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After filtering chimeric and eukaryotic sequences from the data, the number of sequences per surface sampled ranged from 26,221 - 76,656. Open-reference clustering at 97% similarity resulted in 12,554 OTUs (OTU is a proxy for microbial "species".) This exceeds the number of species observed by Venkateswaran _et al._ 2014, which is not surprising, given the increased sampling depth in this study (~1 million versus ~ 50,000 high-quality sequences.) Our study also observed 3 notable, qualitative differences from Venkateswaran at al 2014. First, in their study, more than 90% of all sequences were assigned to 4 bacterial genera (_Corynebacterium_, _Propionibacterium_, _Staphylococcus_, and _Streptococcus_), while in our study, they comprised only 24% of the data (9.6%, 0.05%, 10.7%, and 3.6%, respectively). Second, they found no evidence of Archaea in their samples, even when interrogating with Archaeal-specific primers, but we did find evidence for a very low-abundance archaeal presence (2335 sequences, from 3 archaeal phyla). Finally, despite the fact that they were able to culture many spore-forming organisms from their samples, they observed no sequence data from spore-forming organisms. However, we found a large percentage of sequences from spore-forming organisms (20.9% Bacilli and 9.6% Clostridia) in our data. These differences are potentially due to differences in PCR primers and/or DNA extraction method, both of which have known taxonomic biases\cite{Brooks_2015}.  The 19 most abundant Orders found in our study, representing 93.8% of the data (Figure PieChart), are predominately comprised of human-associated organisms (Table habitat). This is not surprising, as the only source of microbial influx is via occasional crew and cargo deliveries onboard aboard  spacecraft that have been stringently cleaned to avoid microbial contamination. There were no obvious apparent  biogeographical patterns onboard on  the ISS. ISS surfaces.  That is, there were no significant differences between samples obtained from the different modules (crew, lab, Node2) (crew vs lab)  or different surface types (keyboards, vents, or  handheld mics). This can be visualized in Figure NMDS_ISS_only, in which each point represents one of the 15 samples, and the distance between samples indicates the overall difference in community composition. In Panel A, the metric used to calculate the distance between samples is the Bray-Curtis dissimilarity, and in Panel B, an alternative distance metric (Unifrac) is used, which takes into account the phylogenetic distance between the OTUs in samples. For the most part, all 15 samples form a tight cluster on the NMDS plots, but there is one sample, the starboard crew vent, that appears distinct from all of the other samples in Panel A. In Panel B, that same sample, as well as the aft lab vent sample appear separate from the others. In order to visualize which OTUs are contributing the most to the uniqueness of those samples, we looked at the overall distribution of the most abundant bacterial families in those samples. The three most abundant families in the starboard crew vent sample are Bacteroidaceae, Ruminococcaceae, and Verrumicrobiaceae (comprising 60.1% of all sequences); and the three most abundant families in the aft lab vent sample are Rikenellaceae, Bacteroidales S24-7, and Lactobacillaceae (comprising 60% of all sequences). In Figure ISS_only_SP78_abundant, the relative abundance of these six families in all 15 samples from the ISS provides a clear indication that they are driving the distinctiveness of those two samples.  ##Comparison to the microbial communities of homes on Earth  The ISS  Unlike the ISS, homes on Earth are exposed to a variety of sources of microbes, including the outside air, tracked-in soil, plants, and pets. ##Comparison to the microbial communities of homes on Earth and from the Human Microbiome Project