[BioC] lumi: how is the controlData to be read and used?

[Pan Du]

Hi Gordon,

Sorry for replying late. I think that should work because the
Control_Gene_Profile.txt file basically averaged the negative control
probes. As described in the BeadStudio manual, its background adjustment
basically subtact the mean of negative control probes. But I am not sure
whether BeadStudio did outlier removal or not. Anyway, the results should be
close.
Also I will update lumiR function (or write a new function) to read the
Control_Probe_Profile.txt because the negative control probes have the same
probe Ids. Thanks!


Pan



On 10/28/07 9:03 PM, "Gordon Smyth" <smyth at wehi.EDU.AU> wrote:

> At 10:17 PM 28/10/2007, Pan Du wrote:
>> What I mean here for the using of control Probe data is using control Probe
>> information for the quality control information. For the background
>> adjustment part, currently, we believe using the BeadStudio recommended
>> method works well. Of course further improvement is possible. The
>> contribution in this part is very welcome.
> 
> OK, good, now we're getting somewhere. You're recommending
> BeadStudio's global background correction. Let me now rephrase my
> original question. Suppose that I have BeadStudio output data which
> is not background corrected. How can I use R to reproduce the
> background correction that BeadStudio would have done?
> 
> This is a very important question, because most Bioconductor users of
> the lumi package will I guess have Illumina output data which is not
> normalized and not background corrected. And we will not necessarily
> want to go back to BeadStudio to background correct.
> 
> I have summary probe profile data output from BeadStudio which is not
> background corrected. Let me repeat, it is not background corrected.
> 
>    Sample_Probe_Profile.txt
> 
> I also have control probe summary profiles and control gene summary
> profiles. This includes both positive and negative control probes:
> 
>    Control_Probe_Profile.txt
>    Control_Gene_Profile.txt
> 
> I should surely be able to reproduce BeadStudio's background
> correction. Here is my best effort using the lumi package. Is this
> what you recommend?
> 
>    library(lumi)
>    x <- lumiR("Sample_Probe_Profile.txt")
>    controlgp <- lumiR("Control_Gene_Profile.txt")
>    x at controlData <- as.data.frame(exprs(controlgp))
>    xb <- lumiB(x,method="bgAdjust")
>    y <- lumiT(xb,method="vst")
>    y <- lumiN(y,method="quantile")
> 
> As you can see from the results below, lumiB() simply subtracted the
> negative control expression value from the expression values for each array.
> 
> Best wishes
> Gordon
> 
> 
>> exprs(controlgp)[,1:4]
>                      1957998084_A 1957998084_B 1957998084_C 1957998084_D
> biotin                   11508.6      10857.9      10641.8      10536.3
> cy3_hyb                  20252.0      19227.1      18964.8      19457.2
> high_stringency_hyb      47593.1      43267.2      43966.6      43207.8
> housekeeping             16185.3      14039.6      13277.5      13280.2
> labeling                    85.2         89.5         77.4         80.7
> low_stringency_hyb       17650.5      16441.4      16330.1      16844.8
> negative                    92.0         90.0         83.2         88.1
>> summary(exprs(x)[,1:4])
>    1957998084_A      1957998084_B      1957998084_C      1957998084_D
>   Min.   :   52.9   Min.   :   50.2   Min.   :   48.6   Min.   :   54.1
>   1st Qu.:   86.6   1st Qu.:   84.3   1st Qu.:   78.2   1st Qu.:   82.3
>   Median :   99.0   Median :   96.6   Median :   88.7   Median :   93.9
>   Mean   :  511.4   Mean   :  501.0   Mean   :  400.3   Mean   :  448.0
>   3rd Qu.:  163.9   3rd Qu.:  159.3   3rd Qu.:  138.3   3rd Qu.:  148.9
>   Max.   :59875.4   Max.   :57223.1   Max.   :50414.0   Max.   :49213.6
>> summary(exprs(xb)[,1:4])
>    1957998084_A       1957998084_B       1957998084_C       1957998084_D
>   Min.   :  -39.09   Min.   :  -39.83   Min.   :  -34.64   Min.   :  -34.08
>   1st Qu.:   -5.40   1st Qu.:   -5.73   1st Qu.:   -5.01   1st Qu.:   -5.80
>   Median :    7.05   Median :    6.65   Median :    5.48   Median :    5.76
>   Mean   :  419.47   Mean   :  411.01   Mean   :  317.04   Mean   :  359.90
>   3rd Qu.:   71.95   3rd Qu.:   69.27   3rd Qu.:   55.08   3rd Qu.:   60.77
>   Max.   :59783.48   Max.   :57133.12   Max.   :50330.79   Max.   :49125.42
> 
> 
>