeding, J (2017)}
#' or with \bold{diamond}
#' \emph{Buchfink, B et al. (2021)}.
#' If one specifies cds1 and cds2 as the same input a selfblast is conducted.
#' @param cds1 cds1 sequences as \code{DNAStringSet} [mandatory]
#' @param cds2 cds2 sequences as \code{DNAStringSet} [mandatory]
#' @param dbfile1 aa1 db file [optional]
#' @param dbfile2 aa2 db file [optional]
#' @param searchtool specify sequence search algorithm last, mmseqs2, diamond or
#' lambda3
#' [default: last]
#' @param lastpath specify the PATH to the last binaries
#' [default: /extdata/last-1595/bin/]
#' @param lastD last option D: query letters per random alignment
#' [default: 1e6]
#' @param lastm last option m: maximum initial matches per query position
#' [default: 10]
#' @param mmseqs2path specify the PATH to the mmseqs2 binaries
#' [default: NULL]
#' @param mmseqs2sensitivity specify the sensitivity option of mmseqs2
#' [default: 5.7]
#' @param mmseqs2maxseqs mmseqs2 option: Maximum results per query sequence
#' allowed to pass the prefilter
#' [default: 300]
#' @param diamondpath specify the PATH to the diamond binaries
#' [default: NULL]
#' @param diamondsensitivity specify the sensitivity option of diamond
#' [default: --sensitive]
#' @param diamondmaxtargetseqs specify the maximum number of target sequences
#' per query option of diamond
#' [default: 0]
#' @param lambda3path specify the PATH to the lambda3 binaries
#' [default: NULL]
#' @param lambda3sensitivity specify the sensitivity option of lambda3
#' [default: sensitive]
#' @param lambda3nummatches specify the number of matches per query option of
#' lambda3
#' [default: 25]
#' @param outpath specify the output PATH [default: /tmp]
#' @param crbh specify if conditional-reciprocal hit pairs should be retained
#' as secondary hits [default: TRUE]
#' @param keepSingleDirection specify if single direction secondary hit pairs
#' should be retained [default: FALSE]
#' @param eval evalue [default: 1e-3]
#' @param qcov query coverage [default: 0.0]
#' @param tcov target coverage [default: 0.0]
#' @param pident percent identity [default: 0.0]
#' @param alnlen alignment length [default: 0.0]
#' @param rost1999 specify if hit pairs should be filter by equation 2 of
#' Rost 1999 [default: FALSE]
#' @param filter specify additional custom filters as list to be applied on
#' hit pairs [default: NULL]
#' @param plotCurve specify if crbh fitting curve should be plotted
#' [default: FALSE]
#' @param fit.type specify if mean or median should be used for fitting
#' [default: mean]
#' @param fit.varweight factor for fitting function to consider neighborhood
#' [default: 0.1]
#' @param fit.min specify minimum neighborhood alignment length
#' [default: 5]
#' @param longest.isoform specify if cds sequences should be reduced to the
#' longest isoform (only possible if data was accessed from NCBI or ENSEMBL)
#' [default: FALSE]
#' @param isoform.source specify cds sequences source (either NCBI or ENSEMBL)
#' [default: NCBI]
#' @param threads number of parallel threads [default: 1]
#' @param remove specify if last result files should be removed [default: TRUE]
#' @param remove.db specify if last db files should be removed [default: TRUE]
#' @param shorten1 shorten all sequences to multiple of three [default: FALSE]
#' @param frame1 indicates the first base of the first codon [default: 1]
#' @param framelist1 supply vector of frames for each entry [default: NULL]
#' @param genetic.code1 The genetic code to use for the translation of codons
#' into Amino Acid letters [default: NULL]
#' @param shorten2 shorten all sequences to multiple of three [default: FALSE]
#' @param frame2 indicates the first base of the first codon [default: 1]
#' @param framelist2 supply vector of frames for each entry [default: NULL]
#' @param genetic.code2 The genetic code to use for the translation of codons
#' into Amino Acid letters [default: NULL]
#' @return List of three (crbh=FALSE)\cr
#' 1: $crbh.pairs\cr
#' 2: $crbh1 matrix; query > target\cr
#' 3: $crbh2 matrix; target > query\cr
#' \cr
#' List of four (crbh=TRUE)\cr
#' 1: $crbh.pairs\cr
#' 2: $crbh1 matrix; query > target\cr
#' 3: $crbh2 matrix; target > query\cr
#' 4: $rbh1_rbh2_fit; evalue fitting function
#' @importFrom Biostrings writeXStringSet
#' @importFrom graphics legend par points
#' @importFrom stats median splinefun
#' @importFrom utils read.table
#' @importFrom tidyr %>%
#' @importFrom MSA2dist cds2aa
#' @seealso \code{\link[CRBHits]{cdsfile2rbh}},
#' \code{\link[CRBHits]{isoform2longest}}
#' @references Aubry S, Kelly S et al. (2014) Deep Evolutionary Comparison of
#' Gene Expression Identifies Parallel Recruitment of Trans-Factors in Two
#' Independent Origins of C4 Photosynthesis. \emph{PLOS Genetics},
#' \bold{10(6)} e1004365.
#' @references Kiełbasa, SM et al. (2011) Adaptive seeds tame genomic sequence
#' comparison. \emph{Genome research}, \bold{21(3)}, 487-493.
#' @references Rost B. (1999). Twilight zone of protein sequence alignments.
#' \emph{Protein Engineering}, \bold{12(2)}, 85-94.
#' @examples
#' ## compile last-1595 within CRBHits
#' CRBHits::make_last()
#' ## load example sequence data
#' data("ath", package="CRBHits")
#' data("aly", package="CRBHits")
#' ## get CRBHit pairs
#' ath_aly_crbh <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' plotCurve=TRUE)
#' dim(ath_aly_crbh$crbh.pairs)
#' ## get classical reciprocal best hit (RBHit) pairs
#' ath_aly_rbh <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' crbh=FALSE)
#' dim(ath_aly_rbh$crbh.pairs)
#' ## filter for evalue 1e-100
#' ath_aly_crbh.eval100 <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' eval=1e-100)
#' dim(ath_aly_crbh.eval100$crbh.pairs)
#' ## filter for query coverage
#' ath_aly_crbh.qcov <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' qcov=0.5)
#' dim(ath_aly_crbh.qcov$crbh.pairs)
#' ## custom filter for e.g. bit score (column 12)
#' ## Note: multiple filters can be given in filter param as list
#' myfilter <- function(rbh, value=500.0){
#' return(rbh[as.numeric(rbh[, 12])>=value, , drop=FALSE])
#' }
#' ath_aly_crbh.custom <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' filter=list(myfilter))
#' dim(ath_aly_crbh.custom$crbh.pairs)
#' ## selfblast
#' ath_selfblast_crbh <- cds2rbh(
#' cds1=ath,
#' cds2=ath,
#' plotCurve=TRUE)
#' @export cds2rbh
#' @author Kristian K Ullrich
cds2rbh <- function(cds1, cds2,
dbfile1=NULL,
dbfile2=NULL,
searchtool="last",
lastpath=paste0(find.package("CRBHits"),
"/extdata/last-1595/bin/"),
lastD=1e6,
lastm=10,
mmseqs2path=NULL,
mmseqs2sensitivity=5.7,
mmseqs2maxseqs=300,
diamondpath=NULL,
diamondsensitivity="--sensitive",
diamondmaxtargetseqs=0,
lambda3path=NULL,
lambda3sensitivity="sensitive",
lambda3nummatches=25,
outpath="/tmp",
crbh=TRUE,
keepSingleDirection=FALSE,
eval=1e-3,
qcov=0.0,
tcov=0.0,
pident=0.0,
alnlen=0.0,
rost1999=FALSE,
filter=NULL,
plotCurve=FALSE,
fit.type="mean",
fit.varweight=0.1,
fit.min=5,
longest.isoform=FALSE,
isoform.source="NCBI",
threads=1,
remove=TRUE,
remove.db=TRUE,
shorten1=FALSE,
frame1=1,
framelist1=NULL,
genetic.code1=NULL,
shorten2=FALSE,
frame2=1,
framelist2=NULL,
genetic.code2=NULL
){
#internal function to fit evalue by length
fitSpline <- function(alnlength, evalue, fit.type, fit.varweight, fit.min){
log10evalue <- -log10(evalue)
log10evalue[is.infinite(log10evalue)] <- 324
x <- cbind(alnlength, log10evalue)
x <- x[order(x[, 1]), ]
x.max <- max(x[, 1])
fitMatrix <- matrix(0, ncol=2, nrow=x.max)
for(i in seq(from=1, to=x.max)){
fitMatrix[i, 1] <- i
s <- round(i * fit.varweight)
if(s < fit.min){s <- fit.min}
smin <- i - s
smax <- i + s
s.idx <- which(x[, 1] >= smin & x[, 1] <= smax)
if(length(s.idx)==0){s.value <- 0}
if(length(s.idx)!=0){
if(fit.type=="mean"){
s.value <- mean(x[s.idx, 2])
}
if(fit.type=="median"){
s.value <- median(x[s.idx, 2])
}
}
if(i==1){
fitMatrix[i, 2] <- s.value
}
if(i > 1){
if(fitMatrix[i - 1, 2] <= s.value){
fitMatrix[i, 2] <- s.value
}
if(fitMatrix[i - 1, 2] > s.value){
fitMatrix[i, 2] <- fitMatrix[i - 1, 2]
}
}
}
fitMatrixfun <- splinefun(fitMatrix[,1], fitMatrix[, 2])
return(fitMatrixfun)
}
if(searchtool=="last"){
if(!dir.exists(lastpath)){
stop("Error: last PATH does not exist. Please specify correct
PATH and/or look into package installation prerequisites.
