Merge pull request #136 from Nesvilab/dev

restoring the pipeline functions

Changelog

@@ -1,11 +1,5 @@
 ### Added
-- Added keepold flag for PTMProphet.
-
 ### Changed
-- Philosopher will ignore the interact file when interact.mod is present.
-- Improved quantification mapping to all runs. The  --mapmods option is only necessary to print mod reports.
-- The number of tryptic ternmini is now determined by ProteinProphet.
 
 ### Fixed
-- Error preventing iTRAQ quantification.
-- Several formatting, typoes and Go-Vet issues were fixed.
+- Pipeline functions were restored.

Makefile

@@ -6,7 +6,7 @@ BINARY = philosopher
 VERSION = $(shell date +%Y%m%d)
 BUILD = $(shell  date +%Y%m%d%H%M)
 
-TAG = v3.2.4
+TAG = v3.2.5
 
 LDFLAGS = -ldflags "-w -s -X main.version=${TAG} -X main.build=${BUILD}"
 

cmd/pipeline.go

@@ -10,6 +10,7 @@ import (
 	"philosopher/lib/met"
 	"philosopher/lib/msg"
 	"philosopher/lib/pip"
+	"philosopher/lib/sla"
 	"philosopher/lib/sys"
 
 	"github.com/sirupsen/logrus"
@@ -77,34 +78,42 @@ var pipelineCmd = &cobra.Command{
 			meta = pip.DatabaseSearch(meta, p, dir, args)
 		}
 
-		// PeptideProphet - PTMProphet - ProteinProphet
-		if p.PeptideProphet.Concurrent == true {
-			meta = pip.ParallelProphets(meta, p, dir, args)
-		} else {
-			meta = pip.Prophets(meta, p, dir, args)
+		// PeptideProphet
+		if p.Commands.PeptideProphet == "yes" {
+			meta = pip.PeptideProphet(meta, p, dir, args)
+		}
+
+		// PTMProphet
+		if p.Commands.PTMProphet == "yes" {
+			meta = pip.PTMProphet(meta, p, dir, args)
+		}
+
+		// ProteinProphet
+		if p.Commands.ProteinProphet == "yes" {
+			meta = pip.ProteinProphet(meta, p, dir, args)
 		}
 
 		// Abacus - combined pepxml
-		//meta = pip.CombinedPeptideList(meta, p, dir, args)
+		meta = pip.CombinedPeptideList(meta, p, dir, args)
 
 		// Abacus - combined protxml
-		//meta = pip.CombinedProteinList(meta, p, dir, args)
+		meta = pip.CombinedProteinList(meta, p, dir, args)
 
 		// Filter - Quantification - Clustering - Report
-		//meta = pip.FilterQuantifyReport(meta, p, dir, args)
+		meta = pip.FilterQuantifyReport(meta, p, dir, args)
 
 		// Abacus
-		//meta = pip.Abacus(meta, p, dir, args)
+		meta = pip.Abacus(meta, p, dir, args)
 
 		// TMT-Integrator
-		//meta = pip.TMTIntegrator(meta, p, dir, args)
+		meta = pip.TMTIntegrator(meta, p, dir, args)
 
 		// Backup and Clean
 		//pip.BackupAndClean(meta, p, dir, Version, Build, args)
 
-		// if len(p.SlackToken) > 0 {
-		// 	sla.Run("Philosopher", p.SlackToken, "Philosopher pipeline is done", p.SlackChannel, p.SlackUserID)
-		// }
+		if len(p.SlackToken) > 0 {
+			sla.Run("Philosopher", p.SlackToken, "Philosopher pipeline is done", p.SlackChannel, p.SlackUserID)
+		}
 
 		met.CleanTemp(meta.Temp)
 

lib/pip/pip.go

@@ -273,95 +273,161 @@ func Prophets(meta met.Data, p Directives, dir string, data []string) met.Data {
 	return meta
 }
 
-// ParallelProphets execute the TPP Prophets
-func ParallelProphets(meta met.Data, p Directives, dir string, data []string) met.Data {
+// PeptideProphet executes PeptideProphet in Parallel mode
+func PeptideProphet(meta met.Data, p Directives, dir string, data []string) met.Data {
 
-	var wg sync.WaitGroup
-	wg.Add(len(data))
+	if p.PeptideProphet.Concurrent == false {
+		for _, i := range data {
 
