HSLS MolBio Workshops

This workshop briefly overviews bioinformatics concepts and software for interpreting a gene list using pathway and network information. It focuses on software demonstration using 2 HSLS-licensed tools: Correlation Engine and Ingenuity Pathway Analysis (IPA).

Participants will learn how to

• retrieve a list of differentially expressed genes (DEG) associated with a genome-scale experiment such as an RNA-Seq gene expression study ("treatment vs. control,"  "tumor vs. normal," or "infected vs. Mock") by searching gene expression data repositories (NCBI GEO)
• glean mechanistic insights by finding statistically overrepresented terms (biological functions, molecular processes, diseases, etc.) and pathways present in that DEG list
• predict upstream causal regulators (transcription factors, miRNA, etc.)
• retrieve datasets from GEO that show similar or opposite gene expression profiles

Target Audience

Experimental biologists working with human, mouse, or rat tissues and seeking to interpret gene lists generated through omics experiments such as gene expression, protein interactions, and SNP arrays. The software covered in the workshop operates through a user-friendly, point-and-click graphical user interface, so neither programming experience nor familiarity with the command line interface is required.

Powerpoints

• Slides 
• Practice Exercise - differentially expressed genes – SARS-Cov2 infected vs. Mock infected Calu3 cells (GSE147507 series7) generated by CLC Genomics Workbench

Lecture Videos

• Part-1 offered on March 17, 2021
• Part-2 offered on March 17, 2021
• Recording of the past workshop (July 31, 2024)

Data Download

• AI vs DMSO (CE) - differentially expressed genes formatted for CE upload
• AI vs DMSO (IPA)- differentially expressed genes formatted for IPA upload
• Alzheimer's Gene_List - a list of genes without any expression data
• Practice Exercise - a dataset with differentially expressed genes between SARS-Cov-2 infected vs. mock-infected Calu 3 cells 

Software Registration

• BaseSpace Correlation Engine - to identify mechanisms of disease, drug targets, and prognostic or predictive biomarkers.
• Ingenuity Pathway Analysis - to quickly visualize and understand complex 'omics data and perform insightful data analysis and interpretation by placing experimental results within the context of biological systems.
• IPA Desktop Client Installer - this installer will enable you to access IPA like other desktop applications on your computer (though still requiring an internet connection). You will no longer need to launch IPA through a browser and no longer need to install Java.
• Transfac/f-Match - a database of eukaryotic transcription factors, their genomic binding sites, and DNA-binding profiles.
• BioRender - Scientific illustrations creating tool

Videos

• IPA training videos - important training resources created by Qiagen IPA team
• Fisher Exact Test and Hypergeometric Distribution (StatQuest)
• False Discovery Rate Calculation Explained (StatQuest) 
• FDR calculation in IPA explained

Documentations

• IPA Tutorial: Gene Expression Analysis
• Best Practices for Expression for expression data analysis using IPA
• FAQ on IPA Statistical Calculations
• IPA Upstream Regulator: the IPA Upstream Regulator analytic is to identify the cascade of upstream transcriptional regulators that can explain the observed gene expression changes in a user’s dataset, which can help illuminate the biological activities occurring in the tissues or cells being studied.
• Statistics behind Correlation Engine 

• Correlation Engine Tool - a tool to identify mechanisms of disease, drug targets, and prognostic or predictive biomarkers.
• IPA Target Explorer - search IPA knowledgebase 
• Transfac/f-Match (geneXplain) - access GeneXplain Transfac database
• Gene Ontology - the world’s largest source of information on the functions of genes.
• KEGG -  a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies.
• Reactome Pathway - a biological pathway database for human
• Venn Diagram Creator - With this tool you can calculate the intersection(s) of a list of elements. It will generate a textual output indicating which elements are in each intersection or are unique to a certain list.
• BioRender - Scientific illustrations creating tool

Featured Articles

• Martin, B., Gabris-Weber, B. A., Reddy, R., Romero, G., Chattopadhyay, A. and Salama, G. (2018). Relaxin reverses inflammatory and immune signals in aged hearts. Plos One 13(1), e0190935. 
• Chaparala S, Iwema CL, Chattopadhyay A. SARS-CoV-2 Infections - Gene Expression Omnibus (GEO) Data Mining, Pathway Enrichment Analysis, and Prediction of Repurposable Drugs/Compounds. September 2020. doi:10.20944/preprints202009.0459.v1
• Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102, 15545–15550 (2005). 

• Chaparala, S.; Iwema, C.L.; Chattopadhyay, A. SARS-CoV-2 Infections - Gene Expression Omnibus (GEO) Data Mining, Pathway Enrichment Analysis, and Prediction of Repurposable Drugs/Compounds. Preprints 2020, 2020090459 (doi: 10.20944/preprints202009.0459.v1).

Key References

• Kupershmidt, I. et al. Ontology-based meta-analysis of global collections of high-throughput public data. PLoS ONE 5, (2010).
• Pulikkan, J. A. et al. CBFβ-SMMHC Inhibition Triggers Apoptosis by Disrupting MYC Chromatin Dynamics in Acute Myeloid Leukemia. Cell 174, 172-186.e21 (2018). 

Publications citing Correlation Engine (77), IPA (1110) from Pitt researchers (google scholar, as of February 05,2023)

Attribution

Please include the following statement in the acknowledgments section for all publications, posters, and presentations: 

[Software name] licensed through the Molecular Biology Information Service of the Health Sciences Library System, University of Pittsburgh (RRID:SCR_011975) was used for data analysis.

Feedback

• Please evaluate this workshop

Support

• Request for consultation w/ HSLS-MBIS
• Qiagen Bioinformatics