Try to use make_last() function.")
}
if(!file.exists(paste0(lastpath, "lastdb"))){
stop("Error: lastdb binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites. Try to use make_last() function.")
}
if(!file.exists(paste0(lastpath, "lastal"))){
stop("Error: lastal binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites. Try to use make_last() function.")
}
}
if(searchtool=="mmseqs2"){
if(!dir.exists(mmseqs2path)){
stop("Error: mmseqs2 PATH does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
if(!file.exists(paste0(mmseqs2path, "mmseqs"))){
stop("Error: mmseqs2 binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
}
if(searchtool=="diamond"){
if(!dir.exists(diamondpath)){
stop("Error: diamond PATH does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
if(!file.exists(paste0(diamondpath, "diamond"))){
stop("Error: diamond binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
}
if(searchtool=="lambda3"){
if(!dir.exists(lambda3path)){
stop("Error: lambda3 PATH does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
if(!file.exists(paste0(lambda3path, "lambda3"))){
stop("Error: lambda3 binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
}
selfblast <- FALSE
#suppressWarnings since if length of cds1 and cds2 differ, this will
#raise a warning
if(suppressWarnings(all(cds1==cds2))){
selfblast <- TRUE
}
aa1file <- tempfile("aa1_", outpath)
aa2file <- tempfile("aa2_", outpath)
aa1dbfile <- tempfile("aa1db_", outpath)
aa2dbfile <- tempfile("aa2db_", outpath)
if(!is.null(dbfile1)){
aa1dbfile <- dbfile1
}
if(!is.null(dbfile2)){
aa2dbfile <- dbfile2
}
if(searchtool=="last"){
aa2_aa1_lastout <- tempfile("aa2_aa1_lastout_", outpath)
aa1_aa2_lastout <- tempfile("aa1_aa2_lastout_", outpath)
}
if(searchtool=="mmseqs2"){
aa2_aa1_lastout <- tempfile("aa2_aa1_mmseqs2_", outpath)
aa1_aa2_lastout <- tempfile("aa1_aa2_mmseqs2_", outpath)
}
if(searchtool=="diamond"){
aa2_aa1_lastout <- tempfile("aa2_aa1_diamond_", outpath)
aa1_aa2_lastout <- tempfile("aa1_aa2_diamond_", outpath)
}
if(searchtool=="lambda3"){
aa1file <- tempfile("aa1_", outpath, fileext = ".fa")
aa2file <- tempfile("aa2_", outpath, fileext = ".fa")
aa1dbfile <- tempfile("aa1db_", outpath, fileext = ".lba")
aa2dbfile <- tempfile("aa2db_", outpath, fileext = ".lba")
aa2_aa1_lastout <- tempfile("aa2_aa1_lambda3_", outpath,
fileext = ".m8")
aa1_aa2_lastout <- tempfile("aa1_aa2_lambda3_", outpath,
fileext = ".m8")
}
if(longest.isoform){
Biostrings::writeXStringSet(MSA2dist::cds2aa(isoform2longest(cds1,
isoform.source), shorten=shorten1, frame=frame1,
framelist=framelist1, genetic.code=genetic.code1), file=aa1file)
Biostrings::writeXStringSet(MSA2dist::cds2aa(isoform2longest(cds2,
isoform.source), shorten=shorten2, frame=frame2,
framelist=framelist2, genetic.code=genetic.code2), file=aa2file)
}
if(!longest.isoform){
Biostrings::writeXStringSet(MSA2dist::cds2aa(cds1, shorten=shorten1,
frame=frame1, framelist=framelist1, genetic.code=genetic.code1),
file=aa1file)
Biostrings::writeXStringSet(MSA2dist::cds2aa(cds2, shorten=shorten2,
frame=frame2, framelist=framelist2, genetic.code=genetic.code2),
file=aa2file)
}
if(searchtool=="last"){
system2(command=paste0(lastpath, "lastdb"),
args = c("-p", "-cR01", "-P", threads, aa1dbfile, aa1file))
system2(command=paste0(lastpath, "lastdb"),
args = c("-p", "-cR01", "-P", threads, aa2dbfile, aa2file))
system2(command=paste0(lastpath, "lastal"),
args = c("-f", "BlastTab+", "-P", threads, "-D", lastD, "-m", lastm,
aa1dbfile, aa2file, ">", aa2_aa1_lastout))
system2(command=paste0(lastpath, "lastal"),
args = c("-f", "BlastTab+", "-P", threads, "-D", lastD, "-m", lastm,
aa2dbfile, aa1file, ">", aa1_aa2_lastout))
}
if(searchtool=="mmseqs2"){
system2(command=paste0(mmseqs2path, "mmseqs"),
args = c("easy-search", aa1file, aa2file, aa1_aa2_lastout, outpath,
"--threads", threads, "-s", mmseqs2sensitivity,
"--max-seqs", mmseqs2maxseqs,
"--format-output", paste0("query,target,fident,alnlen,",
"mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,qlen,",
"tlen,raw")))
system2(command=paste0(mmseqs2path, "mmseqs"),
args = c("easy-search", aa2file, aa1file, aa2_aa1_lastout, outpath,
"--threads", threads, "-s", mmseqs2sensitivity,
"--max-seqs", mmseqs2maxseqs,
"--format-output", paste0("query,target,fident,alnlen,",
"mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,qlen,",
"tlen,raw")))
}
if(searchtool=="diamond"){
system2(command=paste0(diamondpath, "diamond"),
args = c("makedb", "--in", aa1file,
"-d", aa1dbfile))
system2(command=paste0(diamondpath, "diamond"),
args = c("makedb", "--in", aa2file,
"-d", aa2dbfile))
system2(command=paste0(diamondpath, "diamond"),
args = c("blastp", "--ignore-warnings", "-d", aa2dbfile,
"-q", aa1file, "-o", aa1_aa2_lastout, diamondsensitivity,
"--max-target-seqs", diamondmaxtargetseqs,
"-f", "6", "qseqid", "sseqid", "pident", "length", "mismatch",
"gapopen", "qstart", "qend", "sstart", "send", "evalue",
"bitscore", "qlen", "slen", "score", "--threads", threads))
system2(command=paste0(diamondpath, "diamond"),
args = c("blastp", "--ignore-warnings", "-d", aa1dbfile,
"-q", aa2file, "-o", aa2_aa1_lastout, diamondsensitivity,
"--max-target-seqs", diamondmaxtargetseqs,
"-f", "6", "qseqid", "sseqid", "pident", "length", "mismatch",
"gapopen", "qstart", "qend", "sstart", "send", "evalue",
"bitscore", "qlen", "slen", "score", "--threads", threads))
}
if(searchtool=="lambda3"){
system2(command=paste0(lambda3path, "lambda3"),
args = c("mkindexp", "-d", aa1file, "-i", aa1dbfile,
"--threads", threads))
system2(command=paste0(lambda3path, "lambda3"),
