ArticlePloS one2011
Application of two-part statistics for comparison of sequence variant counts.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Citizen Sailors Provide a Detailed Map of Open-Ocean Surface Biodiversity and Help Link eDNA Data to Satellite Observations.Molecular ecology · 2026Article
- Machine learning-enabled chemical ecology for integrated pest management: from volatiles to field applications.Journal of insect science (Online) · 2026Review
- Evaluation of imputation and imputation-free strategies for differential abundance analysis in metaproteomics data.Briefings in bioinformatics · 2025Article
- Comprehensive evaluation of methods for differential expression analysis of metatranscriptomics data.Briefings in bioinformatics · 2023Article
- Rationale and study protocol for a randomized controlled feeding study to determine the structural- and functional-level effects of diet-specific interventions on the gut microbiota of non-Hispanic black and white adults.Contemporary clinical trials · 2022Article
- Comparative Analysis of the Apple Root Transcriptome as Affected by Rootstock Genotype and Brassicaceae Seed Meal Soil Amendment: Implications for Plant Health.Microorganisms · 2021Article
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- Characterization of the Ovine Vaginal Microbiome and Inflammation Patterns as an Improved Testing Model of Human Vaginal Irritation.Frontiers in reproductive health · 2021Article
- Ultrasensitive digital quantification of cytokines and bacteria predicts septic shock outcomes.Nature communications · 2020Article
- The Supragingival Biofilm in Early Childhood Caries: Clinical and Laboratory Protocols and Bioinformatics Pipelines Supporting Metagenomics, Metatranscriptomics, and Metabolomics Studies of the Oral Microbiome.Methods in molecular biology (Clifton, N.J.) · 2019Article
- A specific synbiotic-containing amino acid-based formula restores gut microbiota in non-IgE mediated cow's milk allergic infants: a randomized controlled trial.Clinical and translational allergy · 2019Article
- A latent allocation model for the analysis of microbial composition and disease.BMC bioinformatics · 2018Article
- Negative Binomial Mixed Models for Analyzing Longitudinal Microbiome Data.Frontiers in microbiology · 2018Article
- Molecular analysis of endotracheal tube biofilms and tracheal aspirates in the pediatric intensive care unit.Advances in pediatric research · 2017Article
- Normalization and microbial differential abundance strategies depend upon data characteristics.Microbiome · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Investigation of microbial communities, particularly human associated communities, is significantly enhanced by the vast amounts of sequence data produced by high throughput sequencing technologies. However, these data create high-dimensional complex data sets that consist of a large proportion of zeros, non-negative skewed counts, and frequently, limited number of samples. These features distinguish sequence data from other forms of high-dimensional data, and are not adequately addressed by statistical approaches in common use. Ultimately, medical studies may identify targeted interventions or treatments, but lack of analytic tools for feature selection and identification of taxa responsible for differences between groups, is hindering advancement. The objective of this paper is to examine the application of a two-part statistic to identify taxa that differ between two groups. The advantages of the two-part statistic over common statistical tests applied to sequence count datasets are discussed. Results from the t-test, the Wilcoxon test, and the two-part test are compared using sequence counts from microbial ecology studies in cystic fibrosis and from cenote samples. We show superior performance of the two-part statistic for analysis of sequence data. The improved performance in microbial ecology studies was independent of study type and sequence technology used.
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