changeset 0:4bef80b09854 draft default tip

"planemo upload commit 498440b547e1feaa6a81764b55ac8208626d70a8"

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/msms_extractor.py	Tue Oct 29 11:09:46 2019 -0400
@@ -0,0 +1,148 @@
+# 
+# Developed by Praveen Kumar
+# Galaxy-P Team (Griffin's Lab)
+# University of Minnesota
+#
+#
+#
+
+
+from pyteomics import mzml
+import os
+import sys
+import shutil
+import subprocess
+import re
+import pandas as pd
+from operator import itemgetter
+from itertools import groupby
+import random
+import argparse
+
+def main():
+    if len(sys.argv) >= 7:
+        parser = argparse.ArgumentParser()
+        parser.add_argument("msms", help="mzML File")
+        parser.add_argument("psm", help="PSM Report File")
+        parser.add_argument("out", help="Output filename")
+        parser.add_argument("filestring", help="MSMS File string as identifier")
+        parser.add_argument("remove_retain", help="Remove scans reported in the PSM report")
+        parser.add_argument("random", help="Random MSMS scans used with to use with --retain (default=0)", default=0)
+        args = parser.parse_args()
+        # Start of Reading Scans from PSM file
+        # Creating dictionary of PSM file: key = filename key = list of scan numbers
+        
+        # removeORretain = sys.argv[5].strip()
+        # randomScans = int(sys.argv[6].strip())
+        
+        removeORretain = args.remove_retain
+        randomScans = int(args.random)
+        
+        
+        # ScanFile = sys.argv[2]
+        ScanFile = args.psm
+        spectrumTitleList = list(pd.read_csv(ScanFile, "\t")['Spectrum Title'])
+        scanFileNumber = [[".".join(each.split(".")[:-3]), int(each.split(".")[-2:-1][0])] for each in spectrumTitleList]
+        scanDict = {}
+        for each in scanFileNumber:
+            if each[0] in scanDict.keys():
+                scanDict[each[0]].append(int(each[1]))
+            else:
+                scanDict[each[0]] = [int(each[1])]
+        # End of Reading Scans from PSM file
+        
+        # inputPath = sys.argv[1]
+        inputPath = args.msms
+        ##outPath = "/".join(sys.argv[3].split("/")[:-1])
+        # outPath = sys.argv[3]
+        outPath = args.out
+        ##outFile = sys.argv[3].split("/")[-1]
+        allScanList = []
+        # Read all scan numbers using indexedmzML/indexList/index/offset tags
+        for k in mzml.read(inputPath).iterfind('indexedmzML/indexList/index/offset'):
+            if re.search("scan=(\d+)", k['idRef']):
+                a = re.search("scan=(\d+)", k['idRef'])
+                allScanList.append(int(a.group(1)))
+        allScanList = list(set(allScanList))
+        # End of Reading mzML file
+        # fraction_name = sys.argv[4]
+        fraction_name = args.filestring
+        if fraction_name in scanDict.keys():
+            scansInList = scanDict[fraction_name]
+        else:
+            scansInList = []
+        scansNotInList = list(set(allScanList) - set(scansInList))
+        flag = 0
+        if removeORretain == "remove":
+            scan2retain = scansNotInList
+            scan2retain = list(set(scan2retain))
+            scan2retain.sort()
+            scansRemoved = scansInList
+            # scan2retain contains scans that is to be retained
+        elif removeORretain == "retain" and randomScans < len(scansNotInList):
+            # Randomly select spectra
+            random_scans = random.sample(scansNotInList, randomScans)
+            
+            scan2retain = random_scans + scansInList
+            scan2retain = list(set(scan2retain))
+            scan2retain.sort()
+            scansRemoved = list(set(allScanList) - set(scan2retain))
+            # scan2retain contains scans that is to be retained
+        else:
+            flag = 1
+            
+        if flag == 1:
+            scan2retain = scansInList
+            scan2retain = list(set(scan2retain))
+            scan2retain.sort()
+            scansRemoved = list(set(allScanList) - set(scan2retain))
+            
+            # scan2retain contains scans that is to be retained
+            print("ERROR: Number of Random Scans queried is more than available. The result has provided zero random scans.", file=sys.stdout)
+            print("Number of available scans for random selection: " + str(len(scansNotInList)), file=sys.stdout)
+            print("Try a number less than the available number. Thanks!!", file=sys.stdout)
+            print("Number of Scans retained: " + str(len(scan2retain)), file=sys.stdout)
+        else:
+            # Print Stats
+            print("Total number of Scan Numbers: " + str(len(list(set(allScanList)))), file=sys.stdout)
+            print("Number of Scans retained: " + str(len(scan2retain)), file=sys.stdout)
