Biomedical Engineering Reference
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standards, manual intervention is seldom completely avoidable; our job
is to minimize the effort required.
For the IMI InnoMed PredTox, the necessity for well-annotated data
and unambiguous meta-data was especially apparent during data
analysis. Data sets from the same experimental series were generated in
different laboratories, applying diverse technologies, and then had to be
integrated for cross-platform and cross-study analyses. Therefore, both
the methods and procedures in the laboratories, and the collection and
reporting of meta-data had to be highly standardized. The integrated
data analysis was performed on three levels. First, profi ling data (e.g.
transcriptomics) was integrated with conventional data, for example
histopathology and serum chemistry, to identify expression markers
through phenotypic anchors. Already, this level of integration required
reliable identifi cation of animals, treatment regimen, and derived samples
that were further processed and used in the different laboratories to yield
the said data sets. Second, data from multiple profi ling technologies
together with conventional data were analyzed across the different tissue
types, to identify, for example, how transcriptional changes in the target
organ relate to metabolome changes in serum in dependence of
histopathological outcome. Third, data from multiple compounds
(studies) were integrated to allow for the identifi cation of common
mechanisms between compounds causing similar phenotypic (i.e.
histopathological) endpoints.
In summary, the IMI InnoMed PredTox generated a rich data set that
will be of value to the general public in the evaluations of those highly
parallel profi ling techniques and in the curation and annotation practice
applied using the ISA software suite.
7.5 Acknowledgments
The authors would like to thank all the collaborators who have
contributed to the development of the ISA software suite. Special
acknowledgement goes to the InnoMed PredTox consortium, for the
data sets, and Stephen Marshall, Dorothy Reilly and Stephen Cleaver (of
NIBR's Quantitative Biology Unit, Developmental and Molecular
Pathways Platform) for the NIBR's case study. The ISA software suite
and the BioSharing initiative are currently funded by grants from the
Biotechnology and Biological Sciences Research Council and the Natural
Environment Research Council's Environmental Bioinformatics Centre.
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