Transcript Winter/Spring 2012 - Mouse Genome Informatics

Functional Genomics
http://www.ruf.rice.edu/~metabol/images/genotype.jpg
Winter/Spring 2012
Carol Bult, Ph.D.
Course coordinator
[email protected]
The Jackson Laboratory
Keith Hutchison, Ph.D.
Course co-coordinator
[email protected]
University of Maine
What is Functional Genomics?
• A field of molecular genetics that uses
genome-wide, high-throughput
measurement technologies to understanding
the relationships between genotype and
phenotype
– Genomics, epigenomics, transcriptomics, proteomics
– Computational genomics (data mining)
– Transgenics, targeted mutations, etc.
http://en.wikipedia.org/wiki/Functional_genomics
What topics will this course cover?
• Primary focus:
– Transcriptional profiling using microarrays and
high-throughput sequencing (RNA-Seq)
– Data analysis
• R statistical programming language/environment
• Galaxy sequence analysis workflow system
• Other topics:
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Genome structure and sequence variation
Epigenomics
Bio-ontologies
Proteomics
Metabolomics
How will this course be structured?
• Lectures and readings assigned by instructors
• Assignments and discussion (50% of grade)
• Student project (50% of grade)
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Choose a data set to analyze from several options
Do some background research on the data set
Perform an analysis of the data
Write up the analysis in the format of a scientific
manuscript as if you were submitting the manuscript to
PLOS Computational Biology
• http://www.ploscompbiol.org/home.action
– Oral presentation on the project
• Preliminary results mid-course (15 minutes per student)
• Final presentation at end of course (20 minutes per student)
Who are the instructors?
• Carol Bult (JAX), course coordinator
– Microarrays, Using R, Galaxy
• Keith Hutchison (UM), co-coordinator
– Genome structure/variation
• Gary Churchill (JAX)
– experimental design
• Doug Hinerfeld (JAX)
– next generation sequencing and proteomics
• Judith Blake (JAX)
– bio-ontologies
• Matt Hibbs (JAX)
– mining expression data
• Joel Graber (JAX)
– RNA processing
What resources will be used for this course?
• Class Web Site
– functionalgenomics.wordpress.com
• R Project for Statistical Computing
– http://www.r-project.org/
• Gene Expression Omnibus (GEO) @ NCBI
– http://www.ncbi.nlm.nih.gov/geo/
• Gene Ontology web site
– http://www.geneontology.org/
• Maine Innovation Cloud
– http://www.cloud.target.maine.edu/
For next time
• Read about R
– http://www.r-project.org/
– You might find the following link to Dr. Karl Broman’s into to R
useful:
• http://www.biostat.wisc.edu/~kbroman/Rintro/
• In the next week you will be given an account on the
Maine Innovation Cloud which will give you access to R
– You will need some basic Linux/Unix commands to use the Cloud
• http://code.google.com/edu/tools101/linux/basics.html
• http://www.reallylinux.com/docs/basic.shtml
• Next time…Keith Hutchison will lecture on
– Genome Structure/Sequence Variation