+            print("Number of Scans removed: " + str(len(scansRemoved)), file=sys.stdout)
+            
+        
+        # Identifying groups of continuous numbers in the scan2retain and creating scanString
+        scanString = ""
+        for a, b in groupby(enumerate(scan2retain), lambda x:x[1]-x[0]):
+            x = list(map(itemgetter(1), b))
+            scanString = scanString + "["+str(x[0])+","+str(x[-1])+"] "
+        # end identifying
+        # start create filter file
+        filter_file = open("filter.txt", "w")
+        filter_file.write("filter=scanNumber %s\n" % scanString)
+        filter_file.close()
+        # end create filter file 
+    
+        # Prepare command for msconvert
+        inputFile = fraction_name+".mzML"
+        os.symlink(inputPath,inputFile)
+        outFile = "filtered_"+fraction_name+".mzML"
+        # msconvert_command = "msconvert " + inputFile + " --filter " + "\"scanNumber " + scanString + " \" " + " --outfile " + outFile + " --mzML --zlib"
+        msconvert_command = "msconvert " + inputFile + " -c filter.txt " + " --outfile " + outFile + " --mzML --zlib"
+        
+        
+        # Run msconvert
+        try:
+            subprocess.check_output(msconvert_command, stderr=subprocess.STDOUT, shell=True)
+        except subprocess.CalledProcessError as e:
+            sys.stderr.write( "msconvert resulted in error: %s: %s" % ( e.returncode, e.output ))
+            sys.exit(e.returncode)
+        # Copy output to 
+        shutil.copyfile(outFile, outPath)
+    else:
+        print("Please contact the admin. Number of inputs are not sufficient to run the program.\n")
+
+if __name__ == "__main__":
+    main()
+    
+    
+    
+    

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/msms_extractor.xml	Tue Oct 29 11:09:46 2019 -0400
@@ -0,0 +1,81 @@
+<tool id="msms_extractor" name="msms_extractor" version="1.0.0">
+  <description>Extract MS/MS scans from the mzML file(s) based on PSM report</description>
+  <requirements>
+      <requirement type="package" version="3_0_9992">proteowizard</requirement>
+      <requirement type="package" version="3.7.3">python</requirement>
+      <requirement type="package" version="4.1.2">pyteomics</requirement>
+      <requirement type="package" version="0.25.2">pandas</requirement>
+  </requirements>
+  <command detect_errors="aggressive"><![CDATA[python '$__tool_directory__/msms_extractor.py' '$spectrumfile' '$psmreportfile' '$output' ${spectrumfile.name.rsplit('.',1)[0]} '$removeretain.doremoveretain' '$removeretain.num_random_scans']]></command>
+  <inputs>
+    <param name="spectrumfile" type="data" format="mzml" label="Input mzML File"/>
+    <param name="psmreportfile" type="data" format="tabular" label="Input PSM Report File"/>
+    
+    <conditional name="removeretain">
+        <param name="doremoveretain" type="select" display="radio" label="Retain or Remove the MS/MS scans that were identified in PSM report">
+            <option value="remove" selected="True">Remove the scans reported in the PSM Report File</option>
+            <option value="retain">Retain the scans reported in the PSM Report File </option>
+        </param>
+        
+        <when value="remove">
+            <param name="num_random_scans" type="hidden" value="0" />
+        </when>
+        <when value="retain">
+            <param name="num_random_scans" type="integer" label="Add N random scans in addition to those in the list" value="0" optional="true" />
+        </when>
+      </conditional>
+      
+  </inputs>
+
+  <outputs>
+    <data format="mzml" name="output" label="${spectrumfile.name.rsplit('.',1)[0]}.mzml" />
+  </outputs>
+  
+  <tests>
+    <test>
+        <param name="spectrumfile" value="Mo_Tai_iTRAQ_f1.mzml"/>
+        <param name="psmreportfile" value="test_psmreport.tabular"/>
+        <conditional name="removeretain">
+            <param name="doremoveretain" value="retain"/>
+            <param name="num_random_scans" value="5"/>
+        </conditional>
+        <output name="output">
+            <assert_contents>
+                <has_text text="Mo_Tai_iTRAQ_f1" />
+            </assert_contents>
+        </output>
+    </test>
+  </tests>
+
+  <help>
+msms_extractor reads scan numbers from the PSM report (scan numbers with identified PSM) and gives option to create a new mzml file, either with those scans or without those scans.
+
+----
+
+REMOVE option:
+
+Creates a new mzml file with all the unidentified scans (removes those that are in the PSM report).
+
+
+RETAIN option:
+
+Creates a new mzml file with only those scans that is present in the PSM report. In addition to this, it also has an option to add N number of randomly selected scans to the output mzml file.
+
+----
+
+Please Note: This tool currently works only with PeptideShaker generated PSM report file.
