A “behind the scenes” talk for CANOPUS and compound class prediction is now available from our YouTube channel. As usual, this is not a talk which demonstrates how to use our software; rather, this talk explains what design decisions went into CANOPUS, why we did things this way and not that way, what performance you can expect, and so on. It also contains a hint of MAGIC… 😉 Enjoy.
We are fully aware that this post is far less interesting to you than it is to us; but sometimes, proud parents just have to do what proud parents have to do: CANOPUS has passed 25 million queries! Congratulations! Wow, that was fast, the preprint appeared on bioRxiv only 14 months ago.
In this context, we can also report that CSI:FingerID has surpassed 120 million queries. Which basically means we missed the round anniversary. We are bad parents; but kids are sometimes growing so quickly, you turn around and they are past 100 million queries.
Have fun with our tools!
SIRIUS 4.8.0 is out and releases the COSMIC confidence score to the wild. For more details on COSMIC see here.
After 2 and a half successful years and over 35 million predicted fingerprints, SIRIUS 4.0.1 will reach its end of life on Friday the 30th of April 2021.
What does this mean for you? We will shut down the web service for CSI:FingerID, so no fingerprint prediction and structure database search will be possible with SIRIUS 4.0.1 anymore.
We are happy to announce that SIRIUS 4.7.0 is now available for download . This release is all about fixing bugs and performance optimization. To all who had problems with the ILP solvers, a freezing GUI, high memory consumption or long running times: This update should make your life way easier. For a full list of changes see the Changelog.
We further integrated the option to compute fragmentation trees only with our heuristic algorithm (no ILP involved) to speedup molecular formula identification for high mass compounds.
Together with applying timeouts on compound level this should make the processing of large datasets much more feasible.
There is a new video available and it is finally explaining CSI:FingerID in much detail — possibly too much detail, the video is more than 2 hours. Covers everything from general thoughts and considerations about in silico methods and methods evaluation, to the details of molecular fingerprints, FingerID and, finally, CSI:FingerID. I am sorry for the bad audio quality, still using my build-in laptop mic.
We are happy to announce that the new online documentation for SIRIUS is now available at https://boecker-lab.github.io/docs.sirius.github.io/.
The content is completely written in Markdown which makes contributions by the community very easy. No programming skills required!
Help us with your contributions to make this documentation more comprehensive and useful for the community. See our GitHub repository for
detailed information on how to contribute.
Our article “Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra” has just appeared in Nature Biotechnology. Congrats to Kai and all co-authors!
In short: CANOPUS is a computational tool for systematic compound class annotation. It uses a deep neural network to predict 2,497 compound classes from fragmentation spectra, including all biologically relevant classes. From the machine learning perspective, the interesting part is that different levels of the neural network are trained using different data (heterogeneous training). CANOPUS explicitly targets compounds for which neither spectral nor structural reference data are available, and even predicts classes completely lacking tandem mass spectrometry training data. In evaluation using reference data, CANOPUS reached very high prediction performance (average accuracy of 99.7% in cross-validation) and outperformed four (rather advanced) baseline methods. We used CANOPUS to investigating the effect of microbial colonization in the mouse digestive system, for analyzing the chemodiversity of different Euphorbia plants, and for the structural elucidation of a novel marine natural product.
Full citation: K. Dührkop, L.-F. Nothias, M. Fleischauer, R. Reher, M. Ludwig, M. A. Hoffmann, D. Petras, W. H. Gerwick, J. Rousu, P. C. Dorrestein, and S. Böcker. Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra. Nat Biotechnol, 2020. https://doi.org/10.1038/s41587-020-0740-8
We are happy to announce that a new version of SIRIUS is available. With that, CANOPUS now supports negative ion mode data. Additionally, we included more structure databases CSI:FingerID can search in, such as COCONUT (Sorokina & Steinbeck, 2020) and NORMAN (Brack et al., 2012). And in case an important database is missing: With the new version, you can import custom databases using the GUI.
Even more features:
- All molecular structures have been standardized using the PubChem standardization service, to make structures more consistent. This update was already reported for version 4.4 but kept bugging us; it should now be solved for good. The standardization has a (small but measurable) positive impact on CSI:FingerID’s performance. More importantly, you will find fewer cases where CSI:FingerID is doing “something really strange”; this strange behavior was often due to un-standardized structures.
