XiP: a computational environment to create, extend and share workflows.

UNLABELLED: XiP (eXtensible integrative Pipeline) is a flexible, editable and modular environment with a user-friendly interface that does not require previous advanced programming skills to run, construct and edit workflows. XiP allows the construction of workflows by linking components written in both R and Java, the analysis of high-throughput data in grid engine systems and also the development of customized pipelines that can be encapsulated in a package and distributed. XiP already comes with several ready-to-use pipeline flows for the most common genomic and transcriptomic analysis and ∼300 computational components. AVAILABILITY: XiP is open source, freely available under the Lesser General Public License (LGPL) and can be downloaded from http://xip.hgc.jp.

Design and implementation of a hybrid cloud system for large-scale human genomic research.

In the field of genomic medical research, the amount of large-scale information continues to increase due to advances in measurement technologies, such as high-performance sequencing and spatial omics, as well as the progress made in genomic cohort studies involving more than one million individuals. Therefore, researchers require more computational resources to analyze this information. Here, we introduce a hybrid cloud system consisting of an on-premise supercomputer, science cloud, and public cloud at the Kyoto University Center for Genomic Medicine in Japan as a solution. This system can flexibly handle various heterogeneous computational resource-demanding bioinformatics tools while scaling the computational capacity. In the hybrid cloud system, we demonstrate the way to properly perform joint genotyping of whole-genome sequencing data for a large population of 11,238, which can be a bottleneck in sequencing data analysis. This system can be one of the reference implementations when dealing with large amounts of genomic medical data in research centers and organizations.

CSO validator: improving manual curation workflow for biological pathways.

SUMMARY: Manual curation and validation of large-scale biological pathways are required to obtain high-quality pathway databases. In a typical curation process, model validation and model update based on appropriate feedback are repeated and requires considerable cooperation of scientists. We have developed a CSO (Cell System Ontology) validator to reduce the repetition and time during the curation process. This tool assists in quickly obtaining agreement among curators and domain experts and in providing a consistent and accurate pathway database. AVAILABILITY: The tool is available on http://csovalidator.csml.org. CONTACT: masao@hgc.jp.

CSML2SBML: a novel tool for converting quantitative biological pathway models from CSML into SBML.

CSML and SBML are XML-based model definition standards which are developed with the aim of creating exchange formats for modeling, visualizing and simulating biological pathways. In this article we report a release of a format convertor for quantitative pathway models, namely CSML2SBML. It translates models encoded by CSML into SBML without loss of structural and kinetic information. The simulation and parameter estimation of the resulting SBML model can be carried out with compliant tool CellDesigner for further analysis. The convertor is based on the standards CSML version 3.0 and SBML Level 2 Version 4. In our experiments, 11 out of 15 pathway models in CSML model repository and 228 models in Macrophage Pathway Knowledgebase (MACPAK) are successfully converted to SBML models. The consistency of the resulting model is validated by libSBML Consistency Check of CellDesigner. Furthermore, the converted SBML model assigned with the kinetic parameters translated from CSML model can reproduce the same dynamics with CellDesigner as CSML one running on Cell Illustrator. CSML2SBML, along with its instructions and examples for use are available at http://csml2sbml.csml.org.