Qiita: rapid, web-enabled microbiome meta-analysis

Abstract

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

Figure 1.

Example meta-analysis in Qiita. A. Unweighted UniFrac PCoA meta-analysis of three studies examining different IBD subtypes, C. difficile patients who underwent FMT, and the HMP1 and iHMP data. B. Only fecal samples from the same studies as in A. C. Fecal samples only from studies that used the same data-generation methods. D. Calculated distances from a healthy plane as described in Ref. 3. Box plots show the median value (center line), the upper and lower quartiles of the data (box edges), maxima and minima (whiskers), and outliers (individual data points). CD, Crohn’s disease; IC, ileal Crohn’s disease; UC, ulcerative colitis; HC, healthy cohort; CCD, colonic Crohn’s disease; ICD_r, ileal Crohn’s disease patients with previous ileocecal resection; ICD_nr, ileal Crohn’s disease patients with no previous ileocaecal resection; post-FMT, patients with C. difficile infection pre-FMT; pre-FMT, patients with C. difficile infection post-FMT.