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Journal Article
SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines
2019
Overview
Background
Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathogens amid the plethora of human sequencing reads. In cancer research, the tumorigenic ability of pathogens is being recognized, for example,
Helicobacter pylori
and human papillomavirus in the cases of gastric non-cardia and cervical carcinomas, respectively. As of yet, no benchmark has been carried out on the performance of computational approaches for bacterial and viral detection within host-dominated sequence data.
Results
We present the results of benchmarking over 70 distinct combinations of tools and parameters on 100 simulated cancer datasets spiked with realistic proportions of bacteria. mOTUs2 and Kraken are the highest performing individual tools achieving median genus-level F1 scores of 0.90 and 0.91, respectively. mOTUs2 demonstrates a high performance in estimating bacterial proportions. Employing Kraken on unassembled sequencing reads produces a good but variable performance depending on post-classification filtering parameters. These approaches are investigated on a selection of cervical and gastric cancer whole genome sequences where
Alphapapillomavirus
and
Helicobacter
are detected in addition to a variety of other interesting genera.
Conclusions
We provide the top-performing pipelines from this benchmark in a unifying tool called SEPATH, which is amenable to high throughput sequencing studies across a range of high-performance computing clusters. SEPATH provides a benchmarked and convenient approach to detect pathogens in tissue sequence data helping to determine the relationship between metagenomics and disease.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
/ Alphapapillomavirus - isolation & purification
/ Animal Genetics and Genomics
/ Bacteria
/ Biomedical and Life Sciences
/ Biotechnology & Applied Microbiology
/ Cancer
/ Datasets
/ Genera
/ genome
/ Genomes
/ Helicobacter - isolation & purification
/ Humans
/ medicine
/ Microbial Genetics and Genomics
/ Pipeline
/ SEPATH
/ Taxonomy
/ Tissues
/ Viral