args = c("mkindexp", "-d", aa2file, "-i", aa2dbfile,
"--threads", threads))
system2(command=paste0(lambda3path, "lambda3"),
args = c("searchp", "-i", aa2dbfile, "-q", aa1file,
"-o", aa1_aa2_lastout, "-p", lambda3sensitivity,
"--num-matches", lambda3nummatches, "--output-columns",
"'std qlen slen score'", "--threads", threads))
system2(command=paste0(lambda3path, "lambda3"),
args = c("searchp", "-i", aa1dbfile, "-q", aa2file,
"-o", aa2_aa1_lastout, "-p", lambda3sensitivity,
"--num-matches", lambda3nummatches, "--output-columns",
"'std qlen slen score'", "--threads", threads))
}
aa1_aa2 <- read.table(aa1_aa2_lastout, sep="\t", header=FALSE,
stringsAsFactors=FALSE)
aa2_aa1 <- read.table(aa2_aa1_lastout, sep="\t", header=FALSE,
stringsAsFactors=FALSE)
colnames(aa1_aa2) <- colnames(aa2_aa1) <- c("query_id", "subject_id",
"perc_identity", "alignment_length", "mismatches", "gap_opens",
"q_start", "q_end", "s_start", "s_end", "evalue", "bit_score",
"query_length", "subject_length", "raw_score")
if(searchtool=="mmseqs2"){
aa1_aa2[, "perc_identity"] <- aa1_aa2[, "perc_identity"] * 100
aa2_aa1[, "perc_identity"] <- aa2_aa1[, "perc_identity"] * 100
}
if(remove){
system2(command="rm", args = aa1file)
system2(command="rm", args = aa2file)
system2(command="rm", args = aa2_aa1_lastout)
system2(command="rm", args = aa1_aa2_lastout)
}
if(remove.db){
system2(command="rm", args = paste0(aa1dbfile, "*"))
system2(command="rm", args = paste0(aa2dbfile, "*"))
}
#selfblast
if(selfblast){
aa1_aa2 <- aa1_aa2[aa1_aa2[, 1]!=aa1_aa2[, 2], , drop=FALSE]
aa2_aa1 <- aa2_aa1[aa2_aa1[, 1]!=aa2_aa1[, 2], , drop=FALSE]
if(dim(aa1_aa2)[1]==0 & dim(aa2_aa1)[1]==0){
stop("No recirpocal best hits!")
}
}
#apply standard filters on hit pairs
aa1_aa2 <- aa1_aa2 %>% filter_eval(eval) %>% filter_qcov(qcov) %>%
filter_tcov(tcov) %>% filter_pident(pident) %>%
filter_alnlen(alnlen)
aa2_aa1 <- aa2_aa1 %>% filter_eval(eval) %>% filter_qcov(qcov) %>%
filter_tcov(tcov) %>% filter_pident(pident) %>%
filter_alnlen(alnlen)
if(rost1999){
aa1_aa2 <- aa1_aa2 %>% filter_rost1999
aa2_aa1 <- aa2_aa1 %>% filter_rost1999
}
#apply additional filters on hit pairs
for(f_ in filter){
aa1_aa2 <- aa1_aa2 %>% f_
aa2_aa1 <- aa2_aa1 %>% f_
}
if(dim(aa1_aa2)[1]==0 & dim(aa2_aa1)[1]==0){
stop("No recirpocal best hits!")
}
aa1_aa2.idx <- paste0(aa1_aa2[, 1], "\t", aa1_aa2[, 2])
aa2_aa1.idx <- paste0(aa2_aa1[, 2], "\t", aa2_aa1[, 1])
#deduplicate hit pairs and only retain the best hit per query
aa1_aa2.dedup <- aa1_aa2[!duplicated(aa1_aa2[, 1]), , drop=FALSE]
aa2_aa1.dedup <- aa2_aa1[!duplicated(aa2_aa1[, 1]), , drop=FALSE]
aa1_aa2.dedup.idx <- paste0(aa1_aa2.dedup[, 1], "\t", aa1_aa2.dedup[, 2])
aa2_aa1.dedup.idx <- paste0(aa2_aa1.dedup[, 2], "\t", aa2_aa1.dedup[, 1])
#reduce to reciprocal best hits
rbh1 <- aa1_aa2.dedup[which(aa1_aa2.dedup.idx %in% aa2_aa1.dedup.idx), ,
drop=FALSE]
rbh2 <- aa2_aa1.dedup[which(aa2_aa1.dedup.idx %in% aa1_aa2.dedup.idx), ,
drop=FALSE]
if(selfblast){
rbh1 <- rbh1[!duplicated(apply(rbh1[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
rbh2 <- rbh2[!duplicated(apply(rbh2[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
}
#if no crbh - done
if(!crbh){
rbh <- rbh1[, seq_len(2)]
rbh <- cbind(rbh, "rbh")
colnames(rbh) <- c("aa1", "aa2", "rbh_class")
out <- list(rbh, cbind(rbh1, "rbh"), cbind(rbh2, "rbh"))
names(out) <- c("crbh.pairs", "crbh1", "crbh2")
if(!selfblast){
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- FALSE
attr(out, "keepSingleDirection") <- FALSE
attr(out, "selfblast") <- selfblast
return(out)
}
if(selfblast){
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- FALSE
attr(out, "keepSingleDirection") <- FALSE
attr(out, "selfblast") <- selfblast
return(out)
}
}
#if crbh - continue
if(crbh){
#fit evalue by length
if(!selfblast){
rbh1_rbh2_fit <- fitSpline(c(rbh1[, 4], rbh2[, 4]),
c(rbh1[, 11], rbh2[, 11]),
fit.type,
fit.varweight,
fit.min)
}
#selfblast
if(selfblast){
rbh1_rbh2_fit <- fitSpline(c(rbh1[, 4]),
c(rbh1[, 11]),
fit.type,
fit.varweight,
fit.min)
}
#internal function to filter hit pairs using rbh1_rbh2_fit
filter_crbh <- function(x){
minuslog10evalue_by_fit <- lapply(as.numeric(x[, 4]), rbh1_rbh2_fit)
return(x[as.numeric(x[, 16]) >= minuslog10evalue_by_fit, ,
drop=FALSE])
}
#remove reciprocal best hits from hit pairs to only look into
#secondary hits
if(!selfblast){
rbh1.idx <- paste0(rbh1[, 1], "\t", rbh1[, 2])
rbh2.idx <- paste0(rbh2[, 2], "\t", rbh2[, 1])
}
if(selfblast){
rbh1.idx <- c(paste0(rbh1[, 1], "\t", rbh1[, 2]),
paste0(rbh1[, 2], "\t", rbh1[, 1]))
rbh2.idx <- c(paste0(rbh2[, 2], "\t", rbh2[, 1]),
paste0(rbh2[, 1], "\t", rbh2[, 2]))
}
aa1_aa2.red <- aa1_aa2[!aa1_aa2.idx %in% rbh1.idx, , drop=FALSE]
aa2_aa1.red <- aa2_aa1[!aa2_aa1.idx %in% rbh2.idx, , drop=FALSE]
#add -log10(evalue)
aa1_aa2.red <- cbind(aa1_aa2.red, -log10(aa1_aa2.red[, 11]))
aa1_aa2.red[is.infinite(aa1_aa2.red[, 16]), 16] <- 324
aa2_aa1.red <- cbind(aa2_aa1.red, -log10(aa2_aa1.red[, 11]))
aa2_aa1.red[is.infinite(aa2_aa1.red[, 16]), 16] <- 324
#filter retained hit pairs with rbh1_rbh2_fit
aa1_aa2.red <- filter_crbh(aa1_aa2.red)
aa2_aa1.red <- filter_crbh(aa2_aa1.red)
if(dim(aa1_aa2.red)[1]!=0){
aa1_aa2.red.idx <- paste0(aa1_aa2.red[, 1], "\t", aa1_aa2.red[, 2])
}
if(dim(aa1_aa2.red)[1]==0){
aa1_aa2.red.idx <- NULL
}
if(dim(aa2_aa1.red)[1]!=0){
aa2_aa1.red.idx <- paste0(aa2_aa1.red[, 2], "\t", aa2_aa1.red[, 1])
}
if(dim(aa2_aa1.red)[1]==0){
aa2_aa1.red.idx <- NULL
}
#deduplicate hit pairs and only retain the best hit per HSP
