Microbiome studies continue to provide tremendous insight into the importance of microorganism populations throughout the world. While discovery in this field continues unabated at a breakneck pace, multiple reports have revealed a concerning lack of lab-to-lab and method-to-method reproducibility. This lack of reproducibility stems from highly complex workflows that span multiple scientific domains and provide many opportunities to introduce bias or error. In order to manage microbiome biases and errors, they must first be understood. Once biases and errors are understood, methods of detection and mitigation can be put in place to minimize their influence on conclusions. Michael M. Weinstein, Ph.D., will discuss common causes of microbiome analysis bias, as well as methods of detection and mitigation. Additionally, we are excited to release FIGARO - a bioinformatic application designed to facilitate reproducibility in targeted sequence (such as 16S) analysis, and the MIQ score - a bioinformatic application designed to rapidly and easily detect biases in microbiome analysis when using a mock microbial community standard.
Thursday, September 12 at 3:00pm to 4:00pm
Weill Cornell Medical College, LC-504
1300 York Avenue, New York NY
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