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

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

Bulk RNA-seq CLCGx Workflow

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

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

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

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

Partek flow software access

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

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

Bulk RNA-seq Study http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0099625

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

NCBI SRA Dex vs. Unt

Import CLCGx generated RNA-seq count matrix file into PartekFlow

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

Import DexvsUnt count matrix data

Import DexvsUnt count matrix data Right Click

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

Import DexvsUnt count matrix data

Import DexvsUnt count matrix data Rename samples

Annotate samples with metadata Start Here

Start analyzing the data and create visualization plots in Partek Flow

Browse imported count matrix data

Run PCA 1 2 3

Create sample correlation plots

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

Filter DE genes

Display DE genes in a dot / violin plot

Create a heatmap using hierarchical clustering

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