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@gordon-smyth
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WEHI, Melbourne, Australia
> Date: Wed, 8 Aug 2012 19:55:11 +0200 > From: Amos Kirilovsky <amos.kirilovsky at="" gmail.com=""> > To: Matthew Ritchie <mritchie at="" wehi.edu.au=""> > Cc: bioconductor at r-project.org > Subject: Re: [BioC] Limma, arrayWeights and fold change > > Dear Matt, > > Thank you very much for your answer. I'm glad the function works with > biological replicates. Concerning the other points, you said that one > group is more consistent than the other one. When this appears, can > arrayWeights introduce a bias (more than if not using the function)? If > yes, what can I do? No, there is no bias. > Moreover, if I use logFC to make heatmap or anything else, should I use > logFC as estimated when using arrayWeights or should I use the regular fold > change? Naturally you should use the logFC using arrayWeights, because they take into account the differential quality and the arrays and are therefore more accurate. > My quality controls and arrayWeights showed that some arrays have poor > quality. ArrayWeights allow me to keep them when detecting differentially > expressed genes. Is there a way to take into account the quality when doing > other tests as clustering, correlations... ? Almost all limma functions automatically use the estimated weights. Functions in other packages will generally not do so. Gordon > Best, > > Amos > > > 2012/8/4 Matthew Ritchie <mritchie at="" wehi.edu.au="">: >> Dear Amos, >> >>> I'm using the limma package and the arrayWeights function to make some >>> transcriptomic analysis: One group of samples versus an another group. >>> arrayWeights allow me to get very interesting results but in >>> documentation it says you need replicates. Are they technical or/ and >>> biological replicates? I couldn't find clearly the information. >> >> Ideally biological replicates. Technical replicates are handled by other >> functions in limma, such as duplicateCorrelation(). >> >>> My second question is: can arrayWeights introduce some bias? for >>> example in one of my analysis with 2 groups and 5 samples by group, >>> the weights found by arrayWeights are: >>> for the 1st group : 2.91 0.99 0.43 2.18 0.89 >>> for the 2nd group : 1.40 1.24 0.29 1 .40 0.60 >>> It seems that the weights are in general higher for the first group. >>> Is that a problem? >> >> This would indicate that the first group of arrays are on average more >> consistent than the second group of arrays. >> >>> Next in limma, when Weights calculated by arrayWeights are implemented >>> to the the lmFit function how are calculated the log2 fold change >>> (coefficients ) ? >>> I tried to calculate them by myself applying the weights to the >>> samples but I couldn't get the same results. >>> I observed that the average expression of each probe with or without >>> applying the weights is equal with the function topTable. Is that >>> normal? >> >> The weights are used in gene-wise weighted least squares regression to >> estimate the coefficients in the linear model. So they will affect the >> logFC values. They are not used in the calculation of average expression, >> so these value won't be affected by the use of weights. >> >> I hope this helps. Best wishes, >> >> Matt >> ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
Clustering probe limma GLAD Clustering probe limma GLAD • 808 views
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