-	meta.Restore(sys.Meta())
-	meta.Database = p.Database
+			logrus.Info("Running the validation and inference on ", i)
 
-	if p.Commands.PeptideProphet == "yes" || p.Commands.ProteinProphet == "yes" || p.Commands.PTMProphet == "yes" {
+			// getting inside de the dataset folder
+			dsAbs, _ := filepath.Abs(i)
+			os.Chdir(dsAbs)
 
-		if p.Commands.PeptideProphet == "yes" {
-			for _, ds := range data {
+			// // reload the meta data
+			meta.Restore(sys.Meta())
 
-				db := p.Database.Annot
+			// PeptideProphet
+			if p.Commands.PeptideProphet == "yes" {
+				logrus.Info("Executing PeptideProphet on ", i)
+				meta.PeptideProphet = p.PeptideProphet
+				meta.PeptideProphet.Database = p.Database.Annot
+				meta.PeptideProphet.Decoy = p.Database.Tag
+				meta.PeptideProphet.Output = "interact"
+				meta.PeptideProphet.Combine = true
+				gobExt := fmt.Sprintf("*.%s", p.PeptideProphet.FileExtension)
+				files, e := filepath.Glob(gobExt)
+				if e != nil {
+					msg.Custom(e, "fatal")
+				}
+				peptideprophet.Run(meta, files)
+				meta.Serialize()
+			}
 
-				go func(ds, db string) {
-					defer wg.Done()
+			// return to the top level directory
+			os.Chdir(dir)
+		}
+	} else {
 
-					logrus.Info("Running the validation and inference on ", ds)
+		var wg sync.WaitGroup
+		wg.Add(len(data))
 
-					// getting inside de the dataset folder
-					dsAbs, _ := filepath.Abs(ds)
-					absMeta := fmt.Sprintf("%s%s%s", dsAbs, string(filepath.Separator), sys.Meta())
+		meta.Restore(sys.Meta())
+		meta.Database = p.Database
 
-					// reload the meta data
-					meta.Restore(absMeta)
+		for _, ds := range data {
 
-					// PeptideProphet
-					logrus.Info("Executing PeptideProphet on ", ds)
-					meta.PeptideProphet = p.PeptideProphet
-					meta.PeptideProphet.Database = p.Database.Annot
-					meta.PeptideProphet.Decoy = p.Database.Tag
-					meta.PeptideProphet.Output = "interact"
-					meta.PeptideProphet.Combine = true
+			db := p.Database.Annot
 
-					gobExt := fmt.Sprintf("%s%s*.%s", dsAbs, string(filepath.Separator), p.PeptideProphet.FileExtension)
+			go func(ds, db string) {
+				defer wg.Done()
 
-					files, e := filepath.Glob(gobExt)
-					if e != nil {
-						msg.Custom(e, "fatal")
-					}
+				logrus.Info("Running the validation and inference on ", ds)
 
-					peptideprophet.Run(meta, files)
+				// getting inside de the dataset folder
+				dsAbs, _ := filepath.Abs(ds)
+				absMeta := fmt.Sprintf("%s%s%s", dsAbs, string(filepath.Separator), sys.Meta())
 
-					// give a chance to the execution to untangle the output
-					time.Sleep(time.Second * 1)
+				// reload the meta data
+				meta.Restore(absMeta)
 
-				}(ds, db)
-			}
+				// PeptideProphet
+				logrus.Info("Executing PeptideProphet on ", ds)
+				meta.PeptideProphet = p.PeptideProphet
+				meta.PeptideProphet.Database = p.Database.Annot
+				meta.PeptideProphet.Decoy = p.Database.Tag
+				meta.PeptideProphet.Output = "interact"
+				meta.PeptideProphet.Combine = true
 
-			wg.Wait()
+				gobExt := fmt.Sprintf("%s%s*.%s", dsAbs, string(filepath.Separator), p.PeptideProphet.FileExtension)
+
+				files, e := filepath.Glob(gobExt)
+				if e != nil {
+					msg.Custom(e, "fatal")
+				}
+
+				peptideprophet.Run(meta, files)
+
+				// give a chance to the execution to untangle the output
+				time.Sleep(time.Second * 1)
+
+			}(ds, db)
 		}
 