- Breaking news: We renamed a few columns in the SIRIUS project space (see Changelog), to make column names more descriptive. Sorry about that; please make sure your downstream analysis is reading in the right columns.
- CSI:FingerID now uses the molecular formula-specific Bayesian network scoring from our ISMB 2018 publication. Integrating this new score was a huge effort, but again has a positive impact on CSI:FingerID’s performance.
- To allow for a smooth transition, you can continue to use SIRIUS 4.4 and the corresponding CSI:FingerID web service until November the 30th.
- Please help us to make SIRIUS great again: Report bugs using the SIRIUS GitHub repository, or send an email to .
Our article “Database-independent molecular formula annotation using Gibbs sampling through ZODIAC” has just appeared in Nature Machine Intelligence. Congrats to Marcus and all co-authors!
In short: Annotating the molecular formula of a small molecule is the first step towards its structural elucidation but remains highly challenging, particularly for “large compounds” above 500 Daltons. ZODIAC is a network-based algorithm for the de novo annotation (no database needed) of molecular formulas, and processes complete experimental LC-MS/MS runs. (No metabolite is an island.) In comparison to SIRIUS, previously best-of-class for this task, ZODIAC reduces the error rate of false annotations roughly to the half. And sometimes, much more…
If you have problems accessing the paper: Here is a read-only version.
Full citation: M. Ludwig, L.-F. Nothias, K. Dührkop, I. Koester, M. Fleischauer, M.A. Hoffmann, D. Petras, F. Vargas, M. Morsy, L. Aluwihare, P.C. Dorrestein, and S. Böcker. Database-independent molecular formula annotation using Gibbs sampling through ZODIAC. Nat Mach Intell 2:629–641, 2020.
Some of you may have noticed problems where SIRIUS 4.4 GUI did not start without reporting any error.
This might be due to old incompatible configs (.sirius directory) from version 4.0.1. SIRIUS 4.4.21 fixes this problem and now uses a separate config directory (.sirius-4.4). It is now possible to use version 4.0.1 and 4.4.x along on the same system without interfering each other.
Since we could fix the deadlocks of the SIRIUS GUI on Mac with build 4.4.18, the SIRIUS 4.4. GUI now also available for MacOS: https://bio.informatik.uni-jena.de/software/sirius/
We are happy to introduce CANOPUS, a tool for the comprehensive annotation of compound classes from MS/MS data (certain restrictions apply, see below). In principle, CANOPUS is doing something similar as CSI:FingerID: Whereas CSI:FingerID can tell you what substructures are part of the query compound, CANOPUS does so for compound classes. The differences between both tasks are subtle but have massive consequences. See this preprint on the details of this difference, how CANOPUS works, how good it works etc.
At present, CANOPUS predicts 1270 compound classes. In more detail, CANOPUS predicts ClassyFire compound classes. ClassyFire is not the first but, to the best of our knowledge, by far the most comprehensive approach to assign classes solely from structure. (This last point is key, as this allows us to assign thousands of classes for millions of molecular structures.) Please have a look there if you use CANOPUS: Certain compound class definitions may be not what you expect. For example, we found that many phytosteroids are classified as bile acids in ClassyFire. While the biochemical origin of both classes is very different, they are structural very similar and, therefore, represented by the same class in the ClassyFire ontology.
You can download, install and use CANOPUS through SIRIUS 4.4. You will notice a new tab where you can access, for each compound, all compound classes it does or does not belong to (and, how sure we are about that). Fancier visualizations (see the preprint) will be made available with upcoming releases.
ps. Clearly, CANOPUS is comprehensive only within the limits of the LC-MS/MS technology: If a compound does not ionize, if no fragmentation spectrum is recorded in Data Dependent Acquisition, if a compound does not show any fragmentation, if multiple compounds are fragmented in a single spectrum etc, then CANOPUS cannot help you. We don’t do magic. Also, CANOPUS is limited by the available (structure and MS/MS) training data; but several years of thinking have been invested to get the most out of it.
We are happy to introduce ZODIAC, a tool for the comprehensive annotation of molecular formulas for complete LC-MS/MS runs. SIRIUS 4 is currently best-of-class for this task (as far as we know); but ZODIAC can do better. Different from SIRIUS which considers one compound at a time, ZODIAC considers a complete dataset, assuming that all compounds are somehow related (usually through biotransformations). See the preprint for evaluation and method details.