+
+
+This tool uses msconvert from ProteoWizard: Chambers, M.C., MacLean, B., Burke, R., Amode, D., Ruderman, D.L., Neumann, S., Gatto, L., Fischer, B., Pratt, B., Egertson, J., Hoff, K., Kessner, D., Tasman, N., Shulman, N., Frewen, B., Baker, T.A., Brusniak, M.-Y., Paulse, C., Creasy, D., Flashner, L., Kani, K., Moulding, C., Seymour, S.L., Nuwaysir, L.M., Lefebvre, B., Kuhlmann, F., Roark, J., Rainer, P., Detlev, S., Hemenway, T., Huhmer, A., Langridge, J., Connolly, B., Chadick, T., Holly, K., Eckels, J., Deutsch, E.W., Moritz, R.L., Katz, J.E., Agus, D.B., MacCoss, M., Tabb, D.L. and Mallick, P. A cross-platform toolkit for mass spectrometry and proteomics. Nature Biotechnology 30, 918-920 (2012).
+
+  </help>
+    <citations>
+        <citation type="bibtex">
+@misc{A cross-platform toolkit for mass spectrometry and proteomics,
+    author={Matt Chambers et al.},
+    year={2012},
+    title={ProteoWizard}
+}
+        </citation>
+    </citations>
+</tool>

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Mo_Tai_iTRAQ_f1.mzml	Tue Oct 29 11:09:46 2019 -0400
@@ -0,0 +1,2311 @@
+<?xml version="1.0" encoding="utf-8"?>
+<indexedmzML xmlns="http://psi.hupo.org/ms/mzml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://psi.hupo.org/ms/mzml http://psidev.info/files/ms/mzML/xsd/mzML1.1.2_idx.xsd">
+  <mzML xmlns="http://psi.hupo.org/ms/mzml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://psi.hupo.org/ms/mzml http://psidev.info/files/ms/mzML/xsd/mzML1.1.0.xsd" id="Mo_Tai_iTRAQ_f1" version="1.1.0">
+    <cvList count="2">
+      <cv id="MS" fullName="Proteomics Standards Initiative Mass Spectrometry Ontology" version="4.0.1" URI="http://psidev.cvs.sourceforge.net/*checkout*/psidev/psi/psi-ms/mzML/controlledVocabulary/psi-ms.obo"/>
+      <cv id="UO" fullName="Unit Ontology" version="12:10:2011" URI="http://obo.cvs.sourceforge.net/*checkout*/obo/obo/ontology/phenotype/unit.obo"/>
+    </cvList>
+    <fileDescription>
+      <fileContent>
+        <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+        <cvParam cvRef="MS" accession="MS:1000580" name="MSn spectrum" value=""/>
+      </fileContent>
+      <sourceFileList count="2">
+        <sourceFile id="RAW1" name="Mo_Tai_iTRAQ_f1.raw" location="file:///">
+          <cvParam cvRef="MS" accession="MS:1000768" name="Thermo nativeID format" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000563" name="Thermo RAW format" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000569" name="SHA-1" value="17bd03b806e0b7b43cedc614c91144284085212b"/>
+        </sourceFile>
+        <sourceFile id="Mo_Tai_iTRAQ_f1.mzML" name="Mo_Tai_iTRAQ_f1.mzML" location="file:///">
+          <cvParam cvRef="MS" accession="MS:1000569" name="SHA-1" value="7c5f5e818198c13b5fea1ce690d2eb57354b5e9e"/>
+        </sourceFile>
+      </sourceFileList>
+    </fileDescription>
+    <referenceableParamGroupList count="1">
+      <referenceableParamGroup id="CommonInstrumentParams">
+        <cvParam cvRef="MS" accession="MS:1001910" name="LTQ Orbitrap Elite" value=""/>
+        <cvParam cvRef="MS" accession="MS:1000529" name="instrument serial number" value="SN05085B"/>
+      </referenceableParamGroup>
+    </referenceableParamGroupList>
+    <softwareList count="3">
+      <software id="Xcalibur" version="2.7.0">
+        <cvParam cvRef="MS" accession="MS:1000532" name="Xcalibur" value=""/>
+      </software>
+      <software id="pwiz" version="3.0.6618">
+        <cvParam cvRef="MS" accession="MS:1000615" name="ProteoWizard software" value=""/>
+      </software>
+      <software id="pwiz_3.0.9987" version="3.0.9987">
+        <cvParam cvRef="MS" accession="MS:1000615" name="ProteoWizard software" value=""/>
+      </software>
+    </softwareList>
+    <instrumentConfigurationList count="2">
+      <instrumentConfiguration id="IC1">
+        <referenceableParamGroupRef ref="CommonInstrumentParams"/>
+        <componentList count="3">
+          <source order="1">
+            <cvParam cvRef="MS" accession="MS:1000398" name="nanoelectrospray" value=""/>
+            <cvParam cvRef="MS" accession="MS:1000485" name="nanospray inlet" value=""/>
+          </source>
+          <analyzer order="2">
+            <cvParam cvRef="MS" accession="MS:1000484" name="orbitrap" value=""/>
+          </analyzer>
+          <detector order="3">
+            <cvParam cvRef="MS" accession="MS:1000624" name="inductive detector" value=""/>
