Building a "Comparison of Comparisons" Across Multiple Experiments using Meta-Analysis on ROSALIND

In this webinar, Jeremy demonstrates how to set up and explore new insights across multiple comparisons and experiments using ROSALIND's new Meta-Analysis capability. ROSALIND analyzes your full data set to find and cluster the hidden differentially expressed patterns, and provides a deep interpretation for each one, including interactive heat maps, gene lists and pathways. With ROSALIND Meta-Analysis, you can dive right into what is most significant in your experiments. 

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ROSALIND™ is the first ever genomics analysis platform designed specifically for life science researchers and biologists. Attendees of this event should register for a free account on ROSALIND beforehand: 

Who should attend?: Biologists, Genomics Core Professionals, Researchers, Drug Developers, BioInformaticians

How long is the event?: 45 minutes of content with Q&A afterwards
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About the Presenter: Jeremy Davis-Turak, Ph.D 

Jeremy has over 15 years experience in BioInformatics and Computational Biology. He is passionate about helping researchers obtain important insights from their data without the need for programming.

Jeremy Davis-Turak

Written by Jeremy Davis-Turak

Jeremy earned his Ph.D. in Bioinformatics and Systems Biology in the lab of Alexander Hoffmann at UCSD, researching kinetic models of co-transcriptional splicing. In his studies he developed analyses for RNA-seq, nascent RNA-seq, GRO-seq and MNase-seq that were intimately linked with mechanistic models. Jeremy set up the Bioinformatics Core at the San Diego Center for Systems Biology, optimizing pipeline for RNA-seq and ChIP-seq. Jeremy also has extensive experience analyzing gene expression data from his time working in the Neurogenetics Laboratory at UCLA, where he became an expert in the analysis of Microarrays, Weighted Gene Coexpression Network Analysis, pathways analyses, gene set enrichment and motif analysis. His ambitious goal of enabling researchers without programming experience to ask quantitative questions led to the development of web portals featuring tools to query relational databases of expression data (microarray and sequencing) and perform on-the-fly computational analyses.