ZODIAC is about de novo annotations, meaning that we can assign molecular formulas for novel compounds currently absent from any structure database. ZODIAC takes into account “uncommon” elements, as in C24H47BrNO8P or C15H30ClIO5; both examples are indeed novel molecular formulas annotated by ZODIAC (and verified by us). Enter those molecular formulas into the PubChem search and see what you get back. (Fun fact: the first query now returns two entries created Jan 2020 based on our annotations.)
You can download, install and use ZODIAC through SIRIUS 4.4. Results of ZODIAC are simply displayed in the molecular formula tab, if you choose to run it. You should definitely use ZODIAC if you want to run CANOPUS: Assigning molecular classes to novel compounds implies that some of the molecular formulas may be novel, too; and you do not want provide CANOPUS a wrong molecular formula.
ps. Sorry for tweeting early, WordPress sometimes has a mind of its own.
We are happy to announce that SIRIUS 4.4 is finally released. (Unfortunately, the MacOS version will have to wait a few more days.) There have been numerous changes and improvements, only few of which can be mentioned here.
Probably the biggest change is that SIRIUS 4.4 now reads mzML files (“centroided” data) and processes complete LC-MS/MS datasets. You can use ProteoWizard to transform your dataset to mzML. This does not only make things easier for you; it also allows SIRIUS to extract isotope patterns and adduct information more thoroughly from the MS1 data. SIRIUS 4.4 also supports multi-run datasets and aligns runs.
If you are using the graphical user interface (GUI) you no longer have to care about installing (the correct version of) Java. It is part of the installed SIRIUS software.
SIRIUS 4.4 uses the same project space for the command-line (CLI) and the GUI version, allowing you to use the SIRIUS GUI to browse through results computed with the CLI. The GUI also allows you to save your project and reload it later, including all previously computed results. Finally, you can export summary CSV and mzTab-M files for downstream analysis.
CSI:FingerID also had some updates:
- Additional large molecular substructures: Have a look at the Fingerprint tab in the SIRIUS GUI, filter for large substructures.
- Standardization of molecular structures (mesomerism, charge etc) through PubChem. This does not only improve identification statistics by a few percentage points, but also gets rid of certain cases where CSI:FingerID was doing “strange things”. Unfortunately, PubChem keeps changing the standardization without giving big notice, so some issues remain; but the current situation is definitely better than no standardization.
- There is currently no version for MacOS; we are sorry. Somehow, MacOS does not like our multithreading. At present, we do not have access to a Mac for debugging, thanks to Corona.
- Please report bugs using the SIRIUS GitHub repository or . There will be numerous such bugs, as SIRIUS 4.4 again carries major improvements and transformations under the hood. Help us to make SIRIUS better.
- To allow for a smooth transition, you can continue to use SIRIUS 4.0.1 and the corresponding CSI:FingerID web service for a couple of weeks.
- SIRIUS 4.4 integrates ZODIAC and CANOPUS, see the separate news.
- passatutto is integrated into SIRIUS 4.4, allowing you to generate your own spectral library decoy database for FDR estimation.
- We have included a beautiful interactive fragmentation tree viewer.
- There may be a few more releases of SIRIUS 4.4.x that ship those things which are done in principle.
- Finally, we have not reported the number of CSI:FingerID queries for some time, so here we go: There have been 47 million CSI:FingerID queries. (Plus a few million we lost through a little scripting bug. Our bad.) That is roughly one query every 1.5 seconds since we reported one million queries in Feb 2018.
Yesterday (27 April 2020) our university computer network experienced some issues and was unavailable for several hours. Not unexpectedly, this also resulted in the unavailability of the CSI:FingerID web service, website etc. As usual, computer problems cause more computer problems: It looks like today (28 April 2020) we still have certain issues restarting the CSI:FingerID workers. That is hopefully resolved soon. We apologize for any inconvenience.
Some of you may have noticed that yesterday, April 17, the SIRIUS 4.4 beta has been released. This update is huge so we are particularly careful not to break too many things. (We will definitely break some things so please report bugs using the SIRIUS GitHub repository or .) Some facts of what you can expect:
- The official SIRIUS 4.4 release will happen in a few days.
