Release Note: LipidXplorer 1.2.8
Release Note: LipidXplorer 1.2.8, October 14th, 2019
Improved Import Performance and Implementation of Frequency Filtering
Fadi Al Machot, Nils Hoffmann, Jacobo Miranda Ackerman and Dominik Schwudke
This release is focused on improving the import module and implementing the recently introduced filtering approach based on counting reoccurrences of peaks in MS-scans and MS/MS-scans conceptually following Schuhmann et al. . All other general functionalities of the former releases should not be affected [2-5]. Further changes were made for better documentation and simpler user guidance. Some experimental and/or unused options were deactivated (grouping samples, heuristic hierarchical alignment, dta/csv import). Details are listed below.
The frequency based filtering is active for the *.mzXML and *.mzML import module. For this release we have tested both *.mzXML and *.mzML files after conversion with msConvert of *.raw files of a Q Exactive instrument (Thermo Fisher Scientific, Bremen, Germany). The LipidXplorer (LX) software and also this improved import module were developed for shotgun lipidomics experiments.
Installation instructions and Tutorials for LipidXplorer are available here.
- Added frequency MS-Filter and MS/MS-Filter
The MS-Filter and MS/MS-Filter each take a value between 0 and 1. This value represents the fraction of scans in which a certain peak has to be present.
The filter is applied for both MS and MS/MS according to the given import setting for each scan type.
For each precursor ion, all associated MS/MS scans are collected according to the selection window. Counting of MS/MS scans and association of precursor is done automatically.
Accordingly, the number of MS/MS scan can vary for each precursor ion in the shotgun acquisition, as might occur when using a DDA strategy.
- Improved mzML file loading speed from O(n^2) to O(n).This improves loading speed of mzML files significantly and brings them on par with mzXML files considering import of data.
- Added application and taskbar icons.(Developers) Anaconda package management.LX now comes with a dependency definition for an Anaconda environment for development under Windows. Please check the GitLab README.md file for further information.
- LX executable distributions (convenience binaries).here.
- Updated Wiki locations to https://lifs.isas.de/wiki
- Fixed MFQL editor dialog closing error on Windows 10 and Python 2.7.
- Fixed application not exiting properly due to non-terminated threads.
- Improved file handle closing by switching to auto closing behaviour with 'with'.
- Fixed output file creation for user accounts with '.' characters in path.
- Fixed UI label truncations and spacing issues on Windows 10.
- Updated wxPython dependency from 3.0 to 4.0.4.
- Removed sample grouping
- Removed DTA/CSV + PIS support for input spectra (If you rely on this functionality, please contact us at Service & Support)
- We plan to remove the mzXML format in one of the next LipidXplorer releases. mzXML is not supported anymore by the mass spectrometry community and deprecated. If you need this feature, please contact us for help with migration.
The current maintainers, developers and contributors for LX would like to thank Ronny Herzog – initial author of the software for his continued support.
1. Schuhmann, K., et al., Intensity-Independent Noise Filtering in FT MS and FT MS/MS Spectra for Shotgun Lipidomics. Anal Chem, 2017. 89(13): p. 7046-7052.
2. Eggers, L.F. and D. Schwudke, Shotgun Lipidomics Approach for Clinical Samples. Methods Mol Biol, 2018. 1730: p. 163-174.
3. Herzog, R., et al., LipidXplorer: a software for consensual cross-platform lipidomics. PLoS One, 2012. 7(1): p. e29851.
4. Herzog, R., et al., A novel informatics concept for high-throughput shotgun lipidomics based on the molecular fragmentation query language. Genome Biol, 2011. 12(1): p. R8.
5. Herzog, R., D. Schwudke, and A. Shevchenko, LipidXplorer: Software for Quantitative Shotgun Lipidomics Compatible with Multiple Mass Spectrometry Platforms. Curr Protoc Bioinformatics, 2013. 43: p. 14 12 1-30.
6. Chambers, M.C., et al., A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol, 2012. 30(10): p. 918-20.