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Thu 30 Jul 2020
11:00 - 13:00

Venue: Bioinformatics Training Facility - Webinar (Time Zone = BST)

Provided by: Bioinformatics


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Inferring Co-Expressing Genes and Regulatory Networks from RNA-Seq Data (Webinar)

Thu 30 Jul 2020

Description

One of the most important tasks of systems biology is to create explanatory and predictive models of complex biological systems. Availability of gene expression data in different conditions has paved the way for reconstructing direct or indirect regulatory connections between various genes and gene products. Most often, we are not interested in single interactions between gene products; instead, we try to reconstruct networks that provide insights into the investigated biological processes.

This webinar will introduce the importance and applications of Gene Expression Datasets (Microarrays and RNA-Seq), followed by methods of extraction and analysis of Co-Expression Networks and Transcriptional Regulatory Networks from these datasets. The webinar will focus on the pros and cons of Weighted and Unweighted Networks, citing examples to aid decisions about which networks to use and when.

The webinar will be presented in the form of a lecture and tutorial with screenshots that enable listeners to emulate the protocols in R. Note that this is a webinar and not a coding exercise. Links to further reading and practice will be shared.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Target audience
  • This webinar is suitable for students and early career researchers with interest in Genomics
  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals.
  • There is no fee charged for this event.
Prerequisites

Co-expression Networks represent a kind of Biological Network. Listeners should have a basic knowledge of Networks. Some familiarity with Gene Expression Datasets and R will be useful to understand methods and interpretations.

Sessions

Number of sessions: 1

# Date Time Venue Trainer
1 Thu 30 Jul   11:00 - 13:00 11:00 - 13:00 Bioinformatics Training Facility - Webinar (Time Zone = BST) Gita Yadav
Topics covered

Transcriptome Datasets, Gene Co-expression Networks, Transcriptional Network Inference, R, Cytoscape

Objectives

After this course you should be able to:

  • Conceptualise your RNA-Seq for Network Analyses
  • Differentiate between Hard and Soft Thresholding
  • Differentiate between Weighted and Unweighted Gene Networks
  • Test significance of gene correlations in your Network using R
  • Construct Gene Regulatory and Co-Expression Networks in R
Aims

During this course you will learn about:

  • How Gene Expression data can be used for Systems Biology
  • Two major kinds of Co-Expression Networks
  • Tips for measuring gene-level correlations in RNA-Seq data
Format

Presentations and demonstrations

Timetable

Times Topics
11:00 - 11:30 Introduction to Transcriptome Datasets, Co-Expression and Gene Regulatory Networks
11:30 - 12:00 Reconstruction of Gene Co-Expression Networks in R
12:00 - 12:15 Reconstruction of Gene Regulatory Networks focusing on Master Regulators
12:15 - 12:30 Visual Aids to interpret Gene Expression Data in R & Cytoscape
12:30 - 13:00 Q & A
13:00  Closure
Duration

2 Hours

Related courses
Theme
Specialized Training

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