Major data analysis errors invalidate cancer microbiome findings
University of East Anglia · Johns Hopkins University · +2 more institutions
Abstract
ABSTRACT We re-analyzed the data from a recent large-scale study that reported strong correlations between DNA signatures of microbial organisms and 33 different cancer types and that created machine-learning predictors with near-perfect accuracy at distinguishing among cancers. We found at least two fundamental flaws in the reported data and in the methods: (i) errors in the genome database and the associated computational methods led to millions of false-positive findings of bacterial reads across all samples, largely because most of the sequences identified as bacteria were instead human; and (ii) errors in the transformation of the raw data created an artificial signature, even for microbes with no reads…
Citation impact
- FWCI
- 28.86
- Percentile
- 100%
- References
- 33
Authors
9Topics & keywords
- Microbiome
- Cancer
- Dozen
- Human Microbiome Project
- Data science
- Human microbiome
- Biology
- Computational biology