Abstract
Microbiome analyses can be challenging because microbial strains are numerous, and often, confounding factors in the data set are also numerous. Many tools reduce, summarize, and visualize these high-dimensional data to provide insight at the community level. However, they lose the detailed information about each taxon and can be misleading (for example, the well-known horseshoe effect in ordination plots). Thus, multiple methods at different levels of resolution are required to capture the full range of microbial patterns. Here we present Calour, a user-friendly data exploration tool for microbiome analyses. Calour provides a study-centric data model to store and manipulate sample-by-feature tables (with features typically being operational taxonomic units) and their associated metadata. It generates an interactive heatmap, allowing visualization of microbial patterns and exploration using microbial knowledge databases. We demonstrate the use of Calour by exploring publicly available data sets, including the gut and skin microbiota of habitat-switched fire salamander larvae, gut microbiota of Trichuris muris-infected mice, skin microbiota of different human body sites, gut microbiota of various ant species, and a metabolome study of mice exposed to intermittent hypoxia and hypercapnia. In these cases, Calour reveals novel patterns and potential contaminants of subgroups of microbes that are otherwise hard to find. Calour is open source under the Berkeley Software Distribution (BSD) license and available from https://github.com/biocore/calour. IMPORTANCE Calour allows us to identify interesting microbial patterns and generate novel biological hypotheses by interactively inspecting microbiome studies and incorporating annotation databases and convenient statistical tools. Calour can be used as a first-step tool for microbiome data exploration.
Highlights
Microbiome analyses can be challenging because microbial strains are numerous, and often, confounding factors in the data set are numerous
We demonstrate how Calour can be used in five published data sets to identify microbial and metabolite patterns and develop novel biological hypotheses: the effect of habitat switching on the skin and gut microbiome of salamander larvae [12], the gut microbiome in Trichuris murisinfected mice [13], a cross-sectional study of skin microbiome [14], a low-biomass ant gut microbiome study [15], and a longitudinal metabolome study on the effects of intermittent hypoxia and hypercapnia and diet on fecal metabolites in mice [19]
In order to rigorously elucidate this pattern, we used a permutation-based nonparametric differential abundance rank mean test with a discrete false-discovery rate [11] multiple-hypothesis correction implemented in Calour and applied this analysis between pond-only groups (P, P¡P) and stream-only groups (S, S¡S) on gut samples (Fig. 1C) and skin samples, respectively, to identify environment-specific sOTUs
Summary
Microbiome analyses can be challenging because microbial strains are numerous, and often, confounding factors in the data set are numerous. We demonstrate the use of Calour by exploring publicly available data sets, including the gut and skin microbiota of habitatswitched fire salamander larvae, gut microbiota of Trichuris muris-infected mice, skin microbiota of different human body sites, gut microbiota of various ant species, and a metabolome study of mice exposed to intermittent hypoxia and hypercapnia. In these cases, Calour reveals novel patterns and potential contaminants of subgroups of microbes that are otherwise hard to find. Calour is open source under the Berkeley Software Distribution (BSD) license and available from https://github.com/biocore/ calour
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