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gnps_workflows's Issues

Problem running Dereplicator on MGF file from MZmine

The issue was already reported to @alexeigurevich and Hosein, and is caused by the MGF parser, more specifically the 'ION" line in the MGF from MZmine:
ION=[M+H]+
with "[", "]", and "+" that are special characters.
The issue is observed both for Dereplicator and Dereplicator+
https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=4093ac6cf5d848ca9f166673b3fb496c
https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=6651b66b49d744788cc3e11640c7566f

The work around for now is to delete these lines in the MGF file.

Link to Dereplicator from V2

We were discussing having a linkout button from the MolNet V2 results page to to Dereplicator (VarQuest) workflow.
This would pre-select the clustered MGF file in the Dereplicator workflow.

View Motif Labels for Spectra table empty in MS2LDA_MOTIFDB version 1.1.1

The FEATURE-BASED-MOLECULAR-NETWORKING workflow version 1.2.3 links out to MS2LDA_MOTIFDB version 1.1.1 (Analyze with MS2LDA):

https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=b817262cb6114e7295fee4f73b22a3ad

The .graphml output looks fine, however, the 'View Motif Labels for Spectra' table for MS2LDA_MOTIFDB version 1.1.1 is empty:

https://gnps.ucsd.edu/ProteoSAFe/result.jsp?task=c03bb8a8f5e74cb89a0b30b815f841b5&view=view_motifs

Downloading input files for FBMN

Having a download button in the results interface to the MGF, feature table and metadata.
Also discussed making available the "converted feature" table generated by the converting script.

Error in FBMN workflow - job fails

unknown error message in FBMN workflow; possibly due to IIN part of feature finding in mzMINE?

https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=a17860355635486e96116f7555e2f008

FAILED[Clone][Restart][Delete]Traceback (most recent call last): File "/data/ccms-gnps/tools/feature-based-molecular-networking/scripts/convert_networks_to_graphml.py", line 31, in main() File "/data/ccms-gnps/tools/feature-based-molecular-networking/scripts/convert_networks_to_graphml.py", line 26, in main nx.write_graphml(G, sys.argv[5], infer_numeric_types=True) File "</data/ccms-gnps/tools/anaconda3/lib/python3.5/site-packages/decorator.py:decorator-gen-620>", line 2, in write_graphml_lxml File "/data/ccms-gnps/tools/anaconda3/lib/python3.5/site-packages/networkx/utils/decorators.py", line 240, in _open_file result = func_to_be_decorated(*new_args, **kwargs) File "/data/ccms-gnps/tools/anaconda3/lib/python3.5/site-packages/networkx/readwrite/graphml.py", line 150, in write_graphml_lxml writer.dump() File "/data/ccms-gnps/tools/anaconda3/lib/python3.5/site-packages/networkx/readwrite/graphml.py", line 702, in dump self._xml_base.exit(None, None, None) File "src/lxml/serializer.pxi", line 716, in lxml.etree.xmlfile.exit (src/lxml/lxml.etree.c:137075) File "src/lxml/serializer.pxi", line 993, in lxml.etree._IncrementalFileWriter._close (src/lxml/lxml.etree.c:141610) File "src/lxml/serializer.pxi", line 999, in lxml.etree._IncrementalFileWriter._handle_error (src/lxml/lxml.etree.c:141711) File "src/lxml/serializer.pxi", line 195, in lxml.etree._raiseSerialisationError (src/lxml/lxml.etree.c:131087) lxml.etree.SerialisationError: unknown error -1481614473 Tool execution terminates abnormally with exit code [1]

Sample name without extension in MS-DIAL feature table

MS-DIAL doesn’t output the filename extension (11111_P4_RB1_01_428.mzML) but just (11111_P4_RB1_01_428). After conversion with the "formater" it gives "11111_P4_RB1_01_428 Peak area".
Thus, the user should provide in the metadata table for FTBM job with MS-DIAL the file name without extension in the “sample name" column. @KyobinKang

@mwang87 Reminder for the " Peak area" as general tag for the quant column.

GNPS normalized output to QIIME2 Diversity Analysis

Interested in using the GNPS .qza output to run the qiime2 diversity plugin. I want to run the analysis on a rowsum normalized table but would need to make the final table in ppm in order for QIIME2 to accept it.
Would there be an plugin or automated way to create this ppm table? Would it maybe be beneficial to also have any other normalization options?

[MASST] Input Validation for MASST

Should handle cases:

  1. Where the is not intensity, only masses
  2. Too few peaks given query parameters
  3. Extra random characters that can't be parsed

Example inputs:

305.0830, 3000

144.0805

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