Schematic diagram of the provenance of a QIIME 2 Visualization.

A: An example of a QIIME 2 visualization illustrating the taxonomic composition of several samples. B: The directed, acyclic graph (DAG) tracing the history of the panel A visualization from initial data import into QIIME 2 through the creation of the visualization (denoted with an asterisk). This DAG can be used for analytical interpretation or publication, and serves as the input to Provenance Replay. Additional detail is provided in panel C on the nodes included in the dashed box. C: A DAG describing the inputs and outputs of the ‘action’ node highlighted in gray. D: “Action details,” captured during the execution of the node highlighted in gray. Some data collected as action details, such as information about the computational environment where the action was run, is not presented in this schematic for readability, but can be observed in the provenance of either of the two QIIME 2 results included in Supporting Information S1. The node selected for panel D was arbitrarily chosen.</p

Turing Way reproducibility classes [7] ordered in a hierarchy based on generality, similar to Gundersen and Kjensmo [8].

Turing Way reproducibility classes [7] ordered in a hierarchy based on generality, similar to Gundersen and Kjensmo [8].</p

qiime2-provenance-replay-code-and-tutorial.

The provenance replay code, as of QIIME 2 2023.9, and a brief usage tutorial with corresponding data. The two.qzv files included in this supplement are “QIIME Zipped Visualization” files. These can be used with QIIME 2 Provenance Replay to generate replay scripts, can be viewed using QIIME 2 View (https://view.qiime2.org), or can be unzipped with any typical unzip utility as they are.zip files with a specific internal structure that enables QIIME 2 to interpret them. (ZIP)</p

Additional file 1: Figure S1. of ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses

Principal Coordinates comparing unsimulated (real) samples based on (a) unweighted UniFrac distances where trees are computed using ghost-tree, (b) weighted UniFrac distances where trees are computed using ghost-tree, (c) unweighted UniFrac distances where trees are computed using ghost-tree, 0-branch length-foundation, (d) weighted UniFrac distances where trees are computed using ghost-tree, 0-branch-length foundation, (e) unweighted UniFrac distances where trees are computed using ghost-tree, 0-branch-length extensions, (f) weighted UniFrac distances where trees are computed using ghost-tree, 0-branch-length extensions. Blue points are simulated and real human saliva samples, and red points are simulated and real restroom surface samples. Plots were made using EMPeror software [25]. (PDF 522 kb

American Gut Project fecal sOTU counts table

The Deblur sOTU counts table for the fecal samples used in the American Gut Project manuscript. The samples were trimmed to a common read length of 125nt, and processed by Deblur (Amir et al mSystems 2017). Blooms were removed (Amir et al mSystems 2017) and any sample with fewer than 1250 sequences was omitted. This table is not rarefied,

movie_s2.mp4

Placing changes in the microbiome in the context of the American Gut. We accumulated samples over sequencing runs to demonstrate the structural consistency in the data. We demonstrate that while the ICU dataset (https://www.ncbi.nlm.nih.gov/pubmed/27602409) falls within the American Gut samples, they do not fall close to most samples at any of the body sites. We then highlight samples from the United Kingdom, Australia, the United States and other countries to show that nationality does not overcome the variation in body site. We then highlight the utility of the American Gut in meta-analysis by reproducing results from (https://www.ncbi.nlm.nih.gov/pubmed/20668239) and (https://www.ncbi.nlm.nih.gov/pubmed/23861384), using the AGP dataset as the context for dynamic microbiome changes instead of the HMP dataset. We show rapid, complete recovery of C. diff patients following fecal material transplantation and also contextualized the change in an infant gut over time until it settles into an adult state. This demonstrates the power of the American Gut dataset, both as a cohesive study and as a context for other investigations

ag_tree.tre

The SEPP (Mirarab et al Pac Symp Biocomput 2012) fragment insertion tree used for phylogenetic analyses

movie_s1.mp4

Longitudinal samples from a large bowel resection. We place longitudinal samples collected prior to and following a large bowel resection in the context of samples from the AGP, the Earth Microbiome Project (https://www.ncbi.nlm.nih.gov/pubmed/29088705), intensive care unit patients (https://www.ncbi.nlm.nih.gov/pubmed/27602409), "extreme" diet samples from (https://www.ncbi.nlm.nih.gov/pubmed/24336217), and samples from the Hadza hunter-gatherers (https://www.ncbi.nlm.nih.gov/pubmed/28839072). Unweighted UniFrac was computed on this sample set, and principal coordinates were assessed. Using EMPeror (https://www.ncbi.nlm.nih.gov/pubmed/24280061), we then animate the plot by connect successive data points gut resection time series, while rotating the data frame. We first show the how the extent of change in the microbial community, and how the samples immediately following surgery resemble fecal samples from ICU patients. In the background of the animation, a black line connects a plant rhizosphere sample to a marine sediment sample, which have the same unweighted UniFrac distance (0.78) as the longitudinal sample immediately preceding and immediately following surgery

Unweighted UniFrac distances

The unweighted UniFrac distance (Lozupone and Knight AEM 2005) matrix of the 9511 fecal samples used in the American Gut paper. UniFrac was computed using Striped UniFrac (https://github.com/biocore/unifrac). Prior to execution of UniFrac, Deblur (Amir et al mSystems 2017) was run on the samples, all bloom sOTUs were removed (Amir et al mSystems 2017), and samples were rarefied to a depth of 1250 reads (Weiss et al Microbiome 2017). For the phylogeny, fragments were inserted using SEPP (Mirarab et al Pac Symp Biocomput 2012) into the Greengenes 13_5 99% OTU tree (McDonald et al ISME 2012)

Full American Gut Project mapping file

The full American Gut Project mapping file, includes non-fecal samples