- Even after SIRIUS 4.4 has been officially deployed, you can continue to use SIRIUS 4.0.1 and the corresponding CSI:FingerID web service. We hope that this allows for a smooth transition.
- SIRIUS 4.4 integrates ZODIAC for better molecular formulas.
- SIRIUS 4.4 integrates CANOPUS for compound class assignments.
- SIRIUS 4.4 now reads mzML files (“centroided” data) and processes complete LC-MS/MS datasets.
- CSI:FingerID had some massive updates, including more and larger molecular properties and standardization of molecular structures.
- SIRIUS 4.4 also supports multi-run datasets and aligns runs.
- SIRIUS 4.4 uses the same project space for the command-line and the user interface version, allowing you to use the SIRIUS GUI to browse through results computed with the CLI.
- passatutto is integrated into SIRIUS 4.4, allowing you to generate your own spectral library decoy database for FDR estimation.
- If you wonder why we jump from version 4.0.1 to 4.4: There have been several internal releases in between.
- A word of warning: Many features and changes have accumulated and there will be a few more releases (4.4.x) until the quiver is empty. For example, the structure database will change again as we have massive issues with the way PubChem handles structure standardization.
The International Max Planck Research School at the Max Planck Institute for Chemical Ecology in Jena is looking for PhD students. One of the projects is from our group on “making SIRIUS and CSI:FingerID GCMS-ready”. Deadline is May 08, 2020.
SIRIUS and CSI:FingerID are the best-of-class tools for MS-based compound identification in metabolomics, natural products and related fields. More than one million compound queries have been submitted to our web service, from over 3000 users and 47 countries. See our recent publication in Nature Methods (Dührkop et al., 2019).
Currently, our tools can only process tandem mass spectrometry data; extending them to Gas Chromatography Electron Ionization appears natural, but comes with numerous challenging problems from algorithmics and machine learning. This will be done in cooperation with the group of Georg Pohnert, see his recent publication in Nature (Thume et al., 2018).
We are searching for motivated candidates from bioinformatics, machine learning, cheminformatics and/or computer science who want to work in this exciting, quickly evolving interdisciplinary field. Please contact Sebastian Böcker in case of questions.
Half a position is being paid by the IMPRS; this will be supplemented by funding from our chair to 2/3 TV-L E13. (Note that the cost of living in East Germany is still considerably lower than in West Germany.) Jena is a beautiful city and wine is grown in the region: https://www.youtube.com/watch?v=DQPafhqkabc.
SIRIUS & CSI:FingerID: https://bio.informatik.uni-jena.de/software/sirius/
Literature: https://bio.informatik.uni-jena.de/publications/ and https://bio.informatik.uni-jena.de/textbook-algoms/
It’s been a while since SIRIUS 4 received its last update. We are excited to announce that SIRIUS 4.4 is coming soon.
It comes with many new features, e.g.:
- Project-Space: A standardized persistence layer shared by CLI and GUI that makes both fully compatible.
- Redesigned Command Line Interface: SIRIUS is now a toolbox that contains different sub-tools that can be combined to “tool-chains”.
- New (and newly integrated) tools:
- ZODIAC: Improve Molecular Formula Identifications by re-ranking SIRIUS molecular formula annotations using Bayesian statistics. ZODIAC optimizes annotations on a whole dataset taking advantage of the fact that compounds usually co-occur in a network of derivatives.
- PASSATUTTO: Is now part of SIRIUS and allows you to generate dataset specific decoy spectral libraries from computed fragmentation trees.
- lcms-align: SIRIUS supports mzML/mzXML format to process whole LC-MS/MS runs. The lcms-align preprocessing tool performs feature detection and feature alignment based on the available MS/MS spectra.
- Other handy standalone tools, e.g. compound similarity calculation.
To provide user friendly but also flexible and customizable access to the different tools we completely redesigned the command line interface (CLI).
We know that this might break your workflows and therefore we provide you an early access version of the CLI that can be used for testing and adapting your workflows:
You will also find an updated version of the manual which is still work-in-progress but contains already an updated section on the new CLI.
No worries, even when SIRIUS 4.4. will be released (as soon as the GUI is ready) version 4.0.1 will still be available for some time.
If you find bugs or have any feedback feel free to open an issue on the SIRIUS GitHub repository or contact us via .