Select the ‘Transcription Factors’ tab of the ‘Results Panels’. Each row represents a cluster that combines the results of the related motifs (Motifs tab) or tracks (Tracks tab) or both. This is the most important tab as each row is a transcription factor that is a potential co-regulator of the genes in our network. Explore the enrichment results in the Transcription Factors tabview. The genes with TCF12 peaks in their promoter regions are listed in red under “TargetName”. The first track is ranked number 4 and the second track is ranked number 8. The transcription factor used for this chIP_seq experiment is TCF12. T4 is a track cluster associated with 2 tracks and is highlighted in the table as an example.The 2 tracks are biological replicates (Rep1, Rep2) of a same chIP-seq experiment. Find a ‘ClusterCode’ assigned to more than one track. Select the ‘Tracks’ tab of the ‘Results Panel’. It is a list of all ChIP-seq datasets (or “tracks”) sorted by strongest enrichment from genes inour network. Explore the enrichment results in the Tracks tab. Exercise 3 - Cytoscape/EnrichmentMap using multiple datasetsĪdditional explanation about the results are located at the end of this document and in more detail in the iRegulon reference paper. Step 4 : AutoAnnotate the enrichment map. Module 08 -1 lab - scRNA pathway analysis using g:Profiler. Integrated Assignment Bonus - Automation. PART 5: GSEA (run and create an enrichment map). PART 3: save as Generic Enrichment Map output (NE). PART 2: save as Generic Enrichment Map output (BE). Exercise 3: MORE DETAILS AND SCREENSHOTS. EXERCISE 2 ANSWERS: DETAILED STEPS AND SCREENSHOTS. EXERCISE 1 ANSWERS: DETAILED EXPLANATION AND SCREENSHOTS. EXERCISE 3: QUESTIONS AND STEPS TO FOLLOW. EXERCISE 2: QUESTIONS AND STEPS TO FOLLOW. EXERCISE 1: QUESTIONS AND STEPS TO FOLLOW. Module 6 Lab: GeneMANIA (Cytoscape version). Create a metatargetome using iRegulon and merge 2 networks in Cytoscape. Module 5 Lab 2: Gene Regulation and Motif Analysis Practical Lab / iRegulon. Exercise 6 (optional): Get the iRegulon RUNX1 targets and find the mouse orthologs using g:Orth (from g:Profiler) to create the gmt file used in Exercise 4. CYTOSCAPE TRANSCRIPTION FACTOR HOW TO
Exercise 5: Learning how to run MEME-chip from the MEME suite ( ).Step 4b Optional: Change the edge style of the signature gene-sets:.Exercise 4: Add RUNX1 targets and RUNX1 KO genes on the distal enrichment map.Optional exercise 3c: Repeat the process by building both the Proximal and Distal enrichment maps at the same time.Optional exercise 3b: Repeat the process of building an enrichment map using the proximal data (Proximal_GOBP_greatExportAll.tsv).Optional exercise 3a: AutoAnnotate the enrichment map:.Exercise 3 (optional): Practice building enrichment maps and auto-annotation.Exercise 2 - Build an enrichment map to visualize GREAT results.Perform pathway enrichment - Proximal approach.Exercise 1 - Run pathway analysis using GREAT.Module 5 Lab 1: Gene Regulation and Motif Analysis Practical Lab /chIP-seq.Additional slides about the tools Segway and BEHST presented during the lecture.Practical lab 2: gene list - iREgulon and enrichr/EnrichmentMap.Practical lab 1: chIP_seq data - GREAT and MEME-chIP.Module 4: In-depth Analysis of Networks and Pathways.Step 5 - Step through notebook to run the analysis.Create your first notebook using Docker.Set Up - Option 2 - Docker image with R/Rstudio.Exercise 4 (Optional) - Explore results in GeneMANIA or STRING.Exercise 2 - Post analysis (add drug target gene-sets to the network).Exercise 1 - GSEA output and EnrichmentMap.Exercise 1c (optional) - investigate individual pathways in GeneMANIA or String.Exercise 1c - create EM from results using Baderlab genesets.Exercise 1b - Is specifying the gmt file important?.Exercise 1a - compare different gprofiler geneset size results.Module 3: Network Visualization and Analysis with Cytoscape.
Module 2: Finding Over-represented Pathways (Veronique Voisin).Module 1 - Introduction to Pathway and Network Analysis (Gary Bader).Pre-Workshop Materials and Laptop Setup Instructions.Pathway and Network Analysis of -Omics Data ( May 2021 ).
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