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: