Blobtoolkit: Identification and analysis of non-target data in all Eukaryotic genome projects

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We and others have identified a critical issue with contamination in sequence attribution in genomic sequences in the public databases. To rectify this legacy problem and to reduce its impact on future data submissions we propose a toolkit, BlobToolKit, that aids producers and users in identifying and correctly classifying such data.

How will BlobToolKit impact science and industry?
This work will have impact beyond the purely academic sphere of those generating genome sequences. In particular we envisage impacts in:
* Clinical science and delivery, as pathogens and other possibly harmful species will be correctly identified;
* Food production, where the improvement of methods of fermentation by microbes such as in brewing and cheese manufacture, requires access to accurately attributed sequence data;
* Crop science, as data relevant to invasive and pathogenic species will be available for monitoring, control and eradication programmes;
* Livestock health, as data relevant to emerging threats to production to crop and livestock species from novel or imported pathogens will be available for monitoring and eradication programmes;
* Biofuel species development, where yield optimisation depends upon a clear mechanistic understanding of the genomics of the species to hand and its relatives, free from contaminant sequence
* Drug discovery, where the process of initial lead definition will not be fatally misled by misattributed sequence;
* Bioprospecting, where correct linkage between sequences and the organisms they derive from will speed identification of useful bioactives;
* Biotechnology, where the engineering of synthetic pathways requires accurate identification and characterisation of genomic material to its correct sources.
We also recognise that SMEs are beginning to generate genome assemblies for target species, and BlobToolKit will aid these in generating high-quality data on which future investment can be based. The toolkit will be available under an appropriate open software license, permitting installation on local servers as well as on private cloud computing systems.

How will prospective users become informed about BlobToolKit?
By embedding BlobToolKit in standalone, cloud, and database-proximal versions, and by developing novel interactive visualisations, we will ensure that it has wide uptake and open availability. We will deliver BlobToolKit-enabled assessments of public data via a plugin to the ENA web data services. This will reach tens of thousands of data users per year. By annotating sequences with suspect annotation, we will improve the sequence search results, and interpretation of downloaded data, for many tens of thousands more.

Overall, the toolkit will serve to correct the scientific record at source, and provide an independent measure of data quality and reliability for future reuse.

Ultimately we hope that BlobToolKit will become part of the hidden but essential infrastructure that supports UK and global bioscience, whether academic or commercial. "Users" will realise that the data they are using has been screened by BlobToolKit, and will expect BlobToolKit stamps of credibility on data they access and exploit.