Course Details

  • Date: September 19th, 2018 - September 19th, 2018
  • Time: 8:45 am - 11:00 am
  • Location: Building 37, Room 4041/4107, NIH
  • Presenter(s): Xiaowen Wang (Partek)
  • Course Number: 1001

TOPIC: Single Cell RNA-Seq Data Analysis in Partek Flow

Partek (partek.com) Flow software provides a point-and-click interface for analysis of next -gen sequencing data. Users can customize analysis pathways for sequence alignment, differential expression, QA/QC, variant calling and annotation, clustering, peak calling, statistical analysis and quantification. These pathways can be re-used and shared, resulting  in publication-ready data visualizations.

During this session, attendees will learn how to identify cell populations and detect differentially expressed genes in a simple Single Cell RNA-Seq experiment with the point-and-click interface in Partek Flow. Attendees will work with a set of test data for this tutorial. Please bring a laptop running Google chrome.

– Import count matrix text file

– Filter cells using interactive QA/QC charts

– Filter low expressed genes

– Normalize raw count

– Visualize cell populations using the interactive 3D t-SNE plot

– Overlay gene expression and pathway signatures on the 3D t-SNE plot

– Select and classify cells on the 3D t-SNE plot

– Detect differentially expressed genes between sub populations

– Filter a gene list

– Identify enriched KEGG pathway and/or GO terms

– Visualize cell-level results using heat maps, volcano plots, and violin plots

– Demonstrate how to import fastq files and upstream analysis pipeline on 10X prep kit

To attend this meeting via Webex, please click here:

https://cbiit.webex.com/cbiit/onstage/g.php?MTID=e8fc591c272dbb8074dc7e3f24b1f861f

Course Material 1:  B_cells.txt