Fwd: [BioC] ULYSIS Alexa Fluor labelling kit / dye bias / limma

[Sean Davis]

Begin forwarded message:

> From: Sean Davis <sdavis2 at mail.nih.gov>
> Date: October 1, 2004 1:29:57 PM EDT
> To: "Matthew  Hannah" <Hannah at mpimp-golm.mpg.de>
> Subject: Re: [BioC] ULYSIS Alexa Fluor labelling kit / dye bias / limma
>
> Matt,
>
> Ah, I see what you are saying.  Yes, limma can (and so can many other 
> non-center-based normalization methods like loess) remove the 
> dependence of ratio on amplitude rather nicely.  However, this DOES 
> NOT remove dye bias from any given point.  For example, if one has a 
> spot that has an intensity in the green channel of 200 and 400 in the 
> red channel (for a ratio of 2) and one does the dye swap, the 
> expectation is that the ratio will be 0.5, but for dye-biased spots, 
> the ratio may be 1 (or something other than 0.5).  If this is 
> repeatable, then the spot is said to have dye bias--the expression of 
> the spot is biased by dye.  One can only discover this by looking at 
> at least two arrays, and they must, of course, be in dye swap.  
> Normalization does not account for this effect.
>
> Sean
>
> On Oct 1, 2004, at 1:05 PM, Matthew Hannah wrote:
>
>> Sean,
>> From the limma normalisewithinarrays help
>>
>> This function normalizes M-values (log-ratios) for dye-bias within 
>> each
>> array. Apart from method="none" and method="median", all the
>> normalization methods make use of the relationship between dye-bias 
>> and
>> intensity. The loess normalization methods were proposed by Yang et al
>> (2001, 2002). Smyth and Speed (2003) give a detailed statement of the
>> methods.
>>
>> But I have no idea how this would effect things if there was less/no
>> bias - hence the question.
>>
>> Sorry I remembered reading it but should have mentioned this in the 
>> post
>> rather than being abit vague.
>>
>> Cheers,
>> Matt
>>
>>> -----Original Message-----
>>> From: Sean Davis [mailto:sdavis2 at mail.nih.gov]
>>> Sent: Freitag, 1. Oktober 2004 18:48
>>> To: Matthew Hannah
>>> Subject: Re: [BioC] ULYSIS Alexa Fluor labelling kit / dye
>>> bias / limma
>>>
>>> Matt,
>>>
>>> I don't think limma directly accounts for dye bias in most
>>> (all?) of its normalization methods.  You can't remove dye
>>> bias with a within-slide normalization.  You can remove dye
>>> bias from your analysis using a linear model, but I don't
>>> think that comes in at the normalization level.
>>>
>>> Sean
>>>
>>> On Oct 1, 2004, at 12:33 PM, Matthew Hannah wrote:
>>>
>>>> Hi,
>>>>
>>>> Quick question this time. Basically these dyes have higher
>>> intensity,
>>>> less quenching and correlate more between dye pairs. The ULYSIS kit
>>>> uses chemical labelling which eliminates sequence effects.
>>>>
>>>> http://www.probes.com/servlets/directory?id1=6&id2=48&id3=319
>>>> http://www.probes.com/media/publications/394.pdf
>>>>
>>>> As far as I know Limma accounts for dye bias during
>>> normalisation. If
>>>> there is less/no bias will there be artifacts introduced? Or other
>>>> points I need to be aware of?
>>>>
>>>> Thanks,
>>>> Matt
>>>>
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>>>
>>>
>>>