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    jpfeuffer commented #5498
Fabrizio Donnarumma
@FabrizioDonnarumma

Hello, I was wondering if the OpenMS nodes for PD are working on versions after 2.1 (specifically version 2.4). I installed the manually and I received an error during the Magellan server installation

2021-08-16 16:26:11,833 WARN SafeDirectoryCatalog - Unable to load one or more of the requested types from the assembly PD.OpenMS.AdapterNodes.dll.
Loader Exception List:
Exception: TypeLoadException
Reason: Method 'OnAllSpectraSentForSearch' in type 'PD.OpenMS.AdapterNodes.RNPxlProcessingNode' from assembly 'PD.OpenMS.AdapterNodes, Version=2.0.3.0, Culture=neutral, PublicKeyToken=null' does not have an implementation.
Reason: Method 'PrepareEditorDataField' in type 'Thermo.Discoverer.EntityDataFramework.Controls.GenericGridControl.CustomValueEditors.ShowSpectrumButtonValueEditor' from assembly 'PD.OpenMS.AdapterNodes, Version=2.0.3.0, Culture=neutral, PublicKeyToken=null' does not have an implementation.

2021-08-16 16:26:13,805 WARN SpectrumFileFactory - The following exception raised !

In addition, I see the same error as in issue#12 on github
OpenMS/PDCommunityNodes#12

Best.

Timo Sachsenberg
@timosachsenberg
Hi Fabrizio. The nodes are indeed not compatible with the 2.4 version. For protein-RNA cross-linking I did some update of the nodes to 2.5. May I ask what kind of analysis you want to perform?
Fabrizio Donnarumma
@FabrizioDonnarumma
Hi Timo, the analysis we want to perform is a protein RNA analysis. A user perform UV exposure of a sample containing RNA and their proteins, and we wanted to test the RNPxl workflow. The approach is almost identical to the one on the OpenMS page for the plugin
http://www.openms.de/comp/rnpxl/
Should we give up on using the plugin on PD 2.4?
Best,
F
Timo Sachsenberg
@timosachsenberg
@FabrizioDonnarumma I wrote you a direct message with some details
Michael A. Freitas, PhD
@mafreitas
I am using pyopenms to convert from a pepxml to an idxml. Much of the metadata does not transfer over. Any suggestions as to best way forward would be helpful
Pepxml
<spectrum_query spectrum="controllerType=0 controllerNumber=1 scan=2489" spectrumNativeID="controllerType=0 controllerNumber=1 scan=2489" start_scan="0" end_scan="0" index="0" precursor_neutral_mass="699.433885642605" assumed_charge="1" retention_time_sec="625.65469999998">
      <search_result>
        <search_hit hit_rank="1" peptide="NQVVLK" protein="sp|NHVY|NH_NISTmAb" peptide_prev_aa="K" peptide_next_aa="V" protein_descr="heavy chain" num_tot_proteins="1" num_matched_ions="6" tot_num_ions="10" calc_neutral_pep_mass="699.4279146837" massdiff="0.005970958904981671" num_tol_term="2" num_missed_cleavages="0" is_rejected="0">
          <modification_info/>
          <search_score name="hyperscore" value="0.8925092778361238"/>
          <search_score name="expect" value="1.1204365319590694"/>
          <search_score name="IPGF" value="0"/>
          <search_score name="IPGF2" value="0"/>
          <search_score name="sumI" value="3.1348981252898134"/>
          <search_score name="fragmentMT" value="0.021498891391843244"/>
          <search_score name="nextscore_std" value="0.0"/>
          <search_score name="matched_b1_ions" value="1"/>
          <search_score name="matched_a1_ions" value="2"/>
          <search_score name="matched_c1_ions" value="2"/>
          <search_score name="matched_y1_ions" value="1"/>
          <search_score name="matched_y-171_ions" value="0"/>
        </search_hit>
      </search_result>
idxml 
<PeptideIdentification score_type="expect" higher_score_better="false" significance_threshold="0.0" MZ="700.441710674504975" RT="625.654699999980039" >
            <PeptideHit score="1.120436531959069" sequence="NQVVLK" charge="1" aa_before="K" aa_after="V" protein_refs="PH_0" >
            </PeptideHit>
        </PeptideIdentification>
Script to convert
#!/usr/bin/env python3
from pyopenms import *
import sys