+          </detector>
+        </componentList>
+        <softwareRef ref="Xcalibur"/>
+      </instrumentConfiguration>
+      <instrumentConfiguration id="IC2">
+        <referenceableParamGroupRef ref="CommonInstrumentParams"/>
+        <componentList count="3">
+          <source order="1">
+            <cvParam cvRef="MS" accession="MS:1000398" name="nanoelectrospray" value=""/>
+            <cvParam cvRef="MS" accession="MS:1000485" name="nanospray inlet" value=""/>
+          </source>
+          <analyzer order="2">
+            <cvParam cvRef="MS" accession="MS:1000083" name="radial ejection linear ion trap" value=""/>
+          </analyzer>
+          <detector order="3">
+            <cvParam cvRef="MS" accession="MS:1000253" name="electron multiplier" value=""/>
+          </detector>
+        </componentList>
+        <softwareRef ref="Xcalibur"/>
+      </instrumentConfiguration>
+    </instrumentConfigurationList>
+    <dataProcessingList count="2">
+      <dataProcessing id="pwiz_Reader_Thermo_conversion">
+        <processingMethod order="0" softwareRef="pwiz">
+          <cvParam cvRef="MS" accession="MS:1000544" name="Conversion to mzML" value=""/>
+        </processingMethod>
+        <processingMethod order="1" softwareRef="pwiz">
+          <cvParam cvRef="MS" accession="MS:1000035" name="peak picking" value=""/>
+          <userParam name="Thermo/Xcalibur peak picking"/>
+        </processingMethod>
+      </dataProcessing>
+      <dataProcessing id="pwiz_Reader_conversion">
+        <processingMethod order="0" softwareRef="pwiz_3.0.9987">
+          <cvParam cvRef="MS" accession="MS:1000544" name="Conversion to mzML" value=""/>
+        </processingMethod>
+      </dataProcessing>
+    </dataProcessingList>
+    <run id="Mo_Tai_iTRAQ_f1" defaultInstrumentConfigurationRef="IC1" startTimeStamp="2012-07-30T21:14:16Z" defaultSourceFileRef="RAW1">
+      <spectrumList count="39" defaultDataProcessingRef="pwiz_Reader_conversion">
+        <spectrum index="0" id="controllerType=0 controllerNumber=1 scan=218" defaultArrayLength="562">
+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="371.101440429688" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="2.44826296875e05" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="2.07234625e06"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="300.061706542969" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1648.390502929688" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
+            <scan>
+              <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="6.921275" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p NSI Full ms [300.00-1700.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="100.0" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
+              <scanWindowList count="1">
+                <scanWindow>
+                  <cvParam cvRef="MS" accession="MS:1000501" name="scan window lower limit" value="300.0" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="1700.0" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
+          </scanList>
+          <binaryDataArrayList count="2">
+            <binaryDataArray encodedLength="2604">
+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000514" name="m/z array" value="" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
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+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="3.74258e06" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="6.1881036e07"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="300.061737060547" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1672.70166015625" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
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+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
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+              <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="89.730323333333" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
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+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="13.913149833679" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
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+                <scanWindow>
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+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="1700.0" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
