What is it about?

There is a huge variety of computational methods coming out recently that each claim to be the best at detecting pathogens (ie bacteria/viruses). We apply multiple tools to real and computer simulated data sets that resemble human tissue. Because we know what to expect in each sample, we can measure how each tool does. We combine the top performing steps into a workflow that can be applied to other samples of a similar nature in future.

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Why is it important?

We don't yet fully understand the interaction between our bodies and the germs that naturally inhabit them. This is of particular interest for cancer research where certain bugs may cause cancer. Now we have an approach that we have evaluated and performs well, we can use this to begin characterising this relationship.


It is hoped that this method can be used to uncover amazing facts about pathogens and cancer and hopefully eventually to improve how we treat cancer.

Abraham Gihawi
University of East Anglia

This is the first time that a large array of tools have been tested to see which is best in data that was derived from human tissue. It has the potential to improve our ability to make associations between pathogens and human disease.

Professor Daniel S. Brewer
University of East Anglia

Read the Original

This page is a summary of: SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines, October 2019, Springer Science + Business Media, DOI: 10.1186/s13059-019-1819-8.
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