Question: Human whole genome Codelink arrays and paired analysis
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gravatar for Matthew Neville
12.1 years ago by
Matthew Neville30 wrote:
Hi, This is my first post to this forum and I am right at the bottom of the learning curve when it comes to R but I have a few initial questions. Does anyone have experience with analysing Codelink arrays in R, I see there is a normalisation program which improves on the Codelink software but are there any other considerations I need to take into account ?. Also, my dataset is based on biopsies from 12 individuals taken at 3 time points after they start taking a drug so when looking for differentially expressed genes my most powerful tests would be paired, i.e. paired ttest or repeated measures ANOVA equivalents. However, most analyses seem to be unpaired, does anyone have any advice?. many thanks in advance Matt Matt Neville D.Phil Oxlip Group Oxford Centre for Diabetes,Endocrinology and Metabolism Churchill Hospital Old Road Headington Oxford OX3 7LJ matthew.neville at oxlip.ox.ac.uk TEL: 01865 857289 FAX: 01865 857217
codelink • 465 views
ADD COMMENTlink modified 12.1 years ago by Diego Diez750 • written 12.1 years ago by Matthew Neville30
Answer: Human whole genome Codelink arrays and paired analysis
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gravatar for Diego Diez
12.1 years ago by
Diego Diez750
Japan
Diego Diez750 wrote:
Hi Matt, you can use the codelink package (that I maintain) to background correct and normalize your dataset. For statistical analysis, if you are planning to use for instance, limma, you can use lmFit() with a matrix of intensities that are stored in the Ni slot in the normalized object. For example: # read and pre-processing. foo <- readCodelink() foo <- bkgdCorrect(foo) foo <- normalize(foo) # statistical analysis. ... # linear model step: fit <- lmFit(foo$Ni, ...) ... You can also use the annotation package for the human whole genome chips -available from bioconductor - for reporting a list of differentially expressed genes. I would recommend you to read the codelink vignette for details. If you have any doubt don't hesitate to ask here though. For the statistical part of you mail I'll let others more experienced than me to answer it but a good starting point would be to read the limma user's guide. Best, Diego On Oct 22, 2007, at 8:21 PM, Matthew Neville wrote: > Hi, > > This is my first post to this forum and I am right at the bottom of > the learning curve when it comes to R but I have a few initial > questions. > > Does anyone have experience with analysing Codelink arrays in R, I > see there is a normalisation program which improves on the Codelink > software but are there any other considerations I need to take into > account ?. > > Also, my dataset is based on biopsies from 12 individuals taken at 3 > time points after they start taking a drug so when looking for > differentially expressed genes my most powerful tests would be > paired, i.e. paired ttest or repeated measures ANOVA equivalents. > However, most analyses seem to be unpaired, does anyone have any > advice?. > > many thanks in advance > > Matt > > Matt Neville D.Phil > Oxlip Group > Oxford Centre for Diabetes,Endocrinology and Metabolism > Churchill Hospital > Old Road > Headington > Oxford > OX3 7LJ > matthew.neville at oxlip.ox.ac.uk > TEL: 01865 857289 > FAX: 01865 857217 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/ > gmane.science.biology.informatics.conductor -- Dr. Diego Diez Bioinformatics center, Institute for Chemical Research, Kyoto University. Gokasho, Uji, Kyoto 611-0011 JAPAN diez at kuicr.kyoto-u.ac.jp
ADD COMMENTlink written 12.1 years ago by Diego Diez750
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