GTPB

The Gulbenkian Training Programme in Bioinformatics


GTPB runs at the Instituto Gulbenkian de Ciência on a yearly basis since 1999.
More than 1000 course attendees in 9 years
Pedro Fernandes, GTPB organizer

Microarray Data Analysis using R and

Bioconductor

MDARB08 - course website

IMPORTANT DATES
Deadline for applications: September 8th, 2008
Course date: September 29th - October 3rd 2008

Instructors:

Nuno Barbosa-Morais graduated in Technologic Physics Engineering from Instituto Superior Técnico (Lisbon, Portugal) in 2000. He completed a Graduate Program in Biophysics and Biomedical Engineering at the University of Lisbon and then did his PhD in Biomedical Sciences at the University of Lisbon Medical School with Professor Carmo Fonseca. Most of the PhD research actually took place at the University of Cambridge (UK) with Dr. Samuel Aparicio. He also visited the lab of Juan Valcarcel at EMBL (Heidelberg, Germany). His PhD work involved bioinformatics studies on the complexity of splicing and gene expression. Nuno is currently a Research Associate in the Computational Biology Group, Department of Oncology of the University of Cambridge (UK), based at the CRUK Cambridge Research Institute. His main research is focused on understanding the complexity of gene expression regulation and its impact on disease mechanisms, namely oncogenesis. Nuno is particularly interested in the systems-level transcriptional mechanisms underlying mammalian cell specification (often perturbed in carcinomas). His work in determining the molecular mechanisms responsible for the stability of transcriptional programs involves the analysis, annotation and integration of different sorts of array (namely expression and ChIP-chip) and sequence information. Nuno has been developing a general pipeline for microarray probe reannotation. He is also contributing with microarray analysis and sequence annotation for projects such as the profiling of CpG islands, the gene expression profiling of pediatric malignant germ cell tumors and the determination of protozoan spliceosomal components.
University of Cambridge, Cambridge, UK

Christina Curtis completed a BSc (Departmental and College Hons) in Molecular, Cellular and Developmental Biology at the University of California, Los Angeles (USA) in 2001. She was the recipient of a Deutscher Akademischer Austausch Dienst Fellowship, which enabled her to pursue a MSc in Molecular Biology at the University of Heidelberg (Germany). In 2003, she began a PhD in Molecular and Computational Biology at the University of Southern California (USA) with Simon Tavaré. Her doctoral work focused on the analysis of high-density oligonucleotide gene expression data with application to understanding the molecular mechanisms of aging and cancer. Christina is currently a postdoctoral fellow in the Computational Biology Group (Department of Oncology) at the University of Cambridge (UK). Christina's research interests include: Developing analysis tools for massively parallel single molecule haplotyping and methylation techniques with applications to stem cell biology; developing inference techniques for the integrative analysis of various forms of high throughput biological information including gene expression, transcription factor binding site occupancy, genotype, and copy number; the analysis of microarray data to identify biomarkers of disease and genotype-phenotype associations; issues concerning the low-level analysis of various microarray technologies, in particular Affymetrix GeneChips.
University of Cambridge, Cambridge, UK

Mark Dunning graduated from the University of York (Uk) with a BSc in Mathematics and Computer Science. He then studied a one-year MSc course in Data Analysis, Networks and Nonlinear Dynamics at York before commencing a PhD in the Computational Biology Group, Department of Oncology at the University of Cambridge. Mark has been heavily involved in the development of statistical and computational tools for the analysis of Illumina bead-based microarrays, and is responsible for the development of the `beadarray` Bioconductor software. His research interests include development of low-level diagnositic tools for the analysis of Illumina data (with particular application to large-scale expression studies), adapting existing microarray algorithms to the unique properties of Illumina arrays and optimising the intrepretation of Illumina data via improved annotation.
University of Cambridge, Cambridge, UK

Course Description

This course aims to introduce researchers to a multidisciplinary approach to microrray data analysis. Particular attention is devoted to the design of microarray experiments, data normalization and quality control as well as to statistical analysis. Participants might find the provided basic training invaluable for: how to approach designing microarray experiments planned in their lab; gaining knowledge and understanding of microarray analysis and quality issues; gaining confidence in performing preprocessing, quality assessment, and differential expression and downstream analysis using the limma program and other R libraries in Bioconductor. The course covers a wide range of platforms and more specific topics, such as the analysis of Illumina, Affymetrix and Array CGH data.
Target audience: All aspects of the course are aimed at non-statisticians, suitable for beginners in microarrays as well as those who have already been working in genomics. The course may also be useful to computational biologists new to microarray analysis. The course is intensive so a highly motivated group of trainees, looking forward to dealing with microarray data in the near future, is expected.


Course Timetable(provisional):

MDARB08 Microarray Data Analysis using R and Bioconductor
Mon Sep 29
Day #1
09:30 - 11:00 Lecture: Introduction to MA Software, Exploratory Data Analysis
11:00 - 11:30 Coffee Break
11:30 - 12:30 Lecture: Normalisation, Quality Assessment
12:30 - 14:00 Lunch Break
14:00 - 16:00 Practical: Introduction to R
16:00 - 16:30 Tea Break
16:30 - 18:00 Practical: limma basics
Tue Sep 30
Day #2
09:30 - 11:00 Lecture: Experimental Design
11:00 - 11:30 Coffee Break
11:30 - 12:30 Lecture: Statistics for Differential Expression
12:30 - 14:00 Lunch Break
14:00 - 16:00 Practical: limma basics / limma preprocessing
16:00 - 16:30 Tea Break
16:30 - 18:00 Practical: limma preprocessing
Wed Oct 1
Day #3
09:30 - 11:00 Lecture: Linear models
11:00 - 11:30 Coffee Break
11:30 - 12:30 Lecture: Design matrices
12:30 - 14:00 Lunch Break
14:00 - 16:00 Practical: limma differential expression
16:00 - 16:30 Tea Break
16:30 - 18:00 Practical: limma differential expression
Thu Oct 2
Day #4
09:30 - 11:00 Lecture: Illumina
11:00 - 11:30 Coffee Break
11:30 - 12:30 Practical: Illumina (beadarray)
12:30 - 14:00 Lunch Break
14:00 - 16:00 Lecture: Affymetrix
16:00 - 16:30 Tea Break
16:30 - 18:00 Practical: Affymetrix
Fri Oct 3
Day #5
09:30 - 11:00 Lecture: Downstream Analysis, Clustering, PCA
11:00 - 11:30 Coffee Break
11:30 - 12:30 Practical: Downstream Analysis
12:30 - 14:00 Lunch Break
14:00 - 16:00 Lecture and Practical: Array CGH
16:00 - 16:30 Tea Break
16:30 - 18:00 Lecture: State-of-the-art / future technologies

Pre-requisites: Elementary computing skills. See "Target Audience" in the Course Description box.


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Instituto Gulbenkian de Ciência, Apartado14, 2781-901 Oeiras, Portugal


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Last updated: June 3rd 2008