Mercurial > repos > greg > p_chunks
changeset 0:f45c65e3fd18 draft
Uploaded
| author | greg |
|---|---|
| date | Tue, 10 Jan 2023 20:40:45 +0000 |
| parents | |
| children | db50fb3faffc |
| files | .shed.yml macros.xml p_chunks.R p_chunks.xml |
| diffstat | 4 files changed, 716 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/.shed.yml Tue Jan 10 20:40:45 2023 +0000 @@ -0,0 +1,9 @@ +name: p_chunks +owner: greg +description: Annotates plasmids +long_description: Annotates plasmids +categories: +- Sequence Analysis +remote_repository_url: https://github.com/gregvonkuster/galaxy_tools/tree/master/tools/pima/p_chunks +homepage_url: https://github.com/gregvonkuster/galaxy_tools +type: unrestricted
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Tue Jan 10 20:40:45 2023 +0000 @@ -0,0 +1,22 @@ +<macros> + <token name="@TOOL_VERSION@">1.0.0</token> + <token name="@VERSION_SUFFIX@">0</token> + <token name="@PROFILE@">21.01</token> + <xml name="requirements"> + <requirements> + <requirement type="package" version="2.13.0">blast</requirement> + <requirement type="package" version="0.4.7">r-gridbase</requirement> + <requirement type="package" version="2.3">r-gridextra</requirement> + <requirement type="package" version="3.0.1">r-hash</requirement> + <requirement type="package" version="1.7.3">r-optparse</requirement> + <requirement type="package" version="1.32.1">r-parallelly</requirement> + <requirement type="package" version="1.4.1">r-stringr</requirement> + </requirements> + </xml> + <xml name="citations"> + <citations> + <citation type="doi">10.1038/s41598-019-49700-1</citation> + </citations> + </xml> +</macros> +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/p_chunks.R Tue Jan 10 20:40:45 2023 +0000 @@ -0,0 +1,643 @@ +#!/bin/env Rscript + +library(parallel) +library(hash) +library(stringr) +library(grid) +library(gridExtra) +library(optparse) + +options(width = 180) + +printif = function(string = NULL, condition){ + if (condition) { + print(string) + } +} + +findPlasmids = function(plasmidPSLFile = NULL, plasmidDatabase = NULL, + amrPSLFile = NULL, amrDatabase, noAMR = FALSE, + incPSLFile = NULL, incDatabase, noInc = FALSE, + outputDirectory = NA, overwrite = TRUE, + maxTargetLength = 300000, + minQueryLength = 500, + makeCircos = FALSE, + minQueryCoverage = 1/2, minTargetCoverage = 1/2, + searchDepth = NULL, + verbosity = 0) { + + ## Verify the arguments + argumentsGood = TRUE + if (minQueryCoverage < .1 || minQueryCoverage > 1) { + argumentsGood = FALSE + message(paste('Minimum query coverage', minQueryCoverage, 'is outside of the range 0.1 <= x <= 1')) + } + if (minTargetCoverage < 0.02 || minTargetCoverage > 1) { + argumentsGood = FALSE + message(paste('Minimum target coverage', minTargetCoverage, 'is outside of the range 0.1 <= x <= 1')) + } + if (!argumentsGood){ + message('There is a problem with the arguments') + return() + } + + printif(paste('Finding plasmids in', plasmidPSLFile), verbosity > 0) + + ## Keep track of the total score in case we doing a grid search + totalPlasmidScore = 0 + + ## Check for the existence of the output directory, remove if it exists + if (file.exists(outputDirectory)) { + printif(paste('Removing existing output directory', outputDirectory), verbosity > 1) + unlink(outputDirectory, recursive = TRUE) + } + printif(paste('Making output directory', outputDirectory), verbosity > 1) + dir.create(outputDirectory) + outputPrefix = paste0(outputDirectory, "/plasmids") + + ## Read in and filter the plasmid hits + plasmidHits = read.table(plasmidPSLFile, row.names = NULL, header = FALSE, sep = '\t', stringsAsFactors = FALSE, skip = 5) + colnames(plasmidHits) = c('match', 'mismatch', 'rep_m', 'Ns', 'tgap_c', 'tgap_b', + 'qgap_c', 'qgap_b', 'strand', + 'target', 'tlength', 'tstart', 'tstop', + 'query', 'qlength', 'qstart', 'qstop', + 'blocks', 