[BioC] Using linear models to find differential gene expression (NGS)
Naomi Altman
naomi at stat.psu.edu
Wed Sep 1 15:23:10 CEST 2010
I think that you need to start by learning some elementary
statistics. There are lots of good books out there.
I like the ones by Ott (or Ott and Longnecker) and by Devore and
Peck. Read a few pages a day, work through the examples in the text
and you'll
be much better equipped to handle your analyses in about 3 weeks.
--Naomi
At 08:25 AM 9/1/2010, Johnny H wrote:
>Hi.
>I have found some R/Bioconductor/Genominator code on the web (below) and it
>measures differential expression of RNA-seq short read data using a general
>linear model.
>
>Can someone explain some basic questions I have?
>
>1) What is the reason for using 2 glm's for measuring differential
>expression?
>
>2) In the function(y) there are two linear models ran; one with argument y ~
>groups and the other with argument y ~ 1. Why do this?
>
>3) What does the offset do?
>
>4) Why use ANOVA; is to compare the linear models?
>
>5) What can we say about results, if adjusted for multiple testing; how
>would you explain a significant result?
>
>6) Would an adjusted p-value of <= 0.05 be significant?
>
>Basically, I don't know much about the statistics done below and any advice
>or pointers to good literature for this would be a great help. Thank you.
>
> > head(geneCountsUI)
> mut_1_f mut_2_f wt_1_f wt_2_f
>YAL069W 0 0 0 0
>YBL049W 19 18 10 4
>
># Normalisation of RNA-seq lanes
>notZero <- which(rowSums(geneCountsUI) != 0)
>upper.quartiles <- apply(geneCountsUI[notZero, ], 2, function(x) quantile(x,
>0.75))
>uq.scaled <- upper.quartiles/sum(upper.quartiles) * sum(laneCounts)
>
># Calculating differential expression
>groups <- factor(rep(c("mut", "wt"), times = c(2, 2)))
>
>pvalues <- apply(geneCountsUI[notZero, ], 1,
> function(y) {
> fit <- glm(y ~ groups, family = poisson(), offset = log(uq.scaled))
> fit0 <- glm(y ~ 1, family = poisson(), offset = log(uq.scaled))
> anova(fit0, fit, test = "Chisq")[2, 5]
>})
>
> [[alternative HTML version deleted]]
>
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Naomi S. Altman 814-865-3791 (voice)
Associate Professor
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
University Park, PA 16802-2111
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