Meta-analyses of studies of the human microbiota.

Our body habitat-associated microbial communities are of intense research interest because of their influence on human health. Because many studies of the microbiota are based on the same bacterial 16S ribosomal RNA (rRNA) gene target, they can, in principle, be compared to determine the relative importance of different disease/physiologic/developmental states. However, differences in experimental protocols used may produce variation that outweighs biological differences. By comparing 16S rRNA gene sequences generated from diverse studies of the human microbiota using the QIIME database, we found that variation in composition of the microbiota across different body sites was consistently larger than technical variability across studies. However, samples from different studies of the Western adult fecal microbiota generally clustered by study, and the 16S rRNA target region, DNA extraction technique, and sequencing platform produced systematic biases in observed diversity that could obscure biologically meaningful compositional differences. In contrast, systematic compositional differences in the fecal microbiota that occurred with age and between Western and more agrarian cultures were great enough to outweigh technical variation. Furthermore, individuals with ileal Crohn's disease and in their third trimester of pregnancy often resembled infants from different studies more than controls from the same study, indicating parallel compositional attributes of these distinct developmental/physiological/disease states. Together, these results show that cross-study comparisons of human microbiota are valuable when the studied parameter has a large effect size, but studies of more subtle effects on the human microbiota require carefully selected control populations and standardized protocols.

The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome.

BACKGROUND: We present the Biological Observation Matrix (BIOM, pronounced "biome") format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the "ome-ome") grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses. FINDINGS: The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages. CONCLUSIONS: The BIOM file format and the biom-format project are steps toward reducing the "bioinformatics bottleneck" that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.

TopiaryExplorer: visualizing large phylogenetic trees with environmental metadata.

MOTIVATION: Microbial community profiling is a highly active area of research, but tools that facilitate visualization of phylogenetic trees and associated environmental data have not kept up with the increasing quantity of data generated in these studies. RESULTS: TopiaryExplorer supports the visualization of very large phylogenetic trees, including features such as the automated coloring of branches by environmental data, manipulation of trees and incorporation of per-tip metadata (e.g. taxonomic labels). AVAILABILITY: http://topiaryexplorer.sourceforge.net. CONTACT: rob.knight@colorado.edu.

Meeting report of the RNA Ontology Consortium January 8-9, 2011.

This report summarizes the proceedings of the structure mapping working group meeting of the RNA Ontology Consortium (ROC), held in Kona, Hawaii on January 8-9, 2011. The ROC hosted this workshop to facilitate collaborations among those researchers formalizing concepts in RNA, those developing RNA-related software, and those performing genome annotation and standardization. The workshop included three software presentations, extended round-table discussions, and the constitution of two new working groups, the first to address the need for better software integration and the second to discuss standardization and benchmarking of existing RNA annotation pipelines. These working groups have subsequently pursued concrete implementation of actions suggested during the discussion. Further information about the ROC and its activities can be found at http://roc.bgsu.edu/.