Antonio Gonzalez

TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.

TL;DR: A meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project is presented, creating both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.

TL;DR: It is demonstrated that periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts, and integrative analysis identified microbial, biochemical, and host factors central to this dysregulation.

TL;DR: These findings guide which normalization and differential abundance techniques to use based on the data characteristics of a given study.

TL;DR: A novel sub-operational-taxonomic-unit (sOTU) approach that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms, Deblur, which substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity.