About this Class

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

Files

• B_cells.txt: |