SP11 - Integrated Bioinformatics - Data analysis, integration, and dissemination

A. Jöcker, Jitao Zhang, Dirk Ledwinka (DKFZ) - former member: Heiko Rosenfelder

This subproject comprises the project-related bioinformatics infra- and infostructure that is required to carry out the experimental processes and to analyse and disseminate the resulting data and information:

• Providing Systems for Laboratory Information Management and Data Administration
• Collection of data from other subprojects
• (Statistical) analysis of raw data from cell-based screens
• Integration of data, and linking to external data sources
• Data visualisation
• Internal and public dissemination (e.g. http://www.LIFEdb.de)
• Contribution to the development of the CA-ML data model (with subproject "QM & Standards") for MIACA, and of a common database for data from cellular assays.

This subproject thus substantially supports the biomedical subprojects of IG-CSG and is the major connection point for data dissemination within and beyond NGFN.

Software for the management of data from cellular screening (SP3) as well as from smaller-scale analysis (SPs 4,7) has been implemented and is in use. Several open source ‘R’ packages have been implemented for the analysis of cell-based screening data. ’ScratchIt‘ facilitates an image analysis of high content screening microscopy images from wound healing assays and the statistical analysis of derived data.

The ScratchIt package is able to derive the width of scratches (before and after wound-healing, with or without further perturbations) even from overexposed images (left).

The Bioconductor ’RTCA‘ package has been established for the analysis and visualization of data from impedance measurements using an xCELLigence cell analysis system and has been applied to a data set within a human kinome screen that analyzed the dynamic phenotypes of siRNA-transfected cells. for the transfer of protein- and microRNA interactions from external data sources in ‘R’ – ‘KEGGgraph’ (Zhang 2009), ‘RpsiXML’ und ‘mirNet’ - and for the analysis of qRT-PCR data ‘ddCt’ ‘R’ packages have been implemented. These packages cover most of the statistical analysis of cellular screens that are carried out within the consortium.