protein_ids = []
peptide_ids = []
PepXMLFile().load(sys.argv[1], protein_ids, peptide_ids)
IdXMLFile().store(sys.argv[2], protein_ids, peptide_ids)
MzIdentMLFile().store(sys.argv[3], protein_ids, peptide_ids)
Julianus Pfeuffer
@jpfeuffer
Hm true! Unfortunately we only read specific expected scores for a set of search engines.
https://github.com/OpenMS/OpenMS/blob/develop/src/openms/source/FORMAT/PepXMLFile.cpp#L1231
There would be an "else" case missing that translates arbitrary scores into metavalues.
Maybe with some easy logic like "ending in _ions -> int", otherwise "float"
Michael A. Freitas, PhD
@mafreitas
@jpfeuffer I could easily parse the data via a for loop. I tried by was not able to add in the search summary at the top of the idxml. Also the modifications did not transfer over. Is there an example for setting the search summary and correcting the modification information?
Michael A. Freitas, PhD
@mafreitas
@jpfeuffer Looking over the the PepXMLFile, it think most of the code I would need is there. I take a crack and circle back with questions.
Michael A. Freitas, PhD
@mafreitas
@jpfeuffer FWIW looking through PepXMFile.cpp. You are using the mass of H for calculating the peptide m/z values and not the proton mass. The difference is small.
Amnah Siddiqa
@amnahsiddiqa
image.png
Hi I need this scan metadata information about positive scan or being run on negative mode in the chromatogram file generated by FeatureFinderMetabo chromatogram file but I can not find it. Can anybody help me detect or include this information ion the same file.Thanks
I am using mzML file and using FeatureFinderMetabo created the chromatogram file but it does not have this information
Amnah Siddiqa
@amnahsiddiqa
so basically scan_polarity in chromatogram file
asif-rayhan
@asif-rayhan
I am getting an error during using TOPPAS, that says "loading of idMXL file failed, invalid byte...." How to solve this problem?
Julianus Pfeuffer
@jpfeuffer
@amnahsiddiqa I am not sure if FeatureFinderMetabo makes a distinction between positive and negative scans. If you have an mzML with mixed scan types I would split it first.
@asif-rayhan This is usually due to either a corrupt file or non-UTF8 symbols in file or folder names.
6 replies
Amnah Siddiqa
@amnahsiddiqa
@jpfeuffer Thanks; actually then i just need to get in teh list from mzMl file scan polarity ; could you help me with example script please
So far i can see we should be able to use getitem but i am not sure how to do that;
Julianus Pfeuffer
@jpfeuffer
getitem is a special method from python, indicating that you can use [] 
from pyopenms import *
exp = MSExperiment()  # type: PeakMap
loader = MzMLFile()
loader.load("/test/your.mzML", exp)
for spec in exp:  # type: PeakSpectrum
    instsettings = spec.getInstrumentSettings()  # type: InstrumentSettings
    if instsettings.getPolarity() == IonSource().Polarity.POSITIVE:
        print("positive")
but is is probably best if you jsut iterate
Amnah Siddiqa
@amnahsiddiqa
Screen Shot 2021-08-24 at 7.24.48 AM.png
Thank you very much; I do get that but i just one want to clarify one thing ; i am newbie so sorry for naive questions;
Screen Shot 2021-08-24 at 7.29.35 AM.png
so we get thsi information for every scan from <cvParam cvRef="MS" accession="MS:1000130" value="" name="positive scan" />
If I want to extract other cv param based on their accession say accession="MS:1000579" how do we go around that
Julianus Pfeuffer
@jpfeuffer
Unfortunately, it depends. Since the mzML format is always growing we decided to create special functions for the most common terms, the rest of it is stored in so called optional MetaValues
For the MS level, there is of course a special function.
spec.getMSLevel()
Amnah Siddiqa
@amnahsiddiqa
Alright Thanks for excellent package. I would reallly appreciate an example with any metalevel as well pelase
menaing any metalevel which does not have special function;
Julianus Pfeuffer
@jpfeuffer
from pyopenms import *
exp = MSExperiment()  # type: PeakMap
loader = MzMLFile()
loader.load("your.mzML", exp)