'block_sizes', 'tstarts', 'qstarts') + printif(paste("Sequence-plasmid hits:", nrow(plasmidHits)), verbosity > 0) + + plasmidHits = plasmidHits[order(plasmidHits[,'target'], -plasmidHits[,'qlength']), ] + + ## Toss out any hits missing information + plasmidHits = plasmidHits[complete.cases(plasmidHits),] + + ## Toss out very long plasmid sequences -- probably actually genome chunks labeled incorrectly + veryLongHits = sum(plasmidHits[,'tlength'] >= maxTargetLength) + printif(paste('Removing', veryLongHits, 'hits greater than', maxTargetLength), verbosity > 0) + plasmidHits = plasmidHits[plasmidHits[,'tlength'] <= maxTargetLength, ] + printif(paste("Sequence-plasmid hits after removing very long plasmids:", nrow(plasmidHits)), verbosity > 0) + + ## Toss out very short query sequences -- probably junk or repeats + veryShortQuery = sum(plasmidHits[,'qlength'] >= minQueryLength) + printif(paste('Removing', veryShortQuery, 'queries less than', minQueryLength), verbosity > 0) + plasmidHits = plasmidHits[plasmidHits[,'qlength'] >= minQueryLength, ] + printif(paste("Sequence-plasmid hits after removing very short queries:", nrow(plasmidHits)), verbosity > 0) + + ## Toss out sequece-plasmid pairs below the coverage cutoff + sequenceMatches = aggregate(x = plasmidHits[,'match',drop = FALSE], + by = list(plasmidHits[,'query'], plasmidHits[,'target']), FUN = sum) + printif(head(sequenceMatches), verbosity > 1) + printif(paste('Sequence-plasmid pair matches:', paste(dim(sequenceMatches), collapse = 'x')), verbosity > 1) + + sequenceLengths = aggregate(x = plasmidHits[,'qlength', drop = FALSE], + by = list(plasmidHits[,'query'], plasmidHits[,'target']), FUN = max) + printif(head(sequenceLengths), verbosity > 1) + printif(paste('Sequence-plasmid pair lengths:', paste(dim(sequenceLengths), collapse = 'x')), verbosity > 1) + + matchingFractions = cbind(sequenceMatches[,c(1,2)], sequenceMatches[,3] / sequenceLengths[,3]) + colnames(matchingFractions) = c('query', 'target', 'fraction') + printif(head(matchingFractions), verbosity > 1) + printif(paste('Sequence-plasmid pair fractions:', paste(dim(matchingFractions), collapse = 'x')), verbosity > 1) + + matchingFractions = matchingFractions[matchingFractions[,'fraction'] >= minQueryCoverage,] + printif(head(matchingFractions), verbosity > 1) + printif(paste('Passing sequence-plasmid pair fractions:', paste(dim(matchingFractions), collapse = 'x')), verbosity > 1) + + aboveMinCoverage = apply(matchingFractions, 1, function(i){paste0(i['query'], '|', i['target'])}) + plasmidHits = plasmidHits[apply(plasmidHits, 1, function(i){paste0(i['query'], '|', i['target'])}) %in% aboveMinCoverage, ] + printif(paste("Sequence-plasmid hits after removing low-coverage hits:", nrow(plasmidHits)), verbosity > 0) + + ## Toss out plasmid sequences below the coverage cutoff + targetMatches = aggregate(x = plasmidHits[,'match',drop = FALSE], + by = list(plasmidHits[,'target']), FUN = sum) + printif(head(targetMatches), verbosity > 1) + printif(paste('Plasmid matches:', paste(dim(targetMatches), collapse = 'x')), verbosity > 1) + + targetLengths = aggregate(x = plasmidHits[,'tlength', drop = FALSE], + by = list(plasmidHits[,'target']), FUN = max) + printif(head(targetLengths), verbosity > 1) + printif(paste('Plasmid lengths:', paste(dim(targetLengths), collapse = 'x')), verbosity > 1) + + matchingFractions = cbind(targetMatches[,1], targetMatches[,2] / targetLengths[,2]) + colnames(matchingFractions) = c('target', 'fraction') + printif(head(matchingFractions), verbosity > 1) + printif(paste('Plasmid fractions:', paste(dim(matchingFractions), collapse = 'x')), verbosity > 1) + + matchingFractions = matchingFractions[matchingFractions[,'fraction'] >= minTargetCoverage,] + printif(head(matchingFractions), verbosity > 1) + printif(paste('Passing plasmid