Studies on the association between certain diseases and the gut microbiome tend to focus on microbial composition – the relative proportion of different species of microbes in a sample.
A new study from EMBL Heidelberg demonstrates a machine learning tool to predict microbial load – the density of microbes in a gut microbial sample – from sequencing data without the need for costly additional experiments.
The study asserts that microbial load is an important factor to consider in disease association studies to avoid false associations or conclusions.
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