Microbiome & multi-omics / Differential taxa bar chart
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Each feature (taxon or merged rank) is converted to relative abundance and compared between groups with the Kruskal–Wallis test. With more than two groups, by default the “enriched” group (highest mean) must also differ significantly from every other group in pairwise Wilcoxon rank-sum tests, so the hits are features raised specifically in one group.
Bar length is the effect size: the log2 ratio of the enriched group’s mean relative abundance to the mean of the other groups (with a 0.0001% pseudocount to avoid division by zero); colour shows the enriched group. With two groups the bars diverge: right = higher in the second group, left = higher in the first.
The effect size here is a log fold ratio, not the LDA score of LEfSe; the screening idea is similar but the numbers are not interchangeable. The table lists means, statistics, P and adjusted P for every feature tested, so you can apply your own criteria.
Rare features have little power and are easily driven by a single sample, so by default only features with mean relative abundance ≥ 0.1% are tested.
Kruskal–Wallis and Wilcoxon rank-sum tests match scipy.stats.kruskal / mannwhitneyu; multiple-testing correction matches R p.adjust. The screening follows the idea of Segata N. et al. (2011) Genome Biology 12:R60, but the effect size is a log2 ratio of means rather than an LDA score.
Up to 50,000 features.
Send us your data and research question and you will receive a written plan within 1 working day: analysis steps, parameter rationale, deliverables and timeline. Quoted per project.