aa1_aa2.red.dedup <- aa1_aa2.red[!duplicated(aa1_aa2.red.idx), ,
drop=FALSE]
aa2_aa1.red.dedup <- aa2_aa1.red[!duplicated(aa2_aa1.red.idx), ,
drop=FALSE]
#split into reciprocal direction secondary hits (rbh.sec) and single
#direction (single)
if(dim(aa1_aa2.red.dedup)[1]!=0){
aa1_aa2.red.dedup.idx <- paste0(aa1_aa2.red.dedup[, 1], "\t",
aa1_aa2.red.dedup[, 2])
}
if(dim(aa1_aa2.red.dedup)[1]==0){
aa1_aa2.red.dedup.idx <- NULL
}
if(dim(aa2_aa1.red.dedup)[1]!=0){
aa2_aa1.red.dedup.idx <- paste0(aa2_aa1.red.dedup[, 2], "\t",
aa2_aa1.red.dedup[, 1])
}
if(dim(aa2_aa1.red.dedup)[1]==0){
aa2_aa1.red.dedup.idx <- NULL
}
rbh1.sec <- aa1_aa2.red.dedup[which(aa1_aa2.red.dedup.idx %in%
aa2_aa1.red.dedup.idx), , drop=FALSE]
rbh2.sec <- aa2_aa1.red.dedup[which(aa2_aa1.red.dedup.idx %in%
aa1_aa2.red.dedup.idx), , drop=FALSE]
if(selfblast){
rbh1.sec <- rbh1.sec[!duplicated(apply(rbh1.sec[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
rbh2.sec <- rbh2.sec[!duplicated(apply(rbh2.sec[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
}
single1 <- aa1_aa2.red.dedup[which(!aa1_aa2.red.dedup.idx %in%
aa2_aa1.red.dedup.idx), , drop=FALSE]
single2 <- aa2_aa1.red.dedup[which(!aa2_aa1.red.dedup.idx %in%
aa1_aa2.red.dedup.idx), , drop=FALSE]
#if plotCurve plot fitting
if(plotCurve){
len <- rbh1[, 4]
log10alnlen <- log10(len)
minuslog10evalue <- -log10(rbh1[, 11])
minuslog10evalue[is.infinite(minuslog10evalue)] <- 324
plot(x=log10alnlen, y=minuslog10evalue,
pch=20,
main="Accept / Reject secondary hits as homologs",
ylab="-log10(evalue)",
xlab="log10(alnlength)",
col=col2transparent("#8EBCB5", 50),
cex=0.75)
points(x=log10(rbh1.sec[, 4]), y=-log10(rbh1.sec[, 11]),
pch=21,
bg=col2transparent("#4D83AB", 25),
cex=1)
points(x=log10(single1[, 4]), y=-log10(single1[, 11]),
pch=21,
bg=col2transparent("#CBC106", 25),
cex=1)
if(selfblast){
points(x=log10(seq_len(max(rbh1[, 4]))),
y=rbh1_rbh2_fit(seq(from=1, to=max(rbh1[, 4]))),
type="l",
lwd=2,
col="#9E163C")
legend("bottomright",
legend=c("rbh", "sec", "single"),
col=c("#8EBCB5",
col2transparent("#4D83AB", 25),
col2transparent("#CBC106", 25)),
bty="n",
pch=20)
}
if(!selfblast){
points(x=log10(single2[, 4]), y=-log10(single2[, 11]),
pch=21,
bg=col2transparent("#CB7B26", 25),
cex=1)
points(x=log10(seq_len(max(rbh1[, 4]))),
y=rbh1_rbh2_fit(seq(from=1, to=max(rbh1[, 4]))),
type="l",
lwd=2,
col="#9E163C")
legend("bottomright",
legend=c("rbh", "sec", "single1", "single2"),
col=c("#8EBCB5",
col2transparent("#4D83AB", 25),
col2transparent("#CBC106", 25),
col2transparent("#CB7B26", 25)),
bty="n",
pch=20)
}
}
#if no keepSingleDirection - done
if(!keepSingleDirection){
if(dim(rbh1.sec)[1]!=0){
crbh1 <- data.frame(Map(c ,cbind(rbh1, "rbh"),
cbind(rbh1.sec[, seq_len(15)], "sec")))
}
if(dim(rbh1.sec)[1]==0){
crbh1 <- data.frame(Map(c ,cbind(rbh1, "rbh")))
}
colnames(crbh1)[16] <- "rbh_class"
if(dim(rbh2.sec)[1]!=0){
crbh2 <- data.frame(Map(c ,cbind(rbh2, "rbh"),
cbind(rbh2.sec[, seq_len(15)], "sec")))
}
if(dim(rbh2.sec)[1]==0){
crbh2 <- data.frame(Map(c ,cbind(rbh2, "rbh")))
}
colnames(crbh2)[16] <- "rbh_class"
crbh <- crbh1[, c(seq_len(2), 16)]
colnames(crbh) <- c("aa1", "aa2", "rbh_class")
out <- list(crbh, crbh1, crbh2, rbh1_rbh2_fit)
names(out) <- c("crbh.pairs", "crbh1", "crbh2", "rbh1_rbh2_fit")
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- TRUE
attr(out, "keepSingleDirection") <- FALSE
attr(out, "selfblast") <- selfblast
return(out)
}
#if keepSingleDirection - include single - done
if(keepSingleDirection){
if(dim(rbh1.sec)[1]!=0 & dim(single1)[1]!=0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh"),
cbind(rbh1.sec[, seq_len(15)], "sec"),
cbind(single1[, seq_len(15)], "single")))
}
if(dim(rbh1.sec)[1]!=0 & dim(single1)[1]==0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh"),
cbind(rbh1.sec[, seq_len(15)], "sec")))
}
if(dim(rbh1.sec)[1]==0 & dim(single1)[1]!=0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh"),
cbind(single1[, seq_len(15)], "single")))
}
if(dim(rbh1.sec)[1]==0 & dim(single1)[1]==0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh")))
}
colnames(crbh1)[16] <- "rbh_class"
if(dim(rbh2.sec)[1]!=0 & dim(single2)[1]!=0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh"),
cbind(rbh2.sec[, seq_len(15)], "sec"),
cbind(single2[, seq_len(15)], "single")))
}
if(dim(rbh2.sec)[1]!=0 & dim(single2)[1]==0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh"),
cbind(rbh2.sec[, seq_len(15)], "sec")))
}
if(dim(rbh2.sec)[1]==0 & dim(single2)[1]!=0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh"),
cbind(single2[, seq_len(15)], "single")))
}
if(dim(rbh2.sec)[1]==0 & dim(single2)[1]==0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh")))
}
colnames(crbh2)[16] <- "rbh_class"
crbh <- data.frame(Map(c, crbh1[, c(seq_len(2), 16)],
crbh2[crbh2$rbh_class=="single", , drop=FALSE][, c(2, 1, 16)]))
colnames(crbh) <- c("aa1", "aa2", "rbh_class")
out <- list(crbh, crbh1, crbh2, rbh1_rbh2_fit)
names(out) <- c("crbh.pairs", "crbh1", "crbh2", "rbh1_rbh2_fit")
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- TRUE
attr(out, "keepSingleDirection") <- TRUE
attr(out, "selfblast") <- selfblast
return(out)
}
}
}
kullrich/CRBHits documentation built on Nov. 13, 2024, 7:44 a.m.
R Package Documentation
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Defines functions cds2rbh
Documented in cds2rbh
#' @title cds2rbh
#' @name cds2rbh
#' @description This function calculates (conditional-)reciprocal best hit
#' (CRBHit) pairs from two CDS \code{DNAStringSet}'s.
#' CRBHit pairs were introduced by \emph{Aubry S, Kelly S et al. (2014)}.