fractions:', paste(dim(matchingFractions), collapse = 'x')), verbosity > 1) + + aboveMinCoverage = matchingFractions[, 'target'] + plasmidHits = plasmidHits[plasmidHits[, 'target'] %in% aboveMinCoverage, ] + printif(paste("Sequence-plasmid hits after removing low-coverage hits:", nrow(plasmidHits)), verbosity > 0) + + + ## If we're out of sequece-plasmid hits, then stop here + if (nrow(plasmidHits) == 0) { + message(paste('Not hits found')) + return + } + + ## Find out how much of each query (contig) is covered by each target (plasmid). + ## Query coverage is constant and does not change as we assign contigs to plasmids + queryCoverage = hash() + queryMismatches = hash() + for (i in 1:nrow(plasmidHits)) { + if (!(i %% 1000)) { + printif(paste('Processing hit', i, '/', nrow(plasmidHits)), verbosity > 0) + } + + query = plasmidHits[i,'query'] + target = plasmidHits[i, 'target'] + + ## Represent each sequence-plasmid hit as a series of 0/1 vectors that + if (!has.key(query, queryCoverage)) { + queryCoverage[[query]] = hash() + queryMismatches[[query]] = hash() + } + if (!has.key(target, queryCoverage[[query]])) { + queryCoverage[[query]][[target]] = rep(0, times = plasmidHits[i, 'qlength']) + queryMismatches[[query]][[target]] = 0 + } + + blockSizes = as.numeric(unlist(strsplit(x = plasmidHits[i,'block_sizes'], ','))) + qBlockStarts = as.numeric(unlist(strsplit(x = plasmidHits[i,'qstarts'], ','))) + + for (j in 1:length(blockSizes)) { + queryCoverage[[query]][[target]][qBlockStarts[j]:(qBlockStarts[j]+blockSizes[j])] = 1 + } + queryMismatches[[query]][[target]] = queryMismatches[[query]][[target]] + plasmidHits[i,'mismatch'] + } + + + ## Pull the full plasmid names from the blast database because BLAT/minimap2 doesn't report them, just the ID's + targetIDs = plasmidHits[,'target'] + targetIDs = gsub("\\|$", "", targetIDs) + targetIDs = gsub(".*(\\|.*)$", "\\1", targetIDs) + noDotIDs = gsub("\\|", "", targetIDs) + noDotIDs = gsub("(^H[^.]+).[0-9]+$", "\\1", noDotIDs) + noDotIDs = cbind(noDotIDs) + + targetFile = paste0(outputDirectory, '/targets.tsv', sep = '') + write.table(file = targetFile, x = noDotIDs, quote = FALSE, row.names = FALSE, col.names = FALSE) + command = paste('blastdbcmd -db', plasmidDatabase, + '-entry_batch', targetFile, + '| grep ">"') + targetNames = system(command, intern = TRUE) + printif(paste('Found', length(targetNames), 'target names for', length(targetIDs), 'targets.'), verbosity > 0) + + targetNames = gsub('^>.*\\| ', '', targetNames) + targetNames = gsub('^>[^ ]+', '', targetNames) + plasmidHits = cbind(plasmidHits, targetIDs, targetNames) + printif(paste('Named hits:', nrow(plasmidHits)), verbosity > 1) + + #Pull just the plasmids out of the larget set of hits, i.e, make sure it has the word 'plasmid' in the description. + plasmidHits = plasmidHits[grep('plasmid|vector', plasmidHits[,'targetNames'], ignore.case = TRUE), ,drop = FALSE] + plasmidHits = plasmidHits[!grepl('tig0000|unnamed', plasmidHits[,'targetNames'], ignore.case = TRUE), , drop = FALSE] + printif(paste("Sequece-plasmid hits after screening by name:", paste(dim(plasmidHits), collapse = 'x')), verbosity > 1) + + ## Stop if there is nothing left + if (is.null(plasmidHits)) { + message('Not hits found') + return() + } + if (nrow(plasmidHits) == 0) { + message('Not hits found') + return() + } + + ## Clean up the plasmid names -- they look like crap by default. + plasmidNames = plasmidHits[,'targetNames'] + plasmidNames = gsub(', comp.*', '', plasmidNames) + plasmidNames = gsub(', contig.*', '', plasmidNames) + plasmidNames = gsub(', partial.*', '', plasmidNames) + plasmidNames = gsub('strain ', '', plasmidNames) + plasmidNames = gsub('^ *', '', plasmidNames) + plasmidNames = sub('^(cl\\|)(.*?) ', '', plasmidNames) + plasmidNames = sub('subsp. (.*?) ', '', plasmidNames) + plasmidNames = sub('serovar (.