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+          <binaryDataArrayList count="2">
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+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
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+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="325.227722167969" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="8.69598875e05" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="2.031159e07"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="300.067535400391" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1246.626098632813" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
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+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000515" name="intensity array" value="" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
+              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+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="325.227722167969" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="8.552235e05" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="1.6718774e07"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="300.154815673828" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1186.592407226563" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
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+              </scanWindowList>
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+              <cvParam cvRef="MS" accession="MS:1000515" name="intensity array" value="" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
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+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="620.436828613281" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="8.90169125e05" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="1.8116974e07"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="300.100158691406" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1625.68701171875" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
+            <scan>
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+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p NSI Full ms [300.00-1700.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="62.178173065186" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
+              <scanWindowList count="1">
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+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="1700.0" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
+          </scanList>
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+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000514" name="m/z array" value="" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
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+              <cvParam cvRef="MS" accession="MS:1000515" name="intensity array" value="" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
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w2Dv/BQbliRzcj8FZkpLs0djPFYWq3OS5yw88VgK07i3kHuswO2yk5G/pYLpmyUFs39J0JTdSNlvmdilpSAMuOCG4yd7sOaOJk0fWhMNi5BQN4X3+//D5icvsdxGiYbeutxU/YTxIqJwQRp/7h8ilO35gBFG9rjgQ7yL1qDi7li0HpqBLwnGXBxcSrvH1fj4MhNJe0xodXe28FsqG90uq/hPK5Ypoid8Ot0HHy+GwHbmbLR9aMbE59PQmtmIuyNn8P275VgcY8jgSze5rXUM88S1tlAxoFNRuTgX2xF4JQDbvuSgaOV6WDsNZI9fzsiSshXkCv+gevIfPjfzZsP6EPz+FYE/b3tQZ21PejRuwDL+gepgWWHGvFXwOnkcnqOu0SouEu77pyNjLmHgFAP3T5E4+WwY1TVkOe9uJHYq1lFBQ4nFPy4i+62dcKFmK5Lb9lJFJR+9j3ti46ACmPUeKVhMmktdv370bZ6BtomfkG1pzeNipw0dmMGYZbc4QTYDNhE7oL+sGDr3gZjNtuh7KgQdcjM5L7EAi8p8+EJ1DlYJAzmqMQhtft944WsqVAyUhMrW/VBYbMCKxeksNUnERZUEbrvmizfHRGj6XILklidYFGMu8kvSYvq6bdQTkmHrEwGbqrU4ND0akTKPqfJkPEKuGlEh2R6NQZlcvi+En48FofGdOyTnhsDZQE7Y1b0Uso+3iWvmwHma6Wwt9BW5B8gz//1vfvXQ4b3X0+mzORSp7hOw0GWPkMJoeG+qw6ebrrgu1YNdPma0EN91zcNM/imvgebPB5DcbMBpWCJkPJpPlXnLYGx1C0u/irn020bqmU8Q5+Y4PlmXgnJPMSM8Ec+d/kbOmuMILaVbTJ4kJUyYvAtumvs4Ve0VHv62pVeJBz7LB+HXBXMmdOwXydkMomaeIe0dfyPjVLR4x+sIv84OZUJBLBpXG8H21kF8WhSPLa9C8cB9NaZ2eAhbKuyp4huH38/jKLulkJvmpHGncg9GGEWi+qQDCsd+Q/eSBzDsMZxvxwk8PGsE1yyUFtZejkThRxU+e2kFg9Js5BcshYJrLTok46DpEYdc1U7+d/gW8n/cFZ+5je0LnqJHsazwfUoSfuwtQUm6B0ImDhQdDHiKp897sE+FOW8YSdNvXAw9b1rwlUkn1j1UEfbb2SBaxYVb3vfk5Dv9hBAjBz6PVhCGWiTj1ExvuJUfxN0wUzoty8bOqeo8OSSTCYObcNPCnmo73nNFsBLLfv9BvpYN7FNncUO4DTdL22HP5Nm4+3ELJpsG8/nBcqzo9QflLRd5taqKx8xk6F4dBOsxy6n29wZuF0SJuSYUiic1uCfgMGsksrFidi2KDoXz9OaLuLvCiSkNVeiTrsQ+14Ogvq2E54MisGBJM6JyzwnK3TNQ3KeEzyLnwP/iZ7z96IOCfTMh4zmOUiZpOGA8AWMOnsP3sjHcm3cM2g2L8UTM5b66ZbjbtJEPGrKhvd8POntL8drlEdac16BeyRKs2e2MQ6+2wHtROd1PizNjsSK/bhqLp3sthIs1G/DlezrlZe7ja7APVOR1hdCJYVhi8oslD9IQMfw+12j2pPbfSOx7MZBzuubxblABZlwO4V/RG/yLnY6oY9I888kVRUNDcS9PiflVP7E/zYfaQak4P66PsNjAi75jnNC4u50TR2Thzs1tNDNdiGvfs4SnqxOE0+2m2P8wlMMWS7FBLR/b6rJQe2YQFdfm4FtJby7xNQFfejInbBm6FfbQrcmJBjrdmJmwiK7Dj7BgShwKRoUy5s8UypzYSfmY/6jYX4/BG4w50nk+70cvh4ebPo9YnmHeAR/Epw7my8DHiB1ijZiNGTjv+YH6L7vgoCHHrdYnaXo3E0O/zKBcD2MG7pkPDaVWOD5xR+u8L1BZbI/+A07ifvQCaiw8xLMamXDOzReM1sXRw/oUKl5boaQ5BXdAnPXRp4VxBY1rTtFEV8Rl9YO52TmFS154ImKKA9JqnmKpIrg3wwnec5ejaG0cTA8r8ZW1E/uVHmXd2uVQqrbHRtklaI19y00FkdAJbofFgT0iLTtVYe53L7iZHOeXpH5sEXvlwOJIzLWyxMGtUhSZT6bygASsePkJsX+v43ZasHDUIwJSdsn8auaAl/GTUJ2cyCbhNeZ19eTl9bUo16/EhqhuOOyNZ5XYF21Uk/FmVRMWxW5jTfFCJql2w3JdAjUugQtS5YWuVYk4FxaFkb0vM8R/D/b0WiOcktRk1axW/BoRgaUdcehYo8EFq28jYimEFZvCuV8lCAvk77DhkgR/S+Rh7aItKNvTKvy7eRWeJXG4MOQFnAv6suXJdeGnex6syzoxf+hPDs5vwvn+OyE/v40G059h7S1HqqXn84DyB+z9FEWJ90rCoGmRHB+txZBWNQ4OT8KbaWLPEfP8tpxIIW7fcyQqn6bzOA/ceHsfnx0MeOVXM9S9N8Ds6hCu9e/Lwf5NsK08xrvzvBg98zx766vyVnF/ho7qw3ErGmBY64V3JWlck9aTC7eno8JzHb+VZTN2+BykHw6lXr9orDUpxqGtdjzXsop70xzod/kbbdQu0vDQQ064s5RK2vHw4i9cObwMZ+Y2Y5HkF7ws/IgTy4w55/VNdrv15fzdJjQ4cw3xneGcevosXHc04Pj+YxSLJXy3JPKRuhcuenqhWMwyqZI5OOEbAvlETaGx4htXrQ7DobnLeX1gIIYFHeMnfQPOHHQcy/6LwVLNtaic2p/UycJvwyQeLP5Dm1s9GWkWwbHTs7BHfjxXzvVFj3GZ2PqnAD/m+ONG6Ha69JLhjbAApitG8krFdNGSayFCjrjXznXIMM3gDPbO+khRQy48vgYK7zqkBZW2Lez1swOWgzwRez4BRp4jqGY/XCh97473DjrcGi/HzPdBlNo3lEdvytLL7ymaTjxAwMzNfLk/Qvxm57B04hpqdToyv/s+barO4+7ecPa+3oPdQe6QK45CumY3fN99x8VnI7nHoLfgt3CR0Pf0Qc4cFgaT23NxUjUYwRPvYd0RGU5rCuNzGW32t5vKR/e/8vXCJBiZO3LuIHXqnfTizIv2trnyt3h9iaxgluXPtQptzO4hz9o55qLxpU8Z+eochk614XJrDaZZ1PPgNVXm7j/CorPhbO2MQfhOb5RUX+SKNSe4vdSHS7zc6D+nkqvXWXKD/l+4/ktBs3wrBgx6gMuTYrHjrBQfDDgpUlQPp/3s7Uxr/8ulxv0592Yebll4UfNeGppWrMb8bSk4k1UqZLhIc+X9+ayatBVbNlajx5swuOcE0XdLDW6m1mJsoSENSqzZcjAKzUP0qSFm1dPOURDNV6H2Ih32tlqG9D03oXZQjl9a4qD8qxOoXYagXuXoylZj0GRniEo/4fP1u+yaGohxGrFQD+zFfmeC8WNdDG4vlWCeaB7VAt1R+1ya6SuPcm37V0iqNEOnxyYcQBQON92Fyqfv8Fxfj8XVmTBrK+afA0kMFzOMlfc2XLE6jcVP91Nj0TAeXf1RVLFdkZLLXRGjuAEZ+d7oczwCFy5moDOxHPtnRuCDsg53vhnLTe9iMGvfUricOs3xsmnCRe9YDFt9BkpL/XEgYiC7DEKRrJWB8Qe349zKVYzb9pyj0gReU5ITjqvK8oHFHUwZN1IoaLIRJs9u4J577aLxLtk4UTOaD6R8eK3OlnHPsvHp2VBRtkqysHRwDlcc/o7i09J8u6aHsCQyGNZ+wwV3zb5C/fB8ePzKYa/HUoJKaiTsW4owyEBG2NH7ON6M0RG9qAkS9C7/xdzb42iY7IZ4HznBJ3ao6PTFX9i9LZR5SUZcZjCK1zZ00OluIBxD0iHs1aFXahDNXq/GiO5BPLZNX/RzhwUV82p5PDoOP7WmUvFlDQvDriPcVUJYpRwpjF28k8scZPmjVoLhT5aSOUY8Ui5HveNa3HA6iVeTt6FM2Yz9bWpZ/DGEL5w3MOuhtrCltyNvX4/B1X670GdcfyYdM2VteDLopcdxB7JwMNAXGj2C4C0Thi+nhjC8XI21lu9Rr5kMdy8JejjtYWfuEJq8kWdgZSeOq8+jle96BrW6cMLigTTJrsL7Xk7CpKmvEFX1HIHOQdhxVIIZ6fq02/+Oan+sKWUYyMMBBdzpXYMIaHPZmK9YapgK2W8JqBgYiRuzm5GiHsLR4x9hiWU87ihGUeQXg6O+9/Gzowx/XXZRp8aSXrI5+FpcxxmvkmHncge5fkmcaSfJ2juncC98OSryFJn43A8z71jw4MNfsH3fzkcTFXh+SC6Gasfh8rcgpIX7wTxHlcEF05kRWwX72lIGjp4t6EyLxO6v0Zjg/gUHbgdhyx2xpxrmYFrfoVwmJcexw29j7tWd/BWQhOtzJUT7Z4bgkfYovrJygu/NBGzqGQMvs2xahutRa8UzVvwczTFrnmFl1zq8ffKKukEpCLTaij8NvXhPKwrDjo/m78JEmm4K5aH8SDTsGsj2iCBh3YsBnPnGlt9O6vCmzm68yrTF6BmpFCsNC2b057JjspzYYMp9uyZy4nzx3dYtEdcnD9uzfRjxbjbtin3Y01GV79YN5ZozqXie1AJ/qzlC+aa+fBoRhp3Xj8N7vDFNPR+hc+8IznIdyfnGYXj4Og0Wsms47Gmw+P1ysEG8B9zH5yJqSTwuPrem6YQcPHodyz0yrtTQbMTshmTsCV+JH3FZvDjpHZyapdnbX46z3kzhpzm9efBGLoKvjuXkhBw0XNgFpZZsrK9txL3c9fivVOyiO/czZboMU09tgMHwbzga6id2IGeW10hxUdEoTuwew3tto6jmay3O5bHsWy/DPJcsbvl0jD0my3Lp9Pn0KqvEj5ZTOBTYj7Gf4+k5tw+TrH1R5BvIAfdleH96F/5lpcJf0pY7ns/CzcIzWJGoIOSfVRK+fN6ESVZhkD23DGXiu/VLu8m+IeOoO0eX0zbsE2fhPF7+qE6vZbmYuXQuu0++Z4ePG6JrA7DyRTgqkmPxtNKS+7rmMzf1IuY9khUeFPfk6wgtWsy/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+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1123.689086914063" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
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+              <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="98.628441666667" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p NSI Full ms [300.00-1700.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="66.386138916016" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
+              <scanWindowList count="1">
+                <scanWindow>
+                  <cvParam cvRef="MS" accession="MS:1000501" name="scan window lower limit" value="300.0" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="1700.0" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
