ArticleJournal of the American Statistical Association2025
Integrative analysis of microbial 16S gene and shotgun metagenomic sequencing data improves statistical efficiency in testing differential abundance.
Article in Journal of the American Statistical Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- 16S rRNA Gene and Metagenomic Analysis Revealed an Association Between Cecal Microbiota and Pork Umami.Animals : an open access journal from MDPI · 2026Article
- Current progresses and challenges for microbiome research in human health: a perspective.Frontiers in cellular and infection microbiology · 2024Article
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8 authors.
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Abstract
The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Surprisingly, many microbiome studies have performed both experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, suggesting that an integrative analysis of both datasets could enhance the testing power for these signatures. However, differential experimental biases, partially overlapping samples, and uneven library sizes pose tremendous challenges when combining the two datasets. In this article, we introduce the first method of this kind, named Com-2seq, that combines the two datasets for testing differential abundance at the genus level as well as the community level while overcoming these difficulties. Our simulation studies demonstrate that Com-2seq substantially enhances statistical efficiency over analysis of a single dataset and outperforms two
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