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Bioinformatics Shared Resources
Sanford Burnham Prebys Medical Discovery Institute
About the BSR
Services & Pricing
Systems & Data
GeneSpring demo is available
Here is a link to a well researched article discussing the design and analysis of microarray experiements:
Download presentation from Roy Williams' Feb 7th 2007 Burnham BSR seminar: Microarrays Overview
The shared in-house service for processing illumina microarrays is here:
AffyComp II software:
A free online microarray analysis course from the University of Alabama at Birmingham:
ArrayExpress microarray data repository:
BioConductor open source software for bioinformatics:
Cyber-T statistics program:
ermineJ — Gene Ontology analysis for microarry data:
Gene Expression Omnibus data repository:
Gene Ontology Database:
HDBStat! High Dimension Biology Statistical analysis software:
MAANOVA 2.0 software:
Stanford MicroArray Database:
Current popular techniques (and some not so popular):
: shared resources can help support your GeneSpring needs via remote desktop.
: Cutting edge very large scale data analysis tool. Eg: The sheer volume of large-scale information across multiple types of cancer at different stages of tumor development provides an unprecedented scientific opportunity and at the same time - a daunting challenge for researchers. In this paper we demonstrate the use of NextBio to study cancer across different stages of tumor progression in order to identify biomarkers of tumorigenesis.....
GeneSet enrichment analysis
(GSEA). Tool for detecting differentially expressed pathways between samples. The application automatically creates a zipped results package of graphs, lists and plots. User friendly and well executed.
Non-negative matrix factorisation
(NMF). An incredibly powerful and state-of-the-art clustering algorithm, which is also used for image recognition. Great for categorizing cell lines or tumors on the basis of gene expression data. The software comes as free modules for the R based Bioconductor, or as a plugin for the free package GenePattern. GenePattern is also a rather nice piece of web deployable new software for data analysis, building analysis pipelines and world wide collaboration.
All the data normalisation tools available in R and Bioconductor (about 6 or 7; linear and non-linear) - normalisation results can now be quality controlled using the package
which checks the normalised data for randomly picked gene-to- gene expression pattern correlations (there should be basically none). People like
since it gives a very powerful overview of data processing.
Bioconductor: Open software development for computational biology and bioinformatics Genome Biology
5 2004 R80 Robert C Gentleman and Vincent J. Carey and Douglas M. Bates and Ben Bolstad and Marcel Dettling and
Sandrine Dudoit and Byron Ellis and Laurent Gautier and Yongchao Ge and Jeff Gentry and Kurt Hornik and Torsten Hothorn and Wolfgang
Huber and Stefano Iacus and Rafael Irizarry and Friedrich Leisch Cheng Li and Martin Maechler and Anthony J. Rossini and Gunther Sawitzki and Colin Smith and Gordon Smyth and Luke Tierney and Jean Y. H. Yang and Jianhua Zhang,
Ploner A, Miller LD, Hall P, Bergh J and Pawitan Y. (2005) Correlation test to assess low-level processing of high-density oligonucleotide microarray data. BMC Bioinformatics, 6:80.
Smyth, G. K. (2005). Limma: linear models for microarray data. In:
Bioinformatics and Computational Biology Solutions using R and Bioconductor
, R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds.), Springer, New York, pages 397-420.
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Subramanian, A., Tamayo, P., Mootha V., Mukherjee, S., Ebert, B., Gillette, M., Paulovich. A., Pomeroy, S., Lander, E., Mesirov, J., PNAS 102 43 15545-15550
Jean-Philippe Brunet, Pablo Tamayo, Todd R. Golub, and Jill P. Mesirov
Metagenes and molecular pattern discovery using *matrix
PNAS 2004 101: 4164-4169; published online before print as 10.1073/pnas.0308531101
Background on microarray time course data analysis:
Yu Chuan Tai
Terence P. Speed
(2005) Statistical analysis of microarray time course data. In: DNA Microarrays, U. Nuber (ed.), BIOS Scientific Publishers Limited, Taylor & Francis, 4 Park Square, Milton Park, Abingdon OX14 4RN, Chapter 20. Amazon
Y. C. Tai and T. P. Speed. A multivariate empirical Bayes statistic for replicated microarray time course data. Annals of Statistics, 2005b. To appear.
Links & Downloads:
Roy Williams' Fev. 7th 2007 Burnham BSR Seminar
BeadStudio One Manua
Guide to the Illumina Sentrix analysis package
Beadstudio Two Manual
Manual for the soon to arrive update
Beadstudio normalisation descriptions
Detailed description of what the normalisations in beadstudio actually are and how they do it.
GenePattern is a powerful and free software tool which will apply state of the art analysis to your microarray data. Includes the classic TreeView and Cluster software, as well as the newer GSA (GeneSet Enrichment Analysis) and NMF (Nonnegative Matrix Factorisation).
GSEA Java Desktop Application
User friendly version of the Gene Set Enrichment Analysis tool. Find which pathways are being changed in your array experiements.
Illumina Mouse Manifest File
BeadStation System Manual 2007
Stem Cell Course Lecture#1
Stem Cell Course Lecture#1: Microarray Introduction
Tutorial Data Set
Stem Cell Course tutorial data set
Stem Cell Course Lecture#2
Stem Cell Course Lecture#2. GeneSpring Tutorial.