1. Transcriptomics Data Visualization Using Partek Flow Software
Mar 27, 2019
Ansuman Chattopadhyay, PhD
Asst Director, Molecular Biology information service
Health sciences library system
University of pittsburgh
Sri Chaparala, MS
Bioinformatics Specialist
Health Sciences Library System
University of Pittsburgh

2. Workshop Page

3. Bulk RNA-seq CLCGx Workflow

4. Bulk RNA-seq workshop topics
Brief introduction to RNA-Seq experiments
Analyze RNA-seq data
Dexamethasone treatment on airway smooth muscle cells (Himes et al. PLos One 2014)
Download seq reads from EBI-ENA/NCBI SRA
Import reads to CLC Genomics Workbench
Align reads to Reference Genome
Estimate expressions in the gene level
Estimate expressions in the transcript isoform level
Statistical analysis of the differential expressed genes and transcripts
Create Heat Map, Volcano Plots, and Venn Diagram

5. Bulk RNA-seq CLCGx Workflow
Differential Gene Expressions
Raw Reads
Venn Diagram
Volcano Plot

6. Partek Flow software

7. Software registration@ HSLS MolBio

8. Partek flow software access

9. Partek Flow at Pitt http://partek.crc.pitt.edu/
Access from outside
Pitt Network --
Use Pulse Secure

10. Partek Flow basics
FASTQ Reads
Circular node : Data
Rectangle: Task

11. Bulk RNA-seq Study

13. NCBI SRA
Dex vs. Unt

14. Import CLCGx generated RNA-seq count matrix file into PartekFlow

15. Access to CRC-HTC Cluster – CLC Server
If you DO NOT HAVE CRC-HTC account:
Use the following for a limited access
UserID: hslsmolb
PW: library1#
Server host: clcbio-stage.crc.pitt.edu
Server port: 7777
If you have CRC-HTC account
Use – pitt user name; pitt password
Server host: clcbio-stage.crc.pitt.edu
Server host: 7777

16. Import DexvsUnt count matrix data

17. Import DexvsUnt count matrix data
Right Click

18. Import DexvsUnt Count Matrix data
Select Name and Total Counts
for each sample

19. Import DexvsUnt count matrix data

20. Import DexvsUnt count matrix data
Rename samples

21. Annotate samples with metadata
Start Here

22. Start analyzing the data and create visualization plots in Partek Flow

23. Browse imported count matrix data

24. Run PCA 1 2 3

25. Create sample correlation plots

26. Run DESeq2 to get differentially expressed genes between Dex vs
Run DESeq2 to get differentially expressed genes between Dex vs. Unt samples

27. Filter DE genes

28. Display DE genes in a dot / violin plot

29. Create a heatmap using hierarchical clustering

30. Hands on exercise
Import “Alb vs. Unt” CLCGx created expression browser dataset into Partek Flow
Create a PCA Plot
Run DESeq2 software and generate a differentially expressed gene list - Alb vs. Unt
Display DE genes in dot or violin plots
Create a heatmap displaying clustered samples in rows and clustered genes in columns
Create a Venn diagram showing overlap between DE genes (p-value <=.05, FC <= -1.5 and >=1.5) produced by “Dex vs.Unt” and “Alb vs. Unt” datasets