Weighted network analysis

Dates: May 12th and 13th

Location: Leiden University Medical Center, Leiden, The Netherlands
                Albinusdreef 2, 2333 ZA Leiden,
                Building 1, Room:
J1-83
               
Instructor:
Prof Steve Horvath, Department of Biostatistics, UCLA School of Public Health

Description:
This two-day intensive course will cover (weighted) network analysis methods widely used in systems biologic and systems genetic applications. The goal of the network analysis workshop is to familiarize researchers with network methods and software for integrating genomic data sets with complex phenotype data. Participants will learn how to integrate disparate data sets (genetic variation, gene expression, protein interaction networks, complex phenotypes, gene ontology information, DNA methylation) and use networks for identifying disease genes, pathways and key regulators.

Topics
Review of relevant clustering procedures
Weighted correlation network analysis
Module preservation statistics
Consensus module analysis
Network based meta analysis techniques
Network edge orienting and structural equation models Random generalized linear model predictor Network Biology in Neuroscience and Neuropsychiatric Disease

About the instructor:

Steve Horvath is a Professor in Human Genetics and Biostatistics at the University of California, Los Angeles. His group develops and applies biostatistical, computational, and systems biologic data analysis methods. He has published extensively on gene networks, systems biology and data mining methods for genomic data. Recent research has focused on the development and application of systems biologic and systems genetic methods for addressing biological, genetic and clinical questions. This research has also been published in a Springer book entitled "Weighted Network Analysis: Applications in Genomics and Systems Biology".


Program:

Day I (May, 12th)
--------------------
10:00-10:30 Review of hierarchical clustering and dynamic branch cutting
10:30-11:15 Weighted gene co-expression network analysis (Part 1)
11:15-11:30 Coffee break
11:30-12:30 Weighted gene co-expression network analysis (Part 2)
12:30-14:00 Lunch break
14:00-15:15 Module Preservation statistics
15:15-15:30 Coffee break
15:30-16:30 R software tutorial


Day II (May, 13th)
--------------------
10:00-10:30
Review of the material from day 1
10:30-11:15
Consensus network analysis and applications
11:15-11:30 Coffee break
11:30-12:30
Structural equation models and the network edge orienting software
12:30-14:00 Lunch break
14:00-15:15
R software tutorial
15:15-15:30 Coffee break
15:30-16:30 Data analysis
Subpages (1): CourseMaterial