*?) ', '', plasmidNames) + plasmidNames = sub('strain ', '', plasmidNames) + plasmidNames = sub('plasmid$', '', plasmidNames) + plasmidHits[,'targetNames'] = plasmidNames + + ## Just take the best hit for each plasmid, hence the head, 1 in the agg + plasmidNames = aggregate(plasmidHits, by = list(plasmidHits[,'query']), FUN = head, 1) + plasmidNames = plasmidNames[, 'targetNames', drop = FALSE] + + ## Find the set of plasmid coverage hits for each itteration + usedContigs = c() + plasmidMismatches = c() + + ## Order hits by the plasmid ID and the query length + plasmidHits = plasmidHits[order(plasmidHits[,'target'], -plasmidHits[,'qlength']), ] + + ## Iterate, finding plasmids until we run out of usable sequence-plasmid its + plasmidNumber = 0 + plasmidResults = c() + while (1) { + + ## Keep track of how many plasmids we have gone over + plasmidNumber = plasmidNumber + 1 + + printif(paste('Sequence-plasmid hits left:', nrow(plasmidHits)), verbosity > 1) + contigToPlasmid = hash() + plasmidToContig = hash() + plasmidCoverage = hash() + plasmidCoverageWithRepeats = hash() + contigCoverage = hash() + + ##Find contig/plasmid plasmid/contig pairs + if (is.null(plasmidHits)) { + break + } + if (nrow(plasmidHits) == 0) { + break + } + repLengths = c() + + + ## Find the coverage of each plasmid in the possible set by the contigs + for (i in 1:nrow(plasmidHits)) { + + query = plasmidHits[i,'query'] + target = plasmidHits[i,'target'] + matches = plasmidHits[i,'match'] + mismatches = plasmidHits[i,'mismatch'] + score = matches - mismatches + queryLength = plasmidHits[i,'qlength'] + blockSizes = as.numeric(unlist(strsplit(plasmidHits[i, 'block_sizes'], ','))) + queryStarts = as.numeric(unlist(strsplit(plasmidHits[i, 'qstarts'], ','))) + targetStarts = as.numeric(unlist(strsplit(plasmidHits[i, 'tstarts'], ','))) + + ## Skip matches which have less than 50% of the bases from the contig on the plasmid -- probably not a good match + if ((sum(queryCoverage[[query]][[target]]) - queryMismatches[[query]][[target]]) / queryLength <= minQueryCoverage) { + next + } + + targetLength = plasmidHits[i, 'tlength']; targetStart = plasmidHits[i, 'tstart']; targetStop = plasmidHits[i, 'tstop'] + + ## Relate this contig to this plasmid + if (!has.key(query, contigToPlasmid)) { + contigToPlasmid[[query]] = hash() + contigCoverage[[query]] = hash() + } + if (!has.key(target, contigToPlasmid[[query]])) { + contigToPlasmid[[query]][[target]] = score + contigCoverage[[query]][[target]] = rep(0, queryLength) + } else { + contigToPlasmid[[query]][[target]] = contigToPlasmid[[query]][[target]] + score + } + + ## Keep track of target(plasmid) coverage by the contigs + if (!has.key(target, plasmidCoverage)) { + plasmidCoverage[[target]] = rep(0, targetLength) + plasmidCoverageWithRepeats[[target]] = rep(0, targetLength) + plasmidToContig[[target]] = hash() + plasmidMismatches[target] = 0 + } + + penalized = FALSE + for (j in 1:length(blockSizes)) { + + ## Keep track of all contig alignments to this plasmid, even with repeats + plasmidCoverageWithRepeats[[target]][targetStarts[j]:(targetStarts[j] + blockSizes[j])] = 1 + + ## Skip if this region of the query sequence has already been assigned to this plasmid + if (sum(contigCoverage[[query]][[target]][queryStarts[j]:(queryStarts[j] + blockSizes[j])] == 0) <= 50) { + printif(paste('Sequence', query, 'already used for', target, + '. ', paste0(queryStarts[j], '-', queryStarts[j] + blockSizes[j])), verbosity > 2) + next + } + if (!penalized) { + ## Penalty for every gap, only penalize once per match + ## TODO: Penalize for gap length, not just once per gap + #plasmidMismatches[target] = plasmidMismatches[target] + (length(blockSizes) - 1) * 100 + plasmidMismatches[target] = plasmidMismatches[target] + mismatches * 5 + penalized = TRUE + } + + plasmidCoverage[[target]][targetStarts[j]:(targetStarts[j] + blockSizes[j])][contigCoverage[[query]][[target]][queryStarts[j]:(queryStarts[j] + blockSizes[j])] == 0] = + plasmidCoverage[[target]][targetStarts[j]:(targetStarts[j] + blockSizes[j])][contigCoverage[[query]][[target]][queryStarts[j]:(queryStarts[j] + blockSizes[j])] == 0] + 1 + contigCoverage[[query]][[target]][queryStarts[j]:(queryStarts[j] + blockSizes[j])] = 1 + } + + ## Relate this plasmid to this contig + if (!has.key(query, plasmidToContig[[target]])) { + plasmidToContig[[target]][[query]] = score + } else { + plasmidToContig[[target]][[query]] = plasmidToContig[[target]][[query]] + score + } + if (target == 'NZ_GG692894.1' && query == 'contig_3_0') { + print('NZ_GG692894.1') + print(sum(plasmidCoverage[[target]])) + print(sum(contigCoverage[[query]][[target]])) + } + + } + + ## Get the best set of plasmids out, i.e., the set with the most bases matching between the contig and plasmid + plasmidScores = c() + for (thisPlasmid in keys(plasmidCoverage)){ + thisPlasmidScore = sum(plasmidCoverage[[thisPlasmid]]) + plasmidScores = c(plasmidScores, thisPlasmidScore) + names(plasmidScores)[length(plasmidScores)] = thisPlasmid + } + plasmidScores = sort(plasmidScores - plasmidMismatches[names(plasmidScores)], dec = TRUE) + + if (length(plasmidScores) > 0) { + printif('Highest scoring plasmids', verbosity > 1) + printif(head(cbind(plasmidScores), 20), verbosity > 1) + } + + ## Stop searching for plasmids if nothing matches well or we're out of hits + if (length(plasmidScores) == 0) { + printif('Out of plasmids', verbosity > 0) + break + } else if (max(plasmidScores) < 500) { + printif('Out of min-scoring plasmids', verbosity > 0) + break + } + + ## For each matching plasmid, ordered by total bases matching the assembly, find the set of corresponding contigs + plasmidToUse = 1 + if (!is.null(searchDepth) && plasmidNumber <= length(searchDepth)) { + plasmidToUse = searchDepth[plasmidNumber] + } + if (plasmidToUse > length(plasmidScores)) { + plasmidToUse = length(plasmidScores) + } + + plasmid = names(plasmidScores)[plasmidToUse] + print(paste('Plasmid picked', plasmid)) + totalPlasmidScore = totalPlasmidScore + plasmidScores[plasmid] + printif(paste("Pulling sequences for", plasmid), verbosity > 0) + + ## Find contigs what haven't already been given to another plasmid so we can assign them next round + plasmidContigs = keys(plasmidToContig[[plasmid]]) + unusedContigs = plasmidContigs[!(plasmidContigs %in% usedContigs)] + + ## If no unused contigs that also map to this plasmid then skip it + if (length(unusedContigs) == 0) { + printif(paste("No unused sequences for", plasmid), verbosity > 1) + next + } + + ## Keep just the rows for this plasmid and which haven't already been used by another plasmid + plasmidRows = plasmidHits[plasmidHits[,'target'] == plasmid,] + plasmidRows = plasmidRows[plasmidRows[,'query'] %in% unusedContigs,,drop = FALSE] + plasmidName = plasmidRows[1, 'targetNames'] + plasmidID = plasmidRows[1, 'targetIDs'] + ## Get the plasmid length + command = paste('blastdbcmd -db', plasmidDatabase, + '-entry', plasmidID, + '-outfmt "%l"') + plasmidLength = system(command, intern = TRUE) + plasmidLength = rep(plasmidLength, nrow(plasmidRows)) + + ## How many bases from the plasmid are uncovered? + plasmidMissing = rep(sum(plasmidCoverageWithRepeats[[as.character(plasmidID)]] == 0), nrow(plasmidRows)) + + ## Keep track of all of the contigs included + usedContigs = c(usedContigs, unusedContigs) + + ## How many matching bases for each query sequence? + thisPlasmidQuerySizes = c() + thisPlasmidMatches = c() + for (contig in unusedContigs) { + thisPlasmidQuerySizes = c(thisPlasmidQuerySizes, length(queryCoverage[[contig]][[plasmid]])) + thisPlasmidMatches = c(thisPlasmidMatches, sum(queryCoverage[[contig]][[plasmid]])) + } + + ## Add this plasmid's hits onto the growing