spec = exp[0]  # type: PeakSpectrum
metavaluekeys = []
spec.getKeys(metavaluekeys)
print(metavaluekeys) # metavaluekeys[0] == "base peak m/z"
print(spec.getMetaValue("base peak m/z"))
Amnah Siddiqa
@amnahsiddiqa
I really appreciate your help so much. big thank you!!!!
ichrak97
@ichrak97
Hello , i have an error after i runed the MetaboliteAdductDecharger method with positive charged samples , can someone explain it to me or have an idea how to fix it ? Thank you ! .... ERROR : Failing process stdout: [MassExplainer table size: 248, Generating Masses with threshold: -6.90776 ..., done, 8080 of 26659 valid net charge compomer results did not pass the feature charge constraints, Inferring edges raised edge count from 18579 to 39280, Found 39280 putative edges (of 440837) and avg hit-size of 0.678691, Using solver 'coinor' ..., Optimal solution found!, <Using solver 'coinor' ...> occurred 14 times, Branch and cut took 19170 seconds, with objective value: 1.156., <Optimal solution found!> occurred 14 times, ILP score is: 1.156, Agreeing charges: 262/3444, ConsensusFeature::computeDechargeConsensus() WARNING: Feature's charge is 0! This will lead to M=0!
Julianus Pfeuffer
@jpfeuffer
Hi, is there more output? This does not show the error.
ichrak97
@ichrak97
Failing process stdout: [MassExplainer table size: 248, Generating Masses with threshold: -6.90776 ..., done, 8080 of 26659 valid net charge compomer results did not pass the feature charge constraints, Inferring edges raised edge count from 18579 to 39280, Found 39280 putative edges (of 440837) and avg hit-size of 0.678691, Using solver 'coinor' ..., Optimal solution found!, <Using solver 'coinor' ...> occurred 14 times, Branch and cut took 19836.3 seconds, with objective value: 1.156., <Optimal solution found!> occurred 14 times, ILP score is: 1.156, Agreeing charges: 262/3444, ConsensusFeature::computeDechargeConsensus() WARNING: Feature's charge is 0! This will lead to M=0!, Error: Unable to write file (the file 'C:\Users\abdelwik\AppData\Local\Temp\knime_Workflow71090\fs-ZipLo_0-12-71112\000\000\17_3_MetaboliteAdductDecharger_0\20200127_KPE-M02_SampleNoIntern_4.raw.consensusXML' could not be created), ., <ConsensusFeature::computeDechargeConsensus() WARNING: Feature's charge is 0! This will lead to M=0!> occurred 907 times, .., Warning: a significant portion of your decharged molecules have gapped, even-numbered charge ladders (23 of 352)This might indicate a too low charge interval being tested., ., <..> occurred 2 times]
ERROR MetaboliteAdductDecharger 0:248 0796; q_net 0; logP -6.90776[[ (H12N3) --> (H3) ]], Compomer: Da -43.9639; q_net 0; logP -4.60517[[ (Na2) --> (H2) ]], Compomer: Da -42.9113; q_net 0; logP -5.99146[[ (K1Na1) --> (H1H4N1) ]], Compomer: Da -39.0085; q_net 0; logP -4.60517[[ (H4N1Na1) --> (H2) ]], Compomer: Da -37.9559; q_net 0; logP -3.21888[[ (K1) --> (H1) ]], Compomer: Da -34.0531; q_net 0; logP -4.60517[[ (H8N2) --> (H2) ]], Compomer: Da -33.0005; q_net 0; logP -5.99146[[ (H4N1K1) --> (H1Na1) ]], Compomer: Da -26.9373; q_net 0; logP -5.07517[[ (Na2) --> (H1H4N1) ]], Compomer: Da -25.8847; q_net 0; logP -6.46147[[ (K1Na1) --> (H8N2) ]], Compomer: Da -21.9819; q_net 0; logP -2.30259[[ (Na1) --> (H1) ]], Compomer: Da -20.9293; q_net 0; logP -3.68888[[ (K1) --> (H4N1) ]], Compomer: Da -17.0265; q_net 0; logP -2.30259[[ (H4N1) --> (H1) ]], Compomer: Da -15.9739; q_net 0; logP -3.68888[[ (K1) --> (Na1) ]], Compomer: Da -12.0712; q_net 0; logP -5.07517[[ (H8N2) --> (H1Na1) ]], Compomer: Da -11.0185; q_net 0; logP -6.46147[[ (H4N1K1) --> (Na2) ]], Compomer: Da -9.91079; q_net 0; logP -5.54518[[ (Na2) --> (H8N2) ]], Compomer: Da -6.00801; q_net 0; logP -5.99146[[ (Na2) --> (H1K1) ]], Compomer: Da -4.9554; q_net 0; logP -2.77259[[ (Na1) --> (H4N1) ]], Compomer: Da -3.90278; q_net 0; logP -5.99146[[ (H1K1) --> (H8N2) ]], Compomer: Da -1.05261; q_net 0; logP -5.99146[[ (H4N1Na1) --> (H1K1) ]], Compomer: Da 1.05261; q_net 0; logP -5.99146[[ (H1K1) --> (H4N1Na1) ]], Compomer: Da 3.90278; q_net 0; logP -5.99146[[ (H8N2) --> (H1K1) ]], ........

