Partek Flow Workshop for CCR Scientists at NCI-Frederick
When: Mar. 29th, 2017 2:00 pm - 4:30 pm
To Know
- Where: NCI-F Bldg549, Scientific Library Training Room
- Organized By: BTEP
- Files
About this Class
The CCR Bioinformatics Training and Education Program (BTEP) is pleased to organize a workshop on Partek Flow for scientists at NCI-Frederick.
Partek Flow software is designed specifically for the analysis needs of next generation sequencing (NGS) applications including RNA, small RNA, and DNA sequencing. With an easy-to-use graphical interface, one can perform alignment, quantification, quality control, statistics and visualization for their NGS data.
Date: Wednesday, March 29, 2017
Time: 2:00 - 4:30 pm
Location: NCI-F Building 549, Scientific Library Training Room
Registration is required.
Note: The workshop is limited to 12 seats (10 seats with desktops available for use, and 2 seats for those who can bring their own laptops)
For more information about the venue, please contact:
Alan Doss
Informationist, Scientific Library
Email: dossal@mail.nih.gov
Phone: 301-846-1093
WORKSHOP AGENDA
2:00 - 4:30 pm RNA-Seq Analysis using Partek Flow
Presenter: Eric Seiser, PhD - Partek Field Application Specialist
An overview of getting started on the NIH Helix server and then a live demo of RNA-seq analysis in Partek Flow. The training will highlight key concepts in RNA-seq analysis and their implementation Flow. This will be followed by a hands-on session utilizing Partek Flow to importing raw sequence data in fastq format from a published study, followed by performing QA/QC, alignment, quantification, differential expression detection and finally biological interpretation.
Students will learn how to use basic features of Partek Flow, including:
• Getting set up on NIH Helix server
• Importing data
• Performing QA/AC
• Alignment
• Gene/transcript abundance estimation
• Differential expression detection
• Go Enrichment analysis
• Visualization (PCA, dotplot, volcano plot, chromosome view, hierarchical clustering etc.)
• Microarray analysis and integration with RNA-seq data
• Importing data
• Performing QA/AC
• Alignment
• Gene/transcript abundance estimation
• Differential expression detection
• Go Enrichment analysis
• Visualization (PCA, dotplot, volcano plot, chromosome view, hierarchical clustering etc.)
• Microarray analysis and integration with RNA-seq data