list of sequence-plasmid hits + thisPlasmidResults = cbind(unusedContigs, plasmidName, as.character(plasmidID), thisPlasmidQuerySizes, thisPlasmidMatches, plasmidLength, plasmidMissing) + colnames(thisPlasmidResults) = c('query.name', 'plasmid.name', 'plasmid.accession', 'query.size', 'aligned.bases', 'plasmid.size', 'plasmid.missing') + thisPlasmidResults = thisPlasmidResults[order(-thisPlasmidMatches), ] + plasmidResults = rbind(plasmidResults, thisPlasmidResults) + + ## Remove the contigs added to this plasmid from the list of plasmid/contig BLAT hits + plasmidHits = plasmidHits[!(plasmidHits[,'query'] %in% usedContigs),] + plasmidHits = plasmidHits[!(plasmidHits[,'target'] == plasmid),] + } + + rownames(plasmidResults) = plasmidResults[,1] + + ## Check for the presence of AMR genes in this file + if (!noAMR) { + amrBEDFile = paste0(outputDirectory, '/amrMapping.bed') + command = paste('cat', amrPSLFile, + '| awk -F \'\\t\' \'($3 >= 80) && ($4 / $14 >= .95){OFS = "\t"; print $2,($9 < $10 ? $9 : $10),($9 < $10 ? $10 : $9),$1,$3/100,($9 < $10 ? "+" : "-")}\'', + '| sort -k 1,1 -k 2,2n >', amrBEDFile) + printif(command, verbosity > 1) + system(command) + ## Find local overlapping regions + amrMergedBEDFile = paste0(outputDirectory, '/amrMergedMapping.bed') + command = paste('bedtools merge -d -30 -i', amrBEDFile, '>', amrMergedBEDFile) + printif(command, verbosity > 1) + system(command) + ## Find the best AMR gene for each region + amrFinalBEDFile = paste0(outputDirectory, '/amrFinal.bed') + command = paste('bedtools intersect', + '-a', amrBEDFile, + '-b', amrMergedBEDFile, + '-f .9 -F .9', + '-wao', + '| awk \'$7 != "."\'', + '| awk \'{OFS="\t";locus=$7"\t"$8"\t"$9; if($5 > s[locus]){s[locus]=$5;b[locus] = $1"\t"$2"\t"$3"\t"$4"\t"$5"\t"$6}}END{for(i in b){print i,b[i]}}\'', + '>', amrFinalBEDFile) + printif(command, verbosity > 1) + system(command) + + ## Read the AMR results in and add them to the plasmid contigs + amrResults = read.table(file = amrFinalBEDFile, header = FALSE, row.names = NULL, stringsAsFactors = FALSE, quote = '') + amrResults[,7] = gsub('(_.*$)|(.*\\|)', '', amrResults[,7]) + amrResults = aggregate(amrResults[ , 7, drop = FALSE], by = list(amrResults[,1]), function(i){paste(i, collapse = ', ')}) + rownames(amrResults) = amrResults[,1] + amrResults = amrResults[ , 2, drop = FALSE] + print(amrResults) + + plasmidResults = cbind(plasmidResults, rep('', nrow(plasmidResults))) + colnames(plasmidResults)[ncol(plasmidResults)] = 'amr' + plasmidResults[rownames(plasmidResults) %in% rownames(amrResults), 'amr'] = + amrResults[rownames(plasmidResults)[rownames(plasmidResults) %in% rownames(amrResults)], 1] + + } + + ## Check for the presence of incompatibility groups in this file + if (!noInc) { + incBEDFile = paste0(outputDirectory, '/incMapping.bed') + command = paste('cat', incPSLFile, + '| awk -F \'\\t\' \'($3 >= 80) && ($4 / $14 >= .95){OFS = "\t"; print $2,($9 < $10 ? $9 : $10),($9 < $10 ? $10 : $9),$1,$3/100,($9 < $10 ? "+" : "-")}\'', + '| sort -k 1,1 -k 2,2n >', incBEDFile) + printif(command, verbosity > 1) + system(command) + ## Find local overlapping regions + incMergedBEDFile = paste0(outputDirectory, '/incMergedMapping.bed') + command = paste('bedtools merge -d -30 -i', incBEDFile, '>', incMergedBEDFile) + printif(command, verbosity > 1) + system(command) + ## Find the best INC group for each region + incFinalBEDFile = paste0(outputDirectory, '/incFinal.bed') + command = paste('bedtools intersect', + '-a', incBEDFile, + '-b', incMergedBEDFile, + '-f .9 -F .9', + '-wao', + '| awk \'$7 != "."\'', + '| awk \'{OFS="\t";locus=$7"\t"$8"\t"$9; if($5 > s[locus]){s[locus]=$5;b[locus] = $1"\t"$2"\t"$3"\t"$4"\t"$5"\t"$6}}END{for(i in b){print i,b[i]}}\'', + '>', incFinalBEDFile) + printif(command, verbosity > 1) + system(command) + + ## Read the inc group results in and add them to the plasmid contigs + incResults = read.table(file = incFinalBEDFile, header = FALSE, row.names = NULL, stringsAsFactors = FALSE, quote = '') + incResults[,7] = gsub('(_.