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+          <binaryDataArrayList count="2">
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+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000514" name="m/z array" value="" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
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+          </binaryDataArrayList>
+        </spectrum>
+      </spectrumList>
+      <chromatogramList count="1" defaultDataProcessingRef="pwiz_Reader_conversion">
+        <chromatogram index="0" id="TIC" defaultArrayLength="13467">
+          <cvParam cvRef="MS" accession="MS:1000235" name="total ion current chromatogram" value=""/>
+          <binaryDataArrayList count="2">
+            <binaryDataArray encodedLength="104576">
+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000595" name="time array" value="" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
+              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+              <cvParam cvRef="MS" accession="MS:1000515" name="intensity array" value="" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of detector counts"/>
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</binary>
+            </binaryDataArray>
+          </binaryDataArrayList>
+        </chromatogram>
+      </chromatogramList>
+    </run>
+  </mzML>
+  <indexList count="2">
+    <index name="spectrum">
+      <offset idRef="controllerType=0 controllerNumber=1 scan=218">5320</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=982">14116</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=1058">39333</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=1230">61564</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=1261">67967</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=1505">92556</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=1697">99169</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=1968">106015</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=2044">112799</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=2539">119149</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=2555">128191</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=2725">134594</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=3634">140144</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=3663">159903</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=3905">165653</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=4335">172917</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=5209">178307</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=5338">184806</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=5771">190392</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=5795">196643</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=6094">202884</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=6828">231342</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=6943">238086</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=7612">245057</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=8198">250899</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=8410">257294</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=8515">263692</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=8518">270146</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=10305">276661</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=10715">282886</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=10811">289288</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=11153">295439</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=11592">301592</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=11910">307909</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=12190">313586</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=12804">343849</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=12965">374387</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=13295">404184</offset>
+      <offset idRef="controllerType=0 controllerNumber=1 scan=13303">435064</offset>
+    </index>
+    <index name="chromatogram">
+      <offset idRef="TIC">466355</offset>
+    </index>
+  </indexList>
+  <indexListOffset>638277</indexListOffset>
+  <fileChecksum>539397d5908e882f88418b20b61da40f56907c1c</fileChecksum>
+</indexedmzML>

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test_psmreport.tabular	Tue Oct 29 11:09:46 2019 -0400
