def functionsGoNOW(sampleNames, path, runTrimMetadata, commands): print "\nPerforming quality checks on assemblies." quastList = quastProcesses(sampleNames, path, runTrimMetadata, commands) quastMeta = metadataFiller.filler(runTrimMetadata, quastList) runTrimAssemblyMetadata = quastMetadata(sampleNames, path, quastMeta) jsonReportR.jsonR(sampleNames, path, runTrimAssemblyMetadata, "Collection") return runTrimAssemblyMetadata
def functionsGoNOW(correctedFiles, path, metadata, fLength, commands): """Run the helper function""" print("\nAssembling reads.") flagMetadataList = spadesPrepProcesses(correctedFiles, path, fLength, metadata, commands) flagMetadata = metadataFiller.filler(metadata, flagMetadataList) updatedMetadata = contigFileFormatter(correctedFiles, path, flagMetadata) assembledFiles = completionist(correctedFiles, path) jsonReportR.jsonR(correctedFiles, path, updatedMetadata, "Collection") return updatedMetadata, assembledFiles
def functionsGoNOW(sampleNames, path, runTrimMetadata, commands): """Calls all the functions in a way that they can be multi-processed""" inputData = referenceFiletoAssembly(path, sampleNames) print "\nSampling fastq files." sampleMeta = sampleFastq(path, sampleNames, runTrimMetadata, commands) indexList = indexTargetsProcesses(path, inputData, sampleMeta, commands) indexMeta = metadataFiller.filler(runTrimMetadata, indexList) #Start the mapping operations mappingList = mappingProcesses(path, inputData, indexMeta, commands) mappingMeta = metadataFiller.filler(runTrimMetadata, mappingList) extractingList = extractingProcesses(path, inputData, mappingMeta, commands) extractingMeta = metadataFiller.filler(runTrimMetadata, extractingList) graphingList = graphingProcesses(path, inputData, extractingMeta, commands) graphingMeta = metadataFiller.filler(runTrimMetadata, graphingList) os.chdir(path) runTrimInsertMetadata = formatOutput(path, sampleNames, graphingMeta) jsonReportR.jsonR(sampleNames, path, runTrimInsertMetadata, "Collection") return runTrimInsertMetadata
def functionsGoNow(files, path, metadata, fLength, commands): # print path, fLength commandList = spadesPrepProcesses(files, path, fLength, metadata, commands) commandMetadata = metadataFiller.filler(metadata, commandList) updatedMetadata = contigFileFormatter(files, path, commandMetadata) assembledFiles = completionist(files, path) # moreMetadata = pipelineMetadata(path, updatedMetadata, assembledFiles) jsonReportR.jsonR(files, path, updatedMetadata, "Collection") return updatedMetadata, assembledFiles
def functionsGoNOW(assembledFiles, path, assemblyMetadata, refFilePath, commands): print "\nPerforming GeneSeekr analysis" # Clear out any summary reports from a previous iteration of the pipeline reportRemover(path) # Do everything - uniVec screening, geneSeeking, V-typing, and MLST analysis geneSeekrMetadataList = geneSeekrPrepProcesses(assembledFiles, path, assemblyMetadata, refFilePath, commands) # print json.dumps(geneSeekrMetadata, sort_keys=True, indent=4, separators=(',', ': ')) geneSeekrMetadata = metadataFiller.filler(assemblyMetadata, geneSeekrMetadataList) jsonReportR.jsonR(assembledFiles, path, geneSeekrMetadata, "Collection") return geneSeekrMetadata
def functionsGoNOW(sampleNames, path, runMetadata, fLength, commands): """Run the functions""" print('\nPerforming error correction on fastq files.') # Removed the multiprocessing aspect of this function - it seemed to be unreliable. # Sometimes, fastq files with more data would not be corrected. os.chdir(path) print "Preparing fastq files for processing" prepList = quakePrepProcesses(sampleNames, path, fLength, runMetadata, commands) prepMetadata = metadataFiller.filler(runMetadata, prepList) print "Determining cut-off values for error correction" cutoffList = quakeCutOffProcesses(sampleNames, path, prepMetadata, commands) cutoffMetadata = metadataFiller.filler(prepMetadata, cutoffList) print "Correcting errors" correctList = quakeCorrectProcesses(sampleNames, path, fLength, cutoffMetadata, commands) correctMetadata = metadataFiller.filler(runMetadata, correctList) # runQuake(sampleNames, path) os.chdir(path) # Run completionist to determine unprocessable files, and acquire metadata runTrimMetadata, correctedList = completionist(sampleNames, path, correctMetadata, fLength) # Clean up tmp files tmpFileRemover(path, correctedList) # Return important variables jsonReportR.jsonR(correctedList, path, runTrimMetadata, "Collection") return correctedList, runTrimMetadata