*$)|(.*\\|)', '', incResults[,7]) + incResults = aggregate(incResults[ , 7, drop = FALSE], by = list(incResults[,1]), function(i){paste(i, collapse = ', ')}) + rownames(incResults) = incResults[,1] + incResults = incResults[ , 2, drop = FALSE] + print(incResults) + + plasmidResults = cbind(plasmidResults, rep('', nrow(plasmidResults))) + colnames(plasmidResults)[ncol(plasmidResults)] = 'inc' + plasmidResults[rownames(plasmidResults) %in% rownames(incResults), 'inc'] = + incResults[rownames(plasmidResults)[rownames(plasmidResults) %in% rownames(incResults)], 1] + } + + ## Write the plasmid results to file + plasmidChunksFile = paste0(outputDirectory, '/plasmids.tsv') + write.table(file = plasmidChunksFile, x = plasmidResults, quote = FALSE, sep = '\t', row.names = FALSE, col.names = TRUE) + + ## Dump a sequence file of potential plasmid contigs + plasmidSequenceFile = paste0(outputPrefix, '.fna') + system(paste0('echo "" >', plasmidSequenceFile)) + for (contig in plasmidResults[,'query.name']) { + command = paste('faidx', paste0('assembly.fasta'), contig, '>>', plasmidSequenceFile) + print(command) + #system(command) + } + + + ## Return the total score of this round, in case we are doing a search + return(totalPlasmidScore) + +} + +pChunks = function(plasmidPSLFile = NULL, plasmidDatabase = NULL, + amrPSLFile = NULL, amrDatabase, noAMR = FALSE, + incPSLFile = NULL, incDatabase, noInc = FALSE, + outputDirectory = NA, overwrite = TRUE, + maxTargetLength = 300000, + minQueryLength = 200, + makeCircos = FALSE, + minQueryCoverage = 1/2, minTargetCoverage = 1/2, + searchDepth = c(1), + threads = 1, + verbosity = 2) { + + print(plasmidDatabase) + + ## Verify the arguments + argumentsGood = TRUE + if (!file.exists(plasmidPSLFile)) { + argumentsGood = FALSE + message(paste('Plasmid PSL file', plasmidPSLFile, 'not found')) + } + if (is.na(outputDirectory)) { + argumentsGood = FALSE + message('Output directory not given') + } + if (file.exists(outputDirectory) && !overwrite) { + argumentsGood = FALSE + message(paste('Output directory', outputDirectory, 'already exists. Add overwrite = TRUE')) + } + if (minQueryCoverage < .1 || minQueryCoverage > 1) { + argumentsGood = FALSE + message(paste('Minimum query coverage', minQueryCoverage, 'is outside of the range 0.1 <= x <= 1')) + } + if (minTargetCoverage < 0.02 || minTargetCoverage > 1) { + argumentsGood = FALSE + message(paste('Minimum target coverage', minTargetCoverage, 'is outside of the range 0.1 <= x <= 1')) + } + if (!argumentsGood){ + message('There is a problem with the arguments') + return() + } + + ## Check for the existence of the output directory, remove if it exists + if (file.exists(outputDirectory)) { + printif(paste('Removing existing output directory', outputDirectory), verbosity > 1) + unlink(outputDirectory, recursive = TRUE) + } + printif(paste('Making output directory', outputDirectory), verbosity > 1) + dir.create(outputDirectory) + + ## Default to c(1) for the plasmid search depth + searchDepths = lapply(searchDepth, function(i){seq(i, 1)}) + searchDepths = as.matrix(expand.grid(searchDepths)) + print(searchDepths) + + plasmidScores = mclapply(1:nrow(searchDepths), function(i) { + findPlasmids(plasmidPSLFile = plasmidPSLFile, plasmidDatabase = plasmidDatabase, + amrPSLFile = amrPSLFile, amrDatabase, noAMR = noAMR, + incPSLFile = incPSLFile, incDatabase, noInc = noInc, + outputDirectory = paste0(outputDirectory, '/plasmids_', paste(searchDepths[i,], collapse = '_')), overwrite = overwrite, + maxTargetLength = 300000, + minQueryLength = 200, + makeCircos = makeCircos, + minQueryCoverage = 1/2, minTargetCoverage = 1/2, + searchDepth = searchDepths[i,], ## Search depth i + verbosity = verbosity) + }, + mc.cores = threads) + plasmidScores = unlist(plasmidScores) + + print(cbind(searchDepths, plasmidScores)) + + ## Pick out the best set, penalizing for not taking the first + penalties = (unlist(apply(searchDepths, 1, sum)) - ncol(searchDepths)) * 2500 + print(penalties) + plasmidScores = plasmidScores - penalties + print(cbind(searchDepths, plasmidScores)) + bestScoring = which.max(plasmidScores) + bestScoringDirectory = paste0(outputDirectory, '/plasmids_', paste(searchDepths[bestScoring,], collapse = '_')) + + ## Link to the best scoring files + files = c('plasmids.tsv', 'amrFinal.bed') + commands = paste('ln -s ', paste0('"', bestScoringDirectory, '/', files, '"'), + paste0(outputDirectory, '/', files)) + printif(commands, verbosity >= 2) + lapply(commands, system) + +} + + +optionList = list( + make_option('--plasmid_psl', type = 'character', default = NULL, + help = 'Plasmid PSL database-v-contig output', metavar = '<PSL_FILE>'), + make_option('--plasmid_database', type = 'character', default = NULL, + help = 'Plasmid database', metavar = '<PLASMID_FASTA>'), + make_option('--amr_database', type = 'character', default = NULL, + help = 'AMR database', metavar = '<AMR_FASTA>'), + make_option('--amr_blast', type = 'character', default = NULL, + help = 'AMR blast output', metavar = '<BLAST_6>'), + make_option('--output', type = 'character', default = NULL, + help = 'Output dir', metavar = '<OUTPUT_DIR>'), + make_option('--threads', type = 'numeric', default = NULL, + help = 'Output dir', metavar = '<OUTPUT_DIR>'), + make_option('--no_amr', action = 'store_true', default = FALSE, + help = 'Don\'t run AMR'), + make_option('--no_inc', action = 'store_true', default = FALSE, + help = 'Don\'t run incompatibility groups') + ) + +optParser = OptionParser(option_list = optionList) +opt = parse_args(optParser) +print(opt) +pChunks(plasmidPSLFile = opt$'plasmid_psl', plasmidDatabase = opt$'plasmid_database', + amrPSLFile = opt$'amr_blast', amrDatabase = opt$'amr_database', + outputDirectory = opt$output, + threads = opt$threads, +# searchDepth = c(1,1), + searchDepth = c(5,5), + noAMR = TRUE, noInc = TRUE, + verbosity = 2) + + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/p_chunks.xml Tue Jan 10 20:40:45 2023 +0000 @@ -0,0 +1,42 @@ +<tool id="p_chunks" name="p_chunks" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> + <description></description> + <macros> + <import>macros.xml</import> + </macros> + <expand macro="requirements"/> + <command detect_errors="exit_code"><![CDATA[ +#import os + +#set plasmid_db_name = $os.path.join($plasmid_database.extra_files_path, 'blastdb') + +mkdir 'output_dir' && + +export BLASTDB='$plasmid_database.extra_files_path' && +Rscript '${__tool_directory__}/p_chunks.R' +--plasmid_psl '$plasmid_psl' +--plasmid_database '$plasmid_db_name' +--no_amr +--no_inc +--output 'output_dir' +--threads \${GALAXY_SLOTS:-4} +&& cat `readlink output_dir/plasmids.tsv` > '$output_plasmids' + ]]></command> + <inputs> + <param argument="--plasmid_psl" type="data" format="psl" label="PSL file"/> + <param argument="--plasmid_database" type="data" format="blastdbn" label="BLAST database of the plasmid sequences" help="Plasmid sequences are typically contianed in file named plasmids_and_vectors.fasta"/> + </inputs> + <outputs> + <data name="output_plasmids" format="tsv" label="${tool.name} on ${on_string} (plasmids)"/> + </outputs> + <tests> + <!-- Tests are not possible due to file size requirements --> + </tests> + <help> +**What it does** + +Accepts a PSL file and a BLAST database of the associated plasmid sequences and produces a tabular file containing query name, +plasmid name, plasmid accession, query size, aligned bases, plasmid size and missing plasmids. + </help> + <expand macro="citations"/> +</tool> +