#' Sequence searches are performed with \bold{last}
#' \emph{Kiełbasa, SM et al. (2011)} [default]
#' or with \bold{mmseqs2}
#' \emph{Steinegger, M and Soeding, J (2017)}
#' or with \bold{diamond}
#' \emph{Buchfink, B et al. (2021)}.
#' If one specifies cds1 and cds2 as the same input a selfblast is conducted.
#' @param cds1 cds1 sequences as \code{DNAStringSet} [mandatory]
#' @param cds2 cds2 sequences as \code{DNAStringSet} [mandatory]
#' @param dbfile1 aa1 db file [optional]
#' @param dbfile2 aa2 db file [optional]
#' @param searchtool specify sequence search algorithm last, mmseqs2, diamond or
#' lambda3
#' [default: last]
#' @param lastpath specify the PATH to the last binaries
#' [default: /extdata/last-1595/bin/]
#' @param lastD last option D: query letters per random alignment
#' [default: 1e6]
#' @param lastm last option m: maximum initial matches per query position
#' [default: 10]
#' @param mmseqs2path specify the PATH to the mmseqs2 binaries
#' [default: NULL]
#' @param mmseqs2sensitivity specify the sensitivity option of mmseqs2
#' [default: 5.7]
#' @param mmseqs2maxseqs mmseqs2 option: Maximum results per query sequence
#' allowed to pass the prefilter
#' [default: 300]
#' @param diamondpath specify the PATH to the diamond binaries
#' [default: NULL]
#' @param diamondsensitivity specify the sensitivity option of diamond
#' [default: --sensitive]
#' @param diamondmaxtargetseqs specify the maximum number of target sequences
#' per query option of diamond
#' [default: 0]
#' @param lambda3path specify the PATH to the lambda3 binaries
#' [default: NULL]
#' @param lambda3sensitivity specify the sensitivity option of lambda3
#' [default: sensitive]
#' @param lambda3nummatches specify the number of matches per query option of
#' lambda3
#' [default: 25]
#' @param outpath specify the output PATH [default: /tmp]
#' @param crbh specify if conditional-reciprocal hit pairs should be retained
#' as secondary hits [default: TRUE]
#' @param keepSingleDirection specify if single direction secondary hit pairs
#' should be retained [default: FALSE]
#' @param eval evalue [default: 1e-3]
#' @param qcov query coverage [default: 0.0]
#' @param tcov target coverage [default: 0.0]
#' @param pident percent identity [default: 0.0]
#' @param alnlen alignment length [default: 0.0]
#' @param rost1999 specify if hit pairs should be filter by equation 2 of
#' Rost 1999 [default: FALSE]
#' @param filter specify additional custom filters as list to be applied on
#' hit pairs [default: NULL]
#' @param plotCurve specify if crbh fitting curve should be plotted
#' [default: FALSE]
#' @param fit.type specify if mean or median should be used for fitting
#' [default: mean]
#' @param fit.varweight factor for fitting function to consider neighborhood
#' [default: 0.1]
#' @param fit.min specify minimum neighborhood alignment length
#' [default: 5]
#' @param longest.isoform specify if cds sequences should be reduced to the
#' longest isoform (only possible if data was accessed from NCBI or ENSEMBL)
#' [default: FALSE]
#' @param isoform.source specify cds sequences source (either NCBI or ENSEMBL)
#' [default: NCBI]
#' @param threads number of parallel threads [default: 1]
#' @param remove specify if last result files should be removed [default: TRUE]
#' @param remove.db specify if last db files should be removed [default: TRUE]
#' @param shorten1 shorten all sequences to multiple of three [default: FALSE]
#' @param frame1 indicates the first base of the first codon [default: 1]
#' @param framelist1 supply vector of frames for each entry [default: NULL]
#' @param genetic.code1 The genetic code to use for the translation of codons
#' into Amino Acid letters [default: NULL]
#' @param shorten2 shorten all sequences to multiple of three [default: FALSE]
#' @param frame2 indicates the first base of the first codon [default: 1]
#' @param framelist2 supply vector of frames for each entry [default: NULL]
#' @param genetic.code2 The genetic code to use for the translation of codons
#' into Amino Acid letters [default: NULL]
#' @return List of three (crbh=FALSE)\cr
#' 1: $crbh.pairs\cr
#' 2: $crbh1 matrix; query > target\cr
#' 3: $crbh2 matrix; target > query\cr
#' \cr
#' List of four (crbh=TRUE)\cr
#' 1: $crbh.pairs\cr
#' 2: $crbh1 matrix; query > target\cr
#' 3: $crbh2 matrix; target > query\cr
#' 4: $rbh1_rbh2_fit; evalue fitting function
#' @importFrom Biostrings writeXStringSet
#' @importFrom graphics legend par points
#' @importFrom stats median splinefun
#' @importFrom utils read.table
#' @importFrom tidyr %>%
#' @importFrom MSA2dist cds2aa
#' @seealso \code{\link[CRBHits]{cdsfile2rbh}},
#' \code{\link[CRBHits]{isoform2longest}}
#' @references Aubry S, Kelly S et al. (2014) Deep Evolutionary Comparison of
#' Gene Expression Identifies Parallel Recruitment of Trans-Factors in Two
#' Independent Origins of C4 Photosynthesis. \emph{PLOS Genetics},
#' \bold{10(6)} e1004365.
#' @references Kiełbasa, SM et al. (2011) Adaptive seeds tame genomic sequence
#' comparison. \emph{Genome research}, \bold{21(3)}, 487-493.
#' @references Rost B. (1999). Twilight zone of protein sequence alignments.
#' \emph{Protein Engineering}, \bold{12(2)}, 85-94.
#' @examples
#' ## compile last-1595 within CRBHits
#' CRBHits::make_last()
#' ## load example sequence data
#' data("ath", package="CRBHits")
#' data("aly", package="CRBHits")
#' ## get CRBHit pairs
#' ath_aly_crbh <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' plotCurve=TRUE)
#' dim(ath_aly_crbh$crbh.pairs)
#' ## get classical reciprocal best hit (RBHit) pairs
#' ath_aly_rbh <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' crbh=FALSE)
#' dim(ath_aly_rbh$crbh.pairs)
#' ## filter for evalue 1e-100
#' ath_aly_crbh.eval100 <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' eval=1e-100)
#' dim(ath_aly_crbh.eval100$crbh.pairs)
#' ## filter for query coverage
#' ath_aly_crbh.qcov <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' qcov=0.5)
#' dim(ath_aly_crbh.qcov$crbh.pairs)
#' ## custom filter for e.g. bit score (column 12)
#' ## Note: multiple filters can be given in filter param as list
#' myfilter <- function(rbh, value=500.0){
#' return(rbh[as.numeric(rbh[, 12])>=value, , drop=FALSE])
#' }
#' ath_aly_crbh.custom <- cds2rbh(
#' cds1=ath,
#' cds2=aly,
#' filter=list(myfilter))
#' dim(ath_aly_crbh.custom$crbh.pairs)
#' ## selfblast
#' ath_selfblast_crbh <- cds2rbh(
#' cds1=ath,
#' cds2=ath,
#' plotCurve=TRUE)
#' @export cds2rbh
#' @author Kristian K Ullrich
cds2rbh <- function(cds1, cds2,
dbfile1=NULL,
dbfile2=NULL,
searchtool="last",
lastpath=paste0(find.package("CRBHits"),
"/extdata/last-1595/bin/"),
lastD=1e6,
lastm=10,
mmseqs2path=NULL,
mmseqs2sensitivity=5.7,
mmseqs2maxseqs=300,
diamondpath=NULL,
diamondsensitivity="--sensitive",
diamondmaxtargetseqs=0,
lambda3path=NULL,
lambda3sensitivity="sensitive",
lambda3nummatches=25,
outpath="/tmp",
crbh=TRUE,
keepSingleDirection=FALSE,
eval=1e-3,
qcov=0.0,
tcov=0.0,
pident=0.0,
alnlen=0.0,
rost1999=FALSE,
filter=NULL,
plotCurve=FALSE,
fit.type="mean",
fit.varweight=0.1,
fit.min=5,
longest.isoform=FALSE,
isoform.source="NCBI",
threads=1,
remove=TRUE,
remove.db=TRUE,
shorten1=FALSE,
frame1=1,
framelist1=NULL,
genetic.code1=NULL,
shorten2=FALSE,
frame2=1,
framelist2=NULL,
genetic.code2=NULL
){
#internal function to fit evalue by length
fitSpline <- function(alnlength, evalue, fit.type, fit.varweight, fit.min){
log10evalue <- -log10(evalue)
log10evalue[is.infinite(log10evalue)] <- 324
x <- cbind(alnlength, log10evalue)
x <- x[order(x[, 1]), ]
x.max <- max(x[, 1])
fitMatrix <- matrix(0, ncol=2, nrow=x.max)
for(i in seq(from=1, to=x.max)){
fitMatrix[i, 1] <- i
s <- round(i * fit.varweight)
if(s < fit.min){s <- fit.min}
smin <- i - s
smax <- i + s
s.idx <- which(x[, 1] >= smin & x[, 1] <= smax)
if(length(s.idx)==0){s.value <- 0}
if(length(s.idx)!=0){
if(fit.type=="mean"){
s.value <- mean(x[s.idx, 2])
}
if(fit.type=="median"){
s.value <- median(x[s.idx, 2])
}
}
if(i==1){
fitMatrix[i, 2] <- s.value
}
if(i > 1){
if(fitMatrix[i - 1, 2] <= s.value){
fitMatrix[i, 2] <- s.value
}
if(fitMatrix[i - 1, 2] > s.value){
fitMatrix[i, 2] <- fitMatrix[i - 1, 2]
}
}
}
fitMatrixfun <- splinefun(fitMatrix[,1], fitMatrix[, 2])
return(fitMatrixfun)
}
if(searchtool=="last"){
if(!dir.exists(lastpath)){
stop("Error: last PATH does not exist. Please specify correct
PATH and/or look into package installation prerequisites.