@@ -0,0 +1,20 @@
+	Protein(s)	Sequence	Variable Modifications	Fixed Modifications	Spectrum File	Spectrum Title	Spectrum Scan Number	RT	m/z	Measured Charge	Identification Charge	Theoretical Mass	Isotope Number	Precursor m/z Error [ppm]	Localization Confidence	Probabilistic PTM score	D-score	Confidence [%]	Validation
+10575	A0A087WNL7, A0A087WNX7, A0A087WP63, A0A087WQ44, P58390, Q61670	QPPPPPR		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.10305.10305.2		4652.1978	467.2789612	2+	2+	931.5361349	1	4.155868855				93.06930693	Confident
+10576	Q9D6J6, Q9D6J6-2	GPGFGVQAGL		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.8410.8410.2		3878.6177	523.791687	2+	2+	1045.567829	0	0.947096				100	Confident
+10577	A0A140T8V5, P17918	IEDEEAS		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.2555.2555.2		1516.3381	468.7180481	2+	2+	935.4205556	0	1.05361899				95.04950495	Confident
+10578	P10854, Q64478, Q64525, Q6ZWY9	IAGEASR		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.1505.1505.2		1063.2866	424.2417908	2+	2+	846.4681149	0	1.076889273				93.06930693	Confident
+10579	Q60692	FTIATLPPP		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.10811.10811.2		4869.3752	550.828064	2+	2+	1099.639931	0	1.492079647				94.05940594	Confident
+10580	Q9CXU4, Q9WTQ8	GSLLQQSL		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.8515.8515.2		3922.2633	495.291626	2+	2+	988.5674946	0	1.215895185				91.08910891	Confident
+10581	A6X925, B2KF55, Q9D2M8, Q9D2M8-2	LPQPPEGQTYNN		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.5771.5771.2		2795.7924	751.3736572	2+	2+	1500.733056	0	-0.196181326				96.03960396	Confident
+10582	P09411	VLPGVDALSNV		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.11153.11153.2		5015.2472	614.3571167	2+	2+	1226.699237	0	0.360900738				100	Confident
+10583	P63038, P63038-2	DPGMGAMGGMGGG	Oxidation of M(4, 10, 7)	iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.1230.1230.2		936.9463	643.7511597	2+	2+	1285.485892	0	1.455532533	Oxidation of M (4: Very Confident, 7: Very Confident, 10: Very Confident)	Oxidation of M (4: 100.0, 7: 100.0, 10: 100.0)	Oxidation of M (4: 99.85994397759103, 7: 99.85994397759103, 10: 99.85994397759103)	95.04950495	Confident
+10584	D3Z3Z9, E9Q2Q9, F6X737, K4DI78, Q3TRP8, Q8C0D9, Q8C0D9-2, Q9DBN9, Q9JKY0, Q9WUZ7	GIPLPPQ		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.6828.6828.2		3218.7408	433.2674561	2+	2+	864.5190878	0	1.467161264				97.02970297	Confident
+10585	H3BLM7, H9H9T1, Q3TGF2	TGQEVAQAQES		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.1968.1968.2		1266.375	646.3167114	2+	2+	1290.617358	0	1.169742125				96.03960396	Confident
+10586	E9Q3W4, Q9QXS1, Q9QXS1-10, Q9QXS1-11, Q9QXS1-12, Q9QXS1-13, Q9QXS1-14, Q9QXS1-15, Q9QXS1-16, Q9QXS1-2, Q9QXS1-3, Q9QXS1-4, Q9QXS1-5, Q9QXS1-6, Q9QXS1-7, Q9QXS1-8, Q9QXS1-9	YASGPSASLGGPESAVA		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.6943.6943.2		3266.5296	832.9186401	2+	2+	1663.817514	0	3.1294327				100	Confident
+10587	Q8BGD8	FEAGGFQSSQSTENS		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.5795.5795.2		2804.2182	860.8845215	2+	2+	1718.750557	1	0.336087629				97.02970297	Confident
+10588	A0A087WQS2, Q9CQC6	NAEEESESEAEEGD		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.2725.2725.2		1584.4306	834.8273315	2+	2+	1667.640397	0	-0.171970548				100	Confident
+10589	Q99L27	VTQQVNPIFSNSQ		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.7612.7612.2		3547.5953	803.92	2+	2+	1604.828019	1	-3.688672461				90.0990099	Confident
+10590	H3BLM7, H9H9T1, Q3TGF2	TGQEVAQAQES		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.2044.2044.2		1298.5425	646.3157959	2+	2+	1290.617358	0	-0.246790046				99.00990099	Confident
+10591	D3Z2H9, E9Q5J9, P21107-2	MLDQTLLDLNEM	Oxidation of M(12, 1)	iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.10715.10715.2		4829.5611	806.3909302	2+	2+	1610.765345	0	1.21702246	Oxidation of M (1: Very Confident, 12: Very Confident)	Oxidation of M (1: 100.0, 12: 100.0)	Oxidation of M (1: 100.0, 12: 100.0)	100	Confident
+10592	Q64010	LLDQQNPDEDFS		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.8198.8198.2		3792.9843	782.8687134	2+	2+	1563.717466	0	3.453967916				100	Confident
+10593	D3Z6F5, Q03265	EIVTNFLAGFEP		iTRAQ 4-plex of peptide N-term(1)	Mo_Tai_iTRAQ_f1.mgf	Mo_Tai_iTRAQ_f1.11592.11592.2		5136.2899	740.8937988	2+	2+	1479.77313	0	-0.057710511				94.05940594	Confident