Machine Learning for RNA-seq Data vs. Statistical DGE Analysis – Utilizing Both for Deeper Insights

About this Class

Join us for an engaging training session where we will examine the similarities and differences between machine learning and statistical differential gene expression (DGE) analysis using Qlucore Omics Explorer. Qlucore Omics Explorer is a point-and-click package available to NCI CCR scientists that enables visualization-based analysis of multi-omics data including RNA-seq, scRNA, proteomics, metabolomics, as well as enabling the use of machine learning to obtain a deeper understanding of data.
 
At the end of this class, participants will
 
·      Have a deeper understanding of RNA-seq data analysis and understand how to leverage both machine learning and statistical methods to obtain more comprehensive insights.
·      Know the different gene selection methods used by machine learning and statistical DGE analysis.
·      Know how integrating machine learning with DGE analysis can provide additional insights and enhance your research findings.
·      Be able to describe steps for applying machine learning to enhance insight extraction from RNA-seq data.
 
Experience using Qlucore Omics Explorer is not needed to attend. Submit a ticket with service.cancer.gov to get this software installed on personal computer.

Meeting information:

https://cbiit.webex.com/cbiit/j.php?MTID=m11ad78fb6a8303d5d72cffe7c9abfb3a 
Meeting number:
2307 302 4819

Join by video system
Dial 23073024819@cbiit.webex.com
You can also dial 173.243.2.68 and enter your meeting number.

Join by phone
1-650-479-3207 Call-in number (US/Canada)
Access code: 2307 302 4819