Try to use make_last() function.")
}
if(!file.exists(paste0(lastpath, "lastdb"))){
stop("Error: lastdb binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites. Try to use make_last() function.")
}
if(!file.exists(paste0(lastpath, "lastal"))){
stop("Error: lastal binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites. Try to use make_last() function.")
}
}
if(searchtool=="mmseqs2"){
if(!dir.exists(mmseqs2path)){
stop("Error: mmseqs2 PATH does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
if(!file.exists(paste0(mmseqs2path, "mmseqs"))){
stop("Error: mmseqs2 binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
}
if(searchtool=="diamond"){
if(!dir.exists(diamondpath)){
stop("Error: diamond PATH does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
if(!file.exists(paste0(diamondpath, "diamond"))){
stop("Error: diamond binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
}
if(searchtool=="lambda3"){
if(!dir.exists(lambda3path)){
stop("Error: lambda3 PATH does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
if(!file.exists(paste0(lambda3path, "lambda3"))){
stop("Error: lambda3 binary does not exist. Please specify
correct PATH and/or look into package installation
prerequisites.")
}
}
selfblast <- FALSE
#suppressWarnings since if length of cds1 and cds2 differ, this will
#raise a warning
if(suppressWarnings(all(cds1==cds2))){
selfblast <- TRUE
}
aa1file <- tempfile("aa1_", outpath)
aa2file <- tempfile("aa2_", outpath)
aa1dbfile <- tempfile("aa1db_", outpath)
aa2dbfile <- tempfile("aa2db_", outpath)
if(!is.null(dbfile1)){
aa1dbfile <- dbfile1
}
if(!is.null(dbfile2)){
aa2dbfile <- dbfile2
}
if(searchtool=="last"){
aa2_aa1_lastout <- tempfile("aa2_aa1_lastout_", outpath)
aa1_aa2_lastout <- tempfile("aa1_aa2_lastout_", outpath)
}
if(searchtool=="mmseqs2"){
aa2_aa1_lastout <- tempfile("aa2_aa1_mmseqs2_", outpath)
aa1_aa2_lastout <- tempfile("aa1_aa2_mmseqs2_", outpath)
}
if(searchtool=="diamond"){
aa2_aa1_lastout <- tempfile("aa2_aa1_diamond_", outpath)
aa1_aa2_lastout <- tempfile("aa1_aa2_diamond_", outpath)
}
if(searchtool=="lambda3"){
aa1file <- tempfile("aa1_", outpath, fileext = ".fa")
aa2file <- tempfile("aa2_", outpath, fileext = ".fa")
aa1dbfile <- tempfile("aa1db_", outpath, fileext = ".lba")
aa2dbfile <- tempfile("aa2db_", outpath, fileext = ".lba")
aa2_aa1_lastout <- tempfile("aa2_aa1_lambda3_", outpath,
fileext = ".m8")
aa1_aa2_lastout <- tempfile("aa1_aa2_lambda3_", outpath,
fileext = ".m8")
}
if(longest.isoform){
Biostrings::writeXStringSet(MSA2dist::cds2aa(isoform2longest(cds1,
isoform.source), shorten=shorten1, frame=frame1,
framelist=framelist1, genetic.code=genetic.code1), file=aa1file)
Biostrings::writeXStringSet(MSA2dist::cds2aa(isoform2longest(cds2,
isoform.source), shorten=shorten2, frame=frame2,
framelist=framelist2, genetic.code=genetic.code2), file=aa2file)
}
if(!longest.isoform){
Biostrings::writeXStringSet(MSA2dist::cds2aa(cds1, shorten=shorten1,
frame=frame1, framelist=framelist1, genetic.code=genetic.code1),
file=aa1file)
Biostrings::writeXStringSet(MSA2dist::cds2aa(cds2, shorten=shorten2,
frame=frame2, framelist=framelist2, genetic.code=genetic.code2),
file=aa2file)
}
if(searchtool=="last"){
system2(command=paste0(lastpath, "lastdb"),
args = c("-p", "-cR01", "-P", threads, aa1dbfile, aa1file))
system2(command=paste0(lastpath, "lastdb"),
args = c("-p", "-cR01", "-P", threads, aa2dbfile, aa2file))
system2(command=paste0(lastpath, "lastal"),
args = c("-f", "BlastTab+", "-P", threads, "-D", lastD, "-m", lastm,
aa1dbfile, aa2file, ">", aa2_aa1_lastout))
system2(command=paste0(lastpath, "lastal"),
args = c("-f", "BlastTab+", "-P", threads, "-D", lastD, "-m", lastm,
aa2dbfile, aa1file, ">", aa1_aa2_lastout))
}
if(searchtool=="mmseqs2"){
system2(command=paste0(mmseqs2path, "mmseqs"),
args = c("easy-search", aa1file, aa2file, aa1_aa2_lastout, outpath,
"--threads", threads, "-s", mmseqs2sensitivity,
"--max-seqs", mmseqs2maxseqs,
"--format-output", paste0("query,target,fident,alnlen,",
"mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,qlen,",
"tlen,raw")))
system2(command=paste0(mmseqs2path, "mmseqs"),
args = c("easy-search", aa2file, aa1file, aa2_aa1_lastout, outpath,
"--threads", threads, "-s", mmseqs2sensitivity,
"--max-seqs", mmseqs2maxseqs,
"--format-output", paste0("query,target,fident,alnlen,",
"mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,qlen,",
"tlen,raw")))
}
if(searchtool=="diamond"){
system2(command=paste0(diamondpath, "diamond"),
args = c("makedb", "--in", aa1file,
"-d", aa1dbfile))
system2(command=paste0(diamondpath, "diamond"),
args = c("makedb", "--in", aa2file,
"-d", aa2dbfile))
system2(command=paste0(diamondpath, "diamond"),
args = c("blastp", "--ignore-warnings", "-d", aa2dbfile,
"-q", aa1file, "-o", aa1_aa2_lastout, diamondsensitivity,
"--max-target-seqs", diamondmaxtargetseqs,
"-f", "6", "qseqid", "sseqid", "pident", "length", "mismatch",
"gapopen", "qstart", "qend", "sstart", "send", "evalue",
"bitscore", "qlen", "slen", "score", "--threads", threads))
system2(command=paste0(diamondpath, "diamond"),
args = c("blastp", "--ignore-warnings", "-d", aa1dbfile,
"-q", aa2file, "-o", aa2_aa1_lastout, diamondsensitivity,
"--max-target-seqs", diamondmaxtargetseqs,
"-f", "6", "qseqid", "sseqid", "pident", "length", "mismatch",
"gapopen", "qstart", "qend", "sstart", "send", "evalue",
"bitscore", "qlen", "slen", "score", "--threads", threads))
}
if(searchtool=="lambda3"){
