NEWS


patRoon 2.3.3

Import changes

Minor changes

Fixes

patRoon 2.3.2

patRoon 2.3.1

When updating to this release, it is important to remove any cached data, i.e. by running clearCache("all") or manually removing the cache.sqlite file from your project directory.

patRoon 2.3

This release adds significant new functionality, several important changes and several bug fixes thanks to user feedback.

Users of previous patRoon versions should inform themselves with the important changes highlighted in the next section. Furthermore, it is important to remove any cached data, i.e. by running clearCache("all") or manually removing the cache.sqlite file from your project directory.

Important new functionality and changes

Revamped installation of patRoon and its dependencies

This release adds new way to install and update patRoon and its dependencies. The most important changes are

For more information, please read the [updated installation chapter][hb-inst] in the handbook, and see the project pages of [patRoonInst] and [patRoonExt].

IMPORTANT If you installed patRoon via the legacy installation script, please read the [installation chapter][hb-inst] to disable/remove this installation prior to updating patRoon!

Prediction of feature toxicities and concentrations (MS2Tox/MS2Quant integration)

The second milestone of this release is the integration of the [MS2Tox] and [MS2Quant] R packages, which support machine learning approaches to predict the toxicity and concentration of features. The integration adds the following functionality to patRoon:

Please see the relevant section in the handbook, and the project pages of [MS2Tox] and [MS2Quant] for more details.

Minor new functionality and changes

Fixes

patRoon 2.2

This release adds significant new functionality, several important changes and many bug fixes thanks to user feedback.

Users of previous patRoon versions should inform themselves with the important changes highlighted in the next section. Furthermore, it is important to remove any cached data, i.e. by running clearCache("all") or manually removing the cache.sqlite file from your project directory.

Important new functionality and changes

New reporting interface

The most significant change in this release is the addition of redesigned reporting functionality. Some key functionality and changes:

An example can be seen from the report output of the tutorial.

The new reporting interface is used with the new report() method function. All the documentation was updated to reflect these changes. The now 'legacy' report interface (reportCSV(), reportPDF() and reportHTML()) is still available for backwards compatibility and may still be of interest as the new interface currently only supports the HTML format.

The new reporting functionality obviously did not yet underwent years of usage and feedback. Hence, please report any bugs and suggestions you may have!

Usage of SIRIUS version 5

Active logins are now necessary to use webservices such as CSI:FingerID, see e.g. https://boecker-lab.github.io/docs.sirius.github.io/account-and-license/ This release of patRoon adds support to make logging in more easy and adds several compatibility fixes for the latest SIRIUS version. The new utility function getSIRIUSToken() can be used to obtain a necessary login token. The new token argument for generateCompoundsSIRIUS() can be used to automatically log in. The newPorject() function was extended to use this new functionality.

Docker images moved

The Docker images are now served by the GitLab server of the University of Amsterdam. To pull the latest images you can run the following command:

docker pull uva-hva.gitlab.host:4567/r.helmus/patroon/patroonrs

The changes are reflected in the installation section of the handbook.

TP formula libraries

A new algorithm for generateTPs() was added: library_formula. This algorithm is similar to the library algorithm, but only works with chemical formulae. This is especially useful if only formula data is available for parents and/or TPs. The genFormulaTPLibrary() utility function can be used to automatically generate a formula library from given transformation rules. More information can be found in the updated handbook and reference manual (?generateTPsLibraryFormula).

Other

Other important changes include:

Minor new functionality

Minor changes

Fixes

patRoon 2.1

This release extends version 2.0 with new functionality, several important changes and bug fixes. The newProject() function was updated for the new functionality. Please see the updated Handbook and sections below for more information.

Users of previous patRoon versions should inform themselves with the important changes highlighted in the next section. Furthermore, it is highly recommended to remove any cached data, i.e. by running clearCache("all") or manually removing the cache.sqlite file from your project directory.

Important new functionality and changes

Other new functionality

Minor changes

Fixes

patRoon 2.0.2

patRoon 2.0.1

patRoon 2.0

This release adds a significant amount of new functionality and changes. Please see the updated Handbook and sections below for more information.

Users of previous patRoon versions should inform themselves with the important changes highlighted in the next section. Furthermore, it is highly recommended to remove any cached data, i.e. by running clearCache("all") or manually removing the cache.sqlite file from your project directory.

Important changes

Major new functionality

Transformation product screening

The most important new functionality in patRoon 2.0 are transformation product (TP) screening workflows. This release adds functionality to predict TPs (with BioTransformer or metabolic logic) or search TPs in PubChem or custom databases. Furthermore, other data such as MS/MS similarity or feature classification data can be used to relate parent/TP features. Other TP screening functionality includes TP prioritization and automatic generation of TP compound database for MetFrag annotation. The workflows follow the classical design of patRoon, where flexible workflows can be executed with a combination of established algorithms and new functionality. For more information, please see the dedicated chapter about TP screening in the Handbook.

Sets workflows

Another major change in this release is the addition of sets workflows. These workflows are typically used to simultaneously process positive and negative ionization data. Advantages of sets workflows include simplification of data processing, combining positive and negative data to improve e.g. feature annotations and easily comparing features across polarities. A sets workflow requires minimal changes to a 'classical workflow', and most of the additional work needed to process both polarities is done automatically behind the scenes. For more information, please see the dedicated chapter about sets workflows in the Handbook.

Features

The following new feature detection/grouping algorithms were integrated: SIRIUS, KPIC2 and SAFD. Furthermore, integration with MetaClean was implemented for the calculation of peak qualities and machine learning based classification of pass/fail peaks. In addition, the peak qualities are used to calculate peak scores, which can be used for quick assessment and prioritization.

Data curation

Interactive curation of feature data with checkChromatograms() was replaced with checkFeatures(), which is much faster, is better suitable for larger datasets, customizable and has an improved user interface. Furthermore, this tool can be used for training/assessing MetaClean models. Similarly, checkComponents() is a function that allows interactive curation of component data.

The delete() generic function allows straightforward deletion of parts of the workflow data, such as features, components and annotations. Furthermore, this function makes it easy to implement customized filters.

Adduct annotation

The algorithms of OpenMS (MetaboliteAdductDecharger) and cliqueMS were integrated for additional ways to detect adducts/isotopes through componentization. Furthermore, the new selectIons() method uses these annotations to prioritize features (e.g. by only retaining those with preferable adducts). In addition, this function stores the adduct annotations for the remaining feature groups, which can then be automatically used for e.g. formula and compound annotation.

Other new functionality

Minor changes

Fixes

patRoon 1.2.1

patRoon 1.2.0

This releases focuses on a significantly changed suspect screening interface, which brings several utilities to assist suspect annotation, prioritization, mixing of suspect and full NTA workflows and other general improvements.

IMPORTANT: The suspect screening interface has changed significantly. Please read the documentation (?screenSuspects and the handbook) for more details. If you want to quickly update your code without using any new functionality:

Change your existing code, e.g.

scr <- screenSuspects(fGroups, suspectList, ...)
fGroupsScr <- groupFeaturesScreening(fGroups, scr)

to

fGroupsScr <- screenSuspects(fGroups, suspectList, ..., onlyHits = TRUE)

Major changes

Other changes

patRoon 1.1

patRoon 1.0.4

patRoon 1.0.3

patRoon 1.0.2

patRoon 1.0.1

patRoon 1.0

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