Failing process stdout: [MassExplainer table size: 248, Generating Masses with threshold: -6.90776 ..., done, 8080 of 26659 valid net charge compomer results did not pass the feature charge constraints, Inferring edges raised edge count from 18579 to 39280, Found 39280 putative edges (of 440837) and avg hit-size of 0.678691, Using solver 'coinor' ..., Optimal solution found!, <Using solver 'coinor' ...> occurred 14 times, Branch and cut took 19836.3 seconds, with objective value: 1.156., <Optimal solution found!> occurred 14 times, ILP score is: 1.156, Agreeing charges: 262/3444, ConsensusFeature::computeDechargeConsensus() WARNING: Feature's charge is 0! This will lead to M=0!, Error: Unable to write file (the file 'C:\Users\abdelwik\AppData\Local\Temp\knime_Workflow71090\fs-ZipLo_0-12-71112\000\000\17_3_MetaboliteAdductDecharger_0\20200127_KPE-M02_SampleNoIntern_4.raw.consensusXML' could not be created), ., <ConsensusFeature::computeDechargeConsensus() WARNING: Feature's charge is 0! This will lead to M=0!> occurred 907 times, .., Warning: a significant portion of your decharged molecules have gapped, even-numbered charge ladders (23 of 352)This might indicate a too low charge interval being tested., ., <..> occurred 2 times]
ERROR MetaboliteAdductDecharger 0:248 0796; q_net 0; logP -6.90776[[ (H12N3) --> (H3) ]], Compomer: Da -43.9639; q_net 0; logP -4.60517[[ (Na2) --> (H2) ]], Compomer: Da -42.9113; q_net 0; logP -5.99146[[ (K1Na1) --> (H1H4N1) ]], Compomer: Da -39.0085; q_net 0; logP -4.60517[[ (H4N1Na1) --> (H2) ]], Compomer: Da -37.9559; q_net 0; logP -3.21888[[ (K1) --> (H1) ]], Compomer: Da -34.0531; q_net 0; logP -4.60517[[ (H8N2) --> (H2) ]], Compomer: Da -33.0005; q_net 0; logP -5.99146[[ (H4N1K1) --> (H1Na1) ]], Compomer: Da -26.9373; q_net 0; logP -5.07517[[ (Na2) --> (H1H4N1) ]], Compomer: Da -25.8847; q_net 0; logP -6.46147[[ (K1Na1) --> (H8N2) ]], Compomer: Da -21.9819; q_net 0; logP -2.30259[[ (Na1) --> (H1) ]], Compomer: Da -20.9293; q_net 0; logP -3.68888[[ (K1) --> (H4N1) ]], Compomer: Da -17.0265; q_net 0; logP -2.30259[[ (H4N1) --> (H1) ]], Compomer: Da -15.9739; q_net 0; logP -3.68888[[ (K1) --> (Na1) ]], Compomer: Da -12.0712; q_net 0; logP -5.07517[[ (H8N2) --> (H1Na1) ]], Compomer: Da -11.0185; q_net 0; logP -6.46147[[ (H4N1K1) --> (Na2) ]], Compomer: Da -9.91079; q_net 0; logP -5.54518[[ (Na2) --> (H8N2) ]], Compomer: Da -6.00801; q_net 0; logP -5.99146[[ (Na2) --> (H1K1) ]], Compomer: Da -4.9554; q_net 0; logP -2.77259[[ (Na1) --> (H4N1) ]], Compomer: Da -3.90278; q_net 0; logP -5.99146[[ (H1K1) --> (H8N2) ]], Compomer: Da -1.05261; q_net 0; logP -5.99146[[ (H4N1Na1) --> (H1K1) ]], Compomer: Da 1.05261; q_net 0; logP -5.99146[[ (H1K1) --> (H4N1Na1) ]], Compomer: Da 3.90278; q_net 0; logP -5.99146[[ (H8N2) --> (H1K1) ]], ........

and the list goes on !

Julianus Pfeuffer
@jpfeuffer
Error: Unable to write file (the file 'C:\Users\abdelwik\AppData\Local\Temp\knime_Workflow71090\fs-ZipLo_0-12-71112\000\000\17_3_MetaboliteAdductDecharger_0\20200127_KPE-M02_SampleNoIntern_4.raw.consensusXML' could not be created)
Maybe no space anymore?
ichrak97
@ichrak97
yes you are right , i dind't notice that i am running out of space ! It worked , thank you so much !
Julianus Pfeuffer
@jpfeuffer
Remember that you can set the temp folder to some volume with more space as well.
In case you have multiple volumes
ichrak97
@ichrak97
yes thank you !
Timo Sachsenberg
@timosachsenberg
Hi, if you want to learn about OpenMS (and our partner projects) you can sign up for our free user meeting https://www.denbi.de/training/1283-cibi-user-meeting-2021 . Feel free to register to attend and get access to recorded talks.