NASA GeneLab Chats With Dr Amanda Saravia-Butler: NASA GeneLab Transcriptomic Datasets

Welcome to the “GeneLab Chats” series, a platform designed for insightful discussions with authors of GeneLab-enabled publications.

Within these short but meaningful interviews, GeneLab engages in conversations with these accomplished researchers to glean information that can inspire public viewers on how the GeneLab data system enabled their research endeavors. In this segment, we hear from Dr. Amanda Saravia-Butler of KBR and NASA Ames Research Center.

Comparing large quantities of data and combining datasets from different studies often poses challenges that include technical variation.

In the publication “Batch effect correction methods for NASA GeneLab transcriptomic datasets“ by Dr. Saravia-Butler and colleagues, the authors combine RNA sequencing data from several GeneLab datasets to evaluate five batch-effect correction methods and develop a scoring approach to identify the optimal correction method to use for a specific combined dataset.

GeneLab recently spoke to Dr. Saravia-Butler to hear about this work and to highlight how the Open Science data systems and Analysis Working Groups (AWGs) enabled this publication.

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