Question

quality assessment and preprocessing for tiling array-based CGH data

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Zhi-Qiang Ye ▴ 60

@zhi-qiang-ye-3116

Last seen 10.2 years ago

2008/10/22 Sean Davis <sdavis2 at="" mail.nih.gov="">: > You generally will not want to do any normalization besides a possible > shift of the center. Any linear normalization that affects the slope > of the M vs. A plot or nonlinear normalization will likely decrease > signal. As for quality control, a good, general measure to track is > the dlrs, a robust measure of the standard deviation. > > > dlrs <- > function(x) { > nx <- length(x) > if (nx<3) { > stop("Vector length>2 needed for computation") > } > tmp <- embed(x,2) > diffs <- tmp[,2]-tmp[,1] > dlrs <- IQR(diffs)/(sqrt(2)*1.34) > return(dlrs) > } > > For agilent arrays, most of the dlrs should be around or under 0.2, > generally. However, this might vary a bit based on lab-to-lab > variation. In any case, if there is a significant outlier, that is > suspect. The input to the above function is the log ratios for a > single array arranged in chromosome and position order. Hi, Sean What is the base of the log ratios for input to dlrs, 2, 10 or e? Thanks. ZQ Ye

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ADD COMMENT • link updated 16.1 years ago by Sean Davis 21k • written 16.1 years ago by Zhi-Qiang Ye ▴ 60

score 0 · Answer 1 · 2008-11-08

On Tue, Nov 4, 2008 at 1:13 AM, Zhi-Qiang Ye <yezhiqiang@gmail.com> wrote: > 2008/10/22 Sean Davis <sdavis2@mail.nih.gov>: > > You generally will not want to do any normalization besides a possible > > shift of the center. Any linear normalization that affects the slope > > of the M vs. A plot or nonlinear normalization will likely decrease > > signal. As for quality control, a good, general measure to track is > > the dlrs, a robust measure of the standard deviation. > > > > > > dlrs <- > > function(x) { > > nx <- length(x) > > if (nx<3) { > > stop("Vector length>2 needed for computation") > > } > > tmp <- embed(x,2) > > diffs <- tmp[,2]-tmp[,1] > > dlrs <- IQR(diffs)/(sqrt(2)*1.34) > > return(dlrs) > > } > > > > For agilent arrays, most of the dlrs should be around or under 0.2, > > generally. However, this might vary a bit based on lab-to-lab > > variation. In any case, if there is a significant outlier, that is > > suspect. The input to the above function is the log ratios for a > > single array arranged in chromosome and position order. > > Hi, Sean > > What is the base of the log ratios for input to dlrs, 2, 10 or e? > Thanks. > Sorry to take so long to get back to this. To answer the question, it doesn't matter. However, the cutoff of 0.2 is based on log10. The DLRS approximates a standard deviation, so you can it to determine what you can see on the array to some degree. Sean [[alternative HTML version deleted]]