Transcriptomics Data Visualization U sing Partek Flow Software

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 ansuman@pitt.edu Sri Chaparala, MS Bioinformatics Specialist Health Sciences Library System University of Pittsburgh chapa28@pitt.edu

2. Workshop Page http://hsls.libguides.com/molbioworkshops/bulkrnaseqclc

3. Bulk RNA-seqCLCGx 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-seqCLCGx Workflow Differential Gene Expressions Raw Reads Venn Diagram Volcano Plot

6. Partek Flow software http://www.partek.com/partek-flow/

7. Software registration@ HSLS MolBio https://hsls.pitt.edu/molbio/software_registration

8. Partek flow software access

9. Partek Flow at Pitthttp://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 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0099625

12. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52778

13. NCBI SRA Dex vs. Unt

14. Import CLCGx generated RNA-seqcount 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 DexvsUntcount matrix data

17. Import DexvsUntcount matrix data Right Click

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

19. Import DexvsUntcount matrix data

20. Import DexvsUntcount 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. Untsamples

27. Filter DE genes

28. Display DE genes in a dot / violin plot

29. Create a heatmapusing 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 “Dexvs.Unt” and “Alb vs. Unt” datasets