system2(command=paste0(lambda3path, "lambda3"),
args = c("mkindexp", "-d", aa1file, "-i", aa1dbfile,
"--threads", threads))
system2(command=paste0(lambda3path, "lambda3"),
args = c("mkindexp", "-d", aa2file, "-i", aa2dbfile,
"--threads", threads))
system2(command=paste0(lambda3path, "lambda3"),
args = c("searchp", "-i", aa2dbfile, "-q", aa1file,
"-o", aa1_aa2_lastout, "-p", lambda3sensitivity,
"--num-matches", lambda3nummatches, "--output-columns",
"'std qlen slen score'", "--threads", threads))
system2(command=paste0(lambda3path, "lambda3"),
args = c("searchp", "-i", aa1dbfile, "-q", aa2file,
"-o", aa2_aa1_lastout, "-p", lambda3sensitivity,
"--num-matches", lambda3nummatches, "--output-columns",
"'std qlen slen score'", "--threads", threads))
}
aa1_aa2 <- read.table(aa1_aa2_lastout, sep="\t", header=FALSE,
stringsAsFactors=FALSE)
aa2_aa1 <- read.table(aa2_aa1_lastout, sep="\t", header=FALSE,
stringsAsFactors=FALSE)
colnames(aa1_aa2) <- colnames(aa2_aa1) <- c("query_id", "subject_id",
"perc_identity", "alignment_length", "mismatches", "gap_opens",
"q_start", "q_end", "s_start", "s_end", "evalue", "bit_score",
"query_length", "subject_length", "raw_score")
if(searchtool=="mmseqs2"){
aa1_aa2[, "perc_identity"] <- aa1_aa2[, "perc_identity"] * 100
aa2_aa1[, "perc_identity"] <- aa2_aa1[, "perc_identity"] * 100
}
if(remove){
system2(command="rm", args = aa1file)
system2(command="rm", args = aa2file)
system2(command="rm", args = aa2_aa1_lastout)
system2(command="rm", args = aa1_aa2_lastout)
}
if(remove.db){
system2(command="rm", args = paste0(aa1dbfile, "*"))
system2(command="rm", args = paste0(aa2dbfile, "*"))
}
#selfblast
if(selfblast){
aa1_aa2 <- aa1_aa2[aa1_aa2[, 1]!=aa1_aa2[, 2], , drop=FALSE]
aa2_aa1 <- aa2_aa1[aa2_aa1[, 1]!=aa2_aa1[, 2], , drop=FALSE]
if(dim(aa1_aa2)[1]==0 & dim(aa2_aa1)[1]==0){
stop("No recirpocal best hits!")
}
}
#apply standard filters on hit pairs
aa1_aa2 <- aa1_aa2 %>% filter_eval(eval) %>% filter_qcov(qcov) %>%
filter_tcov(tcov) %>% filter_pident(pident) %>%
filter_alnlen(alnlen)
aa2_aa1 <- aa2_aa1 %>% filter_eval(eval) %>% filter_qcov(qcov) %>%
filter_tcov(tcov) %>% filter_pident(pident) %>%
filter_alnlen(alnlen)
if(rost1999){
aa1_aa2 <- aa1_aa2 %>% filter_rost1999
aa2_aa1 <- aa2_aa1 %>% filter_rost1999
}
#apply additional filters on hit pairs
for(f_ in filter){
aa1_aa2 <- aa1_aa2 %>% f_
aa2_aa1 <- aa2_aa1 %>% f_
}
if(dim(aa1_aa2)[1]==0 & dim(aa2_aa1)[1]==0){
stop("No recirpocal best hits!")
}
aa1_aa2.idx <- paste0(aa1_aa2[, 1], "\t", aa1_aa2[, 2])
aa2_aa1.idx <- paste0(aa2_aa1[, 2], "\t", aa2_aa1[, 1])
#deduplicate hit pairs and only retain the best hit per query
aa1_aa2.dedup <- aa1_aa2[!duplicated(aa1_aa2[, 1]), , drop=FALSE]
aa2_aa1.dedup <- aa2_aa1[!duplicated(aa2_aa1[, 1]), , drop=FALSE]
aa1_aa2.dedup.idx <- paste0(aa1_aa2.dedup[, 1], "\t", aa1_aa2.dedup[, 2])
aa2_aa1.dedup.idx <- paste0(aa2_aa1.dedup[, 2], "\t", aa2_aa1.dedup[, 1])
#reduce to reciprocal best hits
rbh1 <- aa1_aa2.dedup[which(aa1_aa2.dedup.idx %in% aa2_aa1.dedup.idx), ,
drop=FALSE]
rbh2 <- aa2_aa1.dedup[which(aa2_aa1.dedup.idx %in% aa1_aa2.dedup.idx), ,
drop=FALSE]
if(selfblast){
rbh1 <- rbh1[!duplicated(apply(rbh1[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
rbh2 <- rbh2[!duplicated(apply(rbh2[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
}
#if no crbh - done
if(!crbh){
rbh <- rbh1[, seq_len(2)]
rbh <- cbind(rbh, "rbh")
colnames(rbh) <- c("aa1", "aa2", "rbh_class")
out <- list(rbh, cbind(rbh1, "rbh"), cbind(rbh2, "rbh"))
names(out) <- c("crbh.pairs", "crbh1", "crbh2")
if(!selfblast){
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- FALSE
attr(out, "keepSingleDirection") <- FALSE
attr(out, "selfblast") <- selfblast
return(out)
}
if(selfblast){
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- FALSE
attr(out, "keepSingleDirection") <- FALSE
attr(out, "selfblast") <- selfblast
return(out)
}
}
#if crbh - continue
if(crbh){
#fit evalue by length
if(!selfblast){
rbh1_rbh2_fit <- fitSpline(c(rbh1[, 4], rbh2[, 4]),
c(rbh1[, 11], rbh2[, 11]),
fit.type,
fit.varweight,
fit.min)
}
#selfblast
if(selfblast){
rbh1_rbh2_fit <- fitSpline(c(rbh1[, 4]),
c(rbh1[, 11]),
fit.type,
fit.varweight,
fit.min)
}
#internal function to filter hit pairs using rbh1_rbh2_fit
filter_crbh <- function(x){
minuslog10evalue_by_fit <- lapply(as.numeric(x[, 4]), rbh1_rbh2_fit)
return(x[as.numeric(x[, 16]) >= minuslog10evalue_by_fit, ,
drop=FALSE])
}
#remove reciprocal best hits from hit pairs to only look into
#secondary hits
if(!selfblast){
rbh1.idx <- paste0(rbh1[, 1], "\t", rbh1[, 2])
rbh2.idx <- paste0(rbh2[, 2], "\t", rbh2[, 1])
}
if(selfblast){
rbh1.idx <- c(paste0(rbh1[, 1], "\t", rbh1[, 2]),
paste0(rbh1[, 2], "\t", rbh1[, 1]))
rbh2.idx <- c(paste0(rbh2[, 2], "\t", rbh2[, 1]),
paste0(rbh2[, 1], "\t", rbh2[, 2]))
}
aa1_aa2.red <- aa1_aa2[!aa1_aa2.idx %in% rbh1.idx, , drop=FALSE]
aa2_aa1.red <- aa2_aa1[!aa2_aa1.idx %in% rbh2.idx, , drop=FALSE]
#add -log10(evalue)
aa1_aa2.red <- cbind(aa1_aa2.red, -log10(aa1_aa2.red[, 11]))
aa1_aa2.red[is.infinite(aa1_aa2.red[, 16]), 16] <- 324
aa2_aa1.red <- cbind(aa2_aa1.red, -log10(aa2_aa1.red[, 11]))
aa2_aa1.red[is.infinite(aa2_aa1.red[, 16]), 16] <- 324
#filter retained hit pairs with rbh1_rbh2_fit
aa1_aa2.red <- filter_crbh(aa1_aa2.red)
aa2_aa1.red <- filter_crbh(aa2_aa1.red)
if(dim(aa1_aa2.red)[1]!=0){
aa1_aa2.red.idx <- paste0(aa1_aa2.red[, 1], "\t", aa1_aa2.red[, 2])
}
if(dim(aa1_aa2.red)[1]==0){
