ArticleBioinformatics (Oxford, England)2023
benchdamic: benchmarking of differential abundance methods for microbiome data.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Maternal and infant gut microbiome.iMeta · 2026Review
- Microbiome differential abundance methodologies to detect relevant taxa associated with chemotherapy toxicity rate in colorectal cancer.Bioinformatics advances · 2026Article
- Revisiting microgenderome: detecting and cataloguing sexually unique and enriched species in human microbiomes.BMC biology · 2024Article
- Article
- lefser: implementation of metagenomic biomarker discovery tool, LEfSe, in R.Bioinformatics (Oxford, England) · 2024Article
- Compositional analysis of microbiome data using the linear decomposition model (LDM).Bioinformatics (Oxford, England) · 2023Article
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Authors and funding
4 authors.
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Abstract
summaryRecently, an increasing number of methodological approaches have been proposed to tackle the complexity of metagenomics and microbiome data. In this scenario, reproducibility and replicability have become two critical issues, and the development of computational frameworks for the comparative evaluations of such methods is of utmost importance. Here, we present benchdamic, a Bioconductor package to benchmark methods for the identification of differentially abundant taxa. AVAILABILITY AND IMPLEMENTATION: benchdamic is available as an open-source R package through the Bioconductor project at https://bioconductor.org/packages/benchdamic/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.