Uncovering How False Assumptions of Microbiome Analysis Can Lead to Misinterpretations
In a recently published paper, researchers have uncovered a major flaw in the current methods used for microbiome analyses: they are falsely identifying microbial species. The findings of this study have serious implications for the field, as many of the scientific papers and studies that use these methods will have to be re-evaluated and possibly revised. The research team found that current microbiome analyses tend to over-estimate the number of microbial species present, due to the fact that many of the sequences generated are not true species. The team used a combination of statistical and computational methods to identify and remove these false sequences, and then re-analyzed the data. The results of this re-analysis showed that the number of true species was much lower than previously reported. This means that many of the studies conducted in the past may have been overestimating the microbial diversity present in their samples. The research team hopes that their findings will help to improve the methods used for microbiome analyses and lead to more accurate results in the future.
source: Phys.org