aa1_aa2.red.idx <- NULL
}
if(dim(aa2_aa1.red)[1]!=0){
aa2_aa1.red.idx <- paste0(aa2_aa1.red[, 2], "\t", aa2_aa1.red[, 1])
}
if(dim(aa2_aa1.red)[1]==0){
aa2_aa1.red.idx <- NULL
}
#deduplicate hit pairs and only retain the best hit per HSP
aa1_aa2.red.dedup <- aa1_aa2.red[!duplicated(aa1_aa2.red.idx), ,
drop=FALSE]
aa2_aa1.red.dedup <- aa2_aa1.red[!duplicated(aa2_aa1.red.idx), ,
drop=FALSE]
#split into reciprocal direction secondary hits (rbh.sec) and single
#direction (single)
if(dim(aa1_aa2.red.dedup)[1]!=0){
aa1_aa2.red.dedup.idx <- paste0(aa1_aa2.red.dedup[, 1], "\t",
aa1_aa2.red.dedup[, 2])
}
if(dim(aa1_aa2.red.dedup)[1]==0){
aa1_aa2.red.dedup.idx <- NULL
}
if(dim(aa2_aa1.red.dedup)[1]!=0){
aa2_aa1.red.dedup.idx <- paste0(aa2_aa1.red.dedup[, 2], "\t",
aa2_aa1.red.dedup[, 1])
}
if(dim(aa2_aa1.red.dedup)[1]==0){
aa2_aa1.red.dedup.idx <- NULL
}
rbh1.sec <- aa1_aa2.red.dedup[which(aa1_aa2.red.dedup.idx %in%
aa2_aa1.red.dedup.idx), , drop=FALSE]
rbh2.sec <- aa2_aa1.red.dedup[which(aa2_aa1.red.dedup.idx %in%
aa1_aa2.red.dedup.idx), , drop=FALSE]
if(selfblast){
rbh1.sec <- rbh1.sec[!duplicated(apply(rbh1.sec[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
rbh2.sec <- rbh2.sec[!duplicated(apply(rbh2.sec[, seq_len(2)], 1,
function(x) paste0(sort(x), collapse="\t"))), , drop=FALSE]
}
single1 <- aa1_aa2.red.dedup[which(!aa1_aa2.red.dedup.idx %in%
aa2_aa1.red.dedup.idx), , drop=FALSE]
single2 <- aa2_aa1.red.dedup[which(!aa2_aa1.red.dedup.idx %in%
aa1_aa2.red.dedup.idx), , drop=FALSE]
#if plotCurve plot fitting
if(plotCurve){
len <- rbh1[, 4]
log10alnlen <- log10(len)
minuslog10evalue <- -log10(rbh1[, 11])
minuslog10evalue[is.infinite(minuslog10evalue)] <- 324
plot(x=log10alnlen, y=minuslog10evalue,
pch=20,
main="Accept / Reject secondary hits as homologs",
ylab="-log10(evalue)",
xlab="log10(alnlength)",
col=col2transparent("#8EBCB5", 50),
cex=0.75)
points(x=log10(rbh1.sec[, 4]), y=-log10(rbh1.sec[, 11]),
pch=21,
bg=col2transparent("#4D83AB", 25),
cex=1)
points(x=log10(single1[, 4]), y=-log10(single1[, 11]),
pch=21,
bg=col2transparent("#CBC106", 25),
cex=1)
if(selfblast){
points(x=log10(seq_len(max(rbh1[, 4]))),
y=rbh1_rbh2_fit(seq(from=1, to=max(rbh1[, 4]))),
type="l",
lwd=2,
col="#9E163C")
legend("bottomright",
legend=c("rbh", "sec", "single"),
col=c("#8EBCB5",
col2transparent("#4D83AB", 25),
col2transparent("#CBC106", 25)),
bty="n",
pch=20)
}
if(!selfblast){
points(x=log10(single2[, 4]), y=-log10(single2[, 11]),
pch=21,
bg=col2transparent("#CB7B26", 25),
cex=1)
points(x=log10(seq_len(max(rbh1[, 4]))),
y=rbh1_rbh2_fit(seq(from=1, to=max(rbh1[, 4]))),
type="l",
lwd=2,
col="#9E163C")
legend("bottomright",
legend=c("rbh", "sec", "single1", "single2"),
col=c("#8EBCB5",
col2transparent("#4D83AB", 25),
col2transparent("#CBC106", 25),
col2transparent("#CB7B26", 25)),
bty="n",
pch=20)
}
}
#if no keepSingleDirection - done
if(!keepSingleDirection){
if(dim(rbh1.sec)[1]!=0){
crbh1 <- data.frame(Map(c ,cbind(rbh1, "rbh"),
cbind(rbh1.sec[, seq_len(15)], "sec")))
}
if(dim(rbh1.sec)[1]==0){
crbh1 <- data.frame(Map(c ,cbind(rbh1, "rbh")))
}
colnames(crbh1)[16] <- "rbh_class"
if(dim(rbh2.sec)[1]!=0){
crbh2 <- data.frame(Map(c ,cbind(rbh2, "rbh"),
cbind(rbh2.sec[, seq_len(15)], "sec")))
}
if(dim(rbh2.sec)[1]==0){
crbh2 <- data.frame(Map(c ,cbind(rbh2, "rbh")))
}
colnames(crbh2)[16] <- "rbh_class"
crbh <- crbh1[, c(seq_len(2), 16)]
colnames(crbh) <- c("aa1", "aa2", "rbh_class")
out <- list(crbh, crbh1, crbh2, rbh1_rbh2_fit)
names(out) <- c("crbh.pairs", "crbh1", "crbh2", "rbh1_rbh2_fit")
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- TRUE
attr(out, "keepSingleDirection") <- FALSE
attr(out, "selfblast") <- selfblast
return(out)
}
#if keepSingleDirection - include single - done
if(keepSingleDirection){
if(dim(rbh1.sec)[1]!=0 & dim(single1)[1]!=0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh"),
cbind(rbh1.sec[, seq_len(15)], "sec"),
cbind(single1[, seq_len(15)], "single")))
}
if(dim(rbh1.sec)[1]!=0 & dim(single1)[1]==0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh"),
cbind(rbh1.sec[, seq_len(15)], "sec")))
}
if(dim(rbh1.sec)[1]==0 & dim(single1)[1]!=0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh"),
cbind(single1[, seq_len(15)], "single")))
}
if(dim(rbh1.sec)[1]==0 & dim(single1)[1]==0){
crbh1 <- data.frame(Map(c, cbind(rbh1, "rbh")))
}
colnames(crbh1)[16] <- "rbh_class"
if(dim(rbh2.sec)[1]!=0 & dim(single2)[1]!=0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh"),
cbind(rbh2.sec[, seq_len(15)], "sec"),
cbind(single2[, seq_len(15)], "single")))
}
if(dim(rbh2.sec)[1]!=0 & dim(single2)[1]==0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh"),
cbind(rbh2.sec[, seq_len(15)], "sec")))
}
if(dim(rbh2.sec)[1]==0 & dim(single2)[1]!=0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh"),
cbind(single2[, seq_len(15)], "single")))
}
if(dim(rbh2.sec)[1]==0 & dim(single2)[1]==0){
crbh2 <- data.frame(Map(c, cbind(rbh2, "rbh")))
}
colnames(crbh2)[16] <- "rbh_class"
crbh <- data.frame(Map(c, crbh1[, c(seq_len(2), 16)],
crbh2[crbh2$rbh_class=="single", , drop=FALSE][, c(2, 1, 16)]))
colnames(crbh) <- c("aa1", "aa2", "rbh_class")
out <- list(crbh, crbh1, crbh2, rbh1_rbh2_fit)
names(out) <- c("crbh.pairs", "crbh1", "crbh2", "rbh1_rbh2_fit")
attr(out, "CRBHits.class") <- "crbh"
attr(out, "crbh") <- TRUE
attr(out, "keepSingleDirection") <- TRUE
attr(out, "selfblast") <- selfblast
return(out)
}
}
}
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