Difference between revisions of "Linear models for Microarray analysis"
From Organic Design wiki
m |
|||
| Line 14: | Line 14: | ||
[[Image:Limma_versions.tiff|thumb|Linear development cycle]] | [[Image:Limma_versions.tiff|thumb|Linear development cycle]] | ||
---- | ---- | ||
| + | ====Object orintated programming environment==== | ||
| + | [[Image:OOP.tiff|thumb]] | ||
| + | [[Category:Sven/Rosaceae]] | ||
| + | |||
| + | ==Scratchpad== | ||
*Essentially t-statistics for each spot/gene | *Essentially t-statistics for each spot/gene | ||
*Uses between gene information in moderated t-statistics | *Uses between gene information in moderated t-statistics | ||
| Line 20: | Line 25: | ||
*benefits/limitations? | *benefits/limitations? | ||
*FDR control? → ranking better than selecting cutoff | *FDR control? → ranking better than selecting cutoff | ||
| − | |||
| − | |||
| − | |||
| − | |||
Revision as of 04:18, 14 March 2006
Contents
Overview of Limma package for R
- Fits a linear model for each spot (gene)
- Focus on normalization and statistical analysis of cDNA microarray gene expression data
- OOP environment for handling information in a microarray experiment
- Statistical analysis approach can be used for Affymetrix microarray experiments
Origin
- Written and maintained by Gordon Smyth with contributions
- From WEHI, Melbourne, Australia
- Software made public at the Australian Genstat Conference, Perth, in Dec 2002
- Became available in the Bioconductor open source bioinformatics project April 2003
- Limma integrates with other Bioconductor software packages, affy, marray, using convert package
- Active development cycle
Object orintated programming environment
Scratchpad
- Essentially t-statistics for each spot/gene
- Uses between gene information in moderated t-statistics
- Computationally fast/robust
- Handles missing information/use defined flag information
- benefits/limitations?
- FDR control? → ranking better than selecting cutoff
