Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry.

MS-based proteomics and metabolomics are rapidly evolving research fields driven by the development of novel instruments, experimental approaches, and analysis methods. Monolithic analysis tools perform well on single tasks but lack the flexibility to cope with the constantly changing requirements and experimental setups. Workflow systems, which combine small processing tools into complex analysis pipelines, allow custom-tailored and flexible data-processing workflows that can be published or shared with collaborators. In this article, we present the integration of established tools for computational MS from the open-source software framework OpenMS into the workflow engine Konstanz Information Miner (KNIME) for the analysis of large datasets and production of high-quality visualizations. We provide example workflows to demonstrate combined data processing and visualization for three diverse tasks in computational MS: isobaric mass tag based quantitation in complex experimental setups, label-free quantitation and identification of metabolites, and quality control for proteomics experiments.

KNIME-CDK: Workflow-driven cheminformatics.

BACKGROUND: Cheminformaticians have to routinely process and analyse libraries of small molecules. Among other things, that includes the standardization of molecules, calculation of various descriptors, visualisation of molecular structures, and downstream analysis. For this purpose, scientific workflow platforms such as the Konstanz Information Miner can be used if provided with the right plug-in. A workflow-based cheminformatics tool provides the advantage of ease-of-use and interoperability between complementary cheminformatics packages within the same framework, hence facilitating the analysis process. RESULTS: KNIME-CDK comprises functions for molecule conversion to/from common formats, generation of signatures, fingerprints, and molecular properties. It is based on the Chemistry Development Toolkit and uses the Chemical Markup Language for persistence. A comparison with the cheminformatics plug-in RDKit shows that KNIME-CDK supports a similar range of chemical classes and adds new functionality to the framework. We describe the design and integration of the plug-in, and demonstrate the usage of the nodes on ChEBI, a library of small molecules of biological interest. CONCLUSIONS: KNIME-CDK is an open-source plug-in for the Konstanz Information Miner, a free workflow platform. KNIME-CDK is build on top of the open-source Chemistry Development Toolkit and allows for efficient cross-vendor structural cheminformatics. Its ease-of-use and modularity enables researchers to automate routine tasks and data analysis, bringing complimentary cheminformatics functionality to the workflow environment.

Extending KNIME for next-generation sequencing data analysis.

SUMMARY: KNIME (Konstanz Information Miner) is a user-friendly and comprehensive open-source data integration, processing, analysis and exploration platform. We present here new functionality and workflows that open the door to performing next-generation sequencing analysis using the KNIME framework. AVAILABILITY: All sources and compiled code are available via the KNIME update mechanism. Example workflows and descriptions are available through http://tech.knime.org/community/next-generation-sequencing. CONTACT: bernd.jagla@pasteur.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

chemalot and chemalot_knime: Command line programs as workflow tools for drug discovery.

BACKGROUND: Analyzing files containing chemical information is at the core of cheminformatics. Each analysis may require a unique workflow. This paper describes the chemalot and chemalot_knime open source packages. Chemalot is a set of command line programs with a wide range of functionalities for cheminformatics. The chemalot_knime package allows command line programs that read and write SD files from stdin and to stdout to be wrapped into KNIME nodes. The combination of chemalot and chemalot_knime not only facilitates the compilation and maintenance of sequences of command line programs but also allows KNIME workflows to take advantage of the compute power of a LINUX cluster. RESULTS: Use of the command line programs is demonstrated in three different workflow examples: (1) A workflow to create a data file with project-relevant data for structure-activity or property analysis and other type of investigations, (2) The creation of a quantitative structure-property-relationship model using the command line programs via KNIME nodes, and (3) The analysis of strain energy in small molecule ligand conformations from the Protein Data Bank database. CONCLUSIONS: The chemalot and chemalot_knime packages provide lightweight and powerful tools for many tasks in cheminformatics. They are easily integrated with other open source and commercial command line tools and can be combined to build new and even more powerful tools. The chemalot_knime package facilitates the generation and maintenance of user-defined command line workflows, taking advantage of the graphical design capabilities in KNIME. Graphical abstract Example KNIME workflow with chemalot nodes and the corresponding command line pipe.