-		// 	// PTMProphet
-		// 	if p.Commands.PTMProphet == "yes" {
-		// 		logrus.Info("Executing PTMProphet on ", i)
-		// 		meta.PTMProphet = p.PTMProphet
-		// 		var files []string
-		// 		files = append(files, "interact.pep.xml")
-		// 		meta.PTMProphet.InputFiles = files
-		// 		ptmprophet.Run(meta, files)
-		// 		meta.Serialize()
-		// 	}
-
-		// 	// ProteinProphet
-		// 	if p.Commands.ProteinProphet == "yes" {
-		// 		logrus.Info("Executing ProteinProphet on ", i)
-		// 		meta.ProteinProphet = p.ProteinProphet
-		// 		meta.ProteinProphet.Output = "interact"
-		// 		var files []string
-		// 		if p.Commands.PTMProphet == "yes" {
-		// 			files = append(files, "interact.mod.pep.xml")
-		// 		} else {
-		// 			files = append(files, "interact.pep.xml")
-		// 		}
-		// 		proteinprophet.Run(meta, files)
-		// 		meta.Serialize()
-		// 	}
+		wg.Wait()
+	}
 
-		// return to the top level directory
-		//os.Chdir(dir)
+	os.Chdir(dir)
+
+	return meta
+}
+
+// PTMProphet execute the TPP PTMProphet
+func PTMProphet(meta met.Data, p Directives, dir string, data []string) met.Data {
+
+	for _, i := range data {
+
+		logrus.Info("Running the validation and inference on ", i)
+
+		// getting inside de the dataset folder
+		dsAbs, _ := filepath.Abs(i)
+		os.Chdir(dsAbs)
 
 		// reload the meta data
-		//meta.Restore(sys.Meta())
-		// /}
+		meta.Restore(sys.Meta())
+
+		// PTMProphet
+		if p.Commands.PTMProphet == "yes" {
+			logrus.Info("Executing PTMProphet on ", i)
+			meta.PTMProphet = p.PTMProphet
+			var files []string
+			files = append(files, "interact.pep.xml")
+			meta.PTMProphet.InputFiles = files
+			ptmprophet.Run(meta, files)
+			meta.Serialize()
+		}
+
+		// return to the top level directory
+		os.Chdir(dir)
 	}
 
-	os.Chdir(dir)
+	return meta
+}
+
+// ProteinProphet execute the TPP ProteinProphet
+func ProteinProphet(meta met.Data, p Directives, dir string, data []string) met.Data {
+
+	for _, i := range data {
+
+		logrus.Info("Running the validation and inference on ", i)
+
+		// getting inside de the dataset folder
+		dsAbs, _ := filepath.Abs(i)
+		os.Chdir(dsAbs)
+
+		// reload the meta data
+		meta.Restore(sys.Meta())
+
+		// ProteinProphet
+		if p.Commands.ProteinProphet == "yes" {
+			logrus.Info("Executing ProteinProphet on ", i)
+			meta.ProteinProphet = p.ProteinProphet
+			meta.ProteinProphet.Output = "interact"
+			var files []string
+			if p.Commands.PTMProphet == "yes" {
+				files = append(files, "interact.mod.pep.xml")
+			} else {
+				files = append(files, "interact.pep.xml")
+			}
+			proteinprophet.Run(meta, files)
+			meta.Serialize()
+			met.CleanTemp(meta.Temp)
+		}
+
+		// return to the top level directory
+		os.Chdir(dir)
+	}
 
 	return meta
 }

philosopher.yml

@@ -257,7 +257,7 @@ abacus:
   uniqueOnly: false                            # report TMT quantification based on only unique peptides
   reprint: false                               # create abacus reports using the Reprint format
 
-tmtintegrator:                                 # v1.1.8
+tmtintegrator:                                 # v1.1.10
   path:                                        # path to TMT-Integrator jar
   memory: 6                                    # memory allocation, in Gb
   output:                                      # the location of output files
@@ -282,4 +282,5 @@ tmtintegrator:                                 # v1.1.8
   top3_pep: true                               # use top 3 most intense peptide ions as part of the reference sample abundance estimation
   print_RefInt: false                          # print individual reference sample abundance estimates for each multiplex in the final reports (in addition to the combined reference sample abundance estimate)
   add_Ref: -1                                  # add an artificial reference channel if there is no reference channel (-1: don't add the reference; 0: use summation as the reference; 1: use average as the reference; 2: use median as the reference)
-  max_pep_prob_thres: 0                        # the threshold for maximum peptide probability
+  max_pep_prob_thres: 0                        # the threshold for maximum peptide probability
+  min_ntt: 0                                   # minimum allowed number of enzymatic termini