[aroma.affymetrix] Dealing with batches

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[aroma.affymetrix] Dealing with batches

Peter Savas
Dear Group,

I have 28 samples of tumour normal pairs, run on 2 GenomeWideSNP6.0 arrays several months apart. Some of the pairs have members on different chips (ie tumor on one, normal on the other). I am not sure about the best way to normalise the data such that these split pairs can be used for downstream analysis. The plan is for ASCRMA, TumorBoost and then PSCBS.

I have applied ASCRMA to each array separately. Probe density plots pre and post this normalisation are attached. It seems that there is still some room for improvement.

Thank you and all the best for the new year.

Regards,
Peter

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Re: [aroma.affymetrix] Dealing with batches

Pierre Neuvial-2
Dear Peter,

First, just to make sure we are talking about the same things, when
you write "I have applied ASCRMA to each array separately.", you mean
that you applied ASCRMA(v2) to each of the two *batches* separately,
right ?  In the aroma-project world, we usually reserve the word
'array' for what you called a 'sample'.

Then, let me recall or clarify that ASCRMA(v2) processes each or the
28 samples separately.  Therefore, it would make no difference you
applied ASCRMAv2 on a single data set of 28 samples, or to two
separate data sets, ...or to 28 separate data sets.  This is why
ASCRMA(v2) is called a "single-array" method.

From the density plots, it seems to me that the normalization was able
to make the intensity distributions more similar, which is a good sign
that part of the experimental variability has been removed.  However,
I would like to emphasize that we do not expect these distributions to
be strictly identical after normalization (as would be the case if we
were performing quantile normalization).  In fact, some of the
differences we see after normalization may correspond to true
biological signal.

At first sight it seems to me that it is safe to use your normalized
data for downstream analysis.

If you want to dig further, one thing you could do is to plot these
densities for the normal samples only.  There, we do not expect much
biological variation in the densities.  If there is still clear
variation between the two batches, then one possibility to reduce it
could be to force the "average" density of the normal samples of the
two batches to be identical.  The transformation used for the normal
samples of each batch could then be used to normalize the other
samples of that batch.

I hope this will help you.

Best,

Pierre



On Tue, Jan 5, 2016 at 7:32 AM, Peter Savas <[hidden email]> wrote:

> Dear Group,
>
> I have 28 samples of tumour normal pairs, run on 2 GenomeWideSNP6.0 arrays
> several months apart. Some of the pairs have members on different chips (ie
> tumor on one, normal on the other). I am not sure about the best way to
> normalise the data such that these split pairs can be used for downstream
> analysis. The plan is for ASCRMA, TumorBoost and then PSCBS.
>
> I have applied ASCRMA to each array separately. Probe density plots pre and
> post this normalisation are attached. It seems that there is still some room
> for improvement.
>
> Thank you and all the best for the new year.
>
> Regards,
> Peter
>
> --
> --
> When reporting problems on aroma.affymetrix, make sure 1) to run the latest
> version of the package, 2) to report the output of sessionInfo() and
> traceback(), and 3) to post a complete code example.
>
>
> You received this message because you are subscribed to the Google Groups
> "aroma.affymetrix" group with website http://www.aroma-project.org/.
> To post to this group, send email to [hidden email]
> To unsubscribe and other options, go to http://www.aroma-project.org/forum/
>
> ---
> You received this message because you are subscribed to the Google Groups
> "aroma.affymetrix" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to [hidden email].
> For more options, visit https://groups.google.com/d/optout.

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--
When reporting problems on aroma.affymetrix, make sure 1) to run the latest version of the package, 2) to report the output of sessionInfo() and traceback(), and 3) to post a complete code example.


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Re: [aroma.affymetrix] Dealing with batches

Peter Savas
Thanks very much Pierre.

Apologies for my confusing use of terminology. I do indeed mean that I applied ASCRMA(v2) to each batch separately.

Regards,
Peter



On Tuesday, January 5, 2016 at 9:22:06 PM UTC+11, Pierre Neuvial wrote:
Dear Peter,

First, just to make sure we are talking about the same things, when
you write "I have applied ASCRMA to each array separately.", you mean
that you applied ASCRMA(v2) to each of the two *batches* separately,
right ?  In the aroma-project world, we usually reserve the word
'array' for what you called a 'sample'.

Then, let me recall or clarify that ASCRMA(v2) processes each or the
28 samples separately.  Therefore, it would make no difference you
applied ASCRMAv2 on a single data set of 28 samples, or to two
separate data sets, ...or to 28 separate data sets.  This is why
ASCRMA(v2) is called a "single-array" method.

From the density plots, it seems to me that the normalization was able
to make the intensity distributions more similar, which is a good sign
that part of the experimental variability has been removed.  However,
I would like to emphasize that we do not expect these distributions to
be strictly identical after normalization (as would be the case if we
were performing quantile normalization).  In fact, some of the
differences we see after normalization may correspond to true
biological signal.

At first sight it seems to me that it is safe to use your normalized
data for downstream analysis.

If you want to dig further, one thing you could do is to plot these
densities for the normal samples only.  There, we do not expect much
biological variation in the densities.  If there is still clear
variation between the two batches, then one possibility to reduce it
could be to force the "average" density of the normal samples of the
two batches to be identical.  The transformation used for the normal
samples of each batch could then be used to normalize the other
samples of that batch.

I hope this will help you.

Best,

Pierre



On Tue, Jan 5, 2016 at 7:32 AM, Peter Savas <<a href="javascript:" target="_blank" gdf-obfuscated-mailto="5RjfDe-DDwAJ" rel="nofollow" onmousedown="this.href=&#39;javascript:&#39;;return true;" onclick="this.href=&#39;javascript:&#39;;return true;">psa...@...> wrote:

> Dear Group,
>
> I have 28 samples of tumour normal pairs, run on 2 GenomeWideSNP6.0 arrays
> several months apart. Some of the pairs have members on different chips (ie
> tumor on one, normal on the other). I am not sure about the best way to
> normalise the data such that these split pairs can be used for downstream
> analysis. The plan is for ASCRMA, TumorBoost and then PSCBS.
>
> I have applied ASCRMA to each array separately. Probe density plots pre and
> post this normalisation are attached. It seems that there is still some room
> for improvement.
>
> Thank you and all the best for the new year.
>
> Regards,
> Peter
>
> --
> --
> When reporting problems on aroma.affymetrix, make sure 1) to run the latest
> version of the package, 2) to report the output of sessionInfo() and
> traceback(), and 3) to post a complete code example.
>
>
> You received this message because you are subscribed to the Google Groups
> "aroma.affymetrix" group with website <a href="http://www.aroma-project.org/" target="_blank" rel="nofollow" onmousedown="this.href=&#39;http://www.google.com/url?q\75http%3A%2F%2Fwww.aroma-project.org%2F\46sa\75D\46sntz\0751\46usg\75AFQjCNGgFm4_bwjITDRdF-uORwY5SRzKjA&#39;;return true;" onclick="this.href=&#39;http://www.google.com/url?q\75http%3A%2F%2Fwww.aroma-project.org%2F\46sa\75D\46sntz\0751\46usg\75AFQjCNGgFm4_bwjITDRdF-uORwY5SRzKjA&#39;;return true;">http://www.aroma-project.org/.
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When reporting problems on aroma.affymetrix, make sure 1) to run the latest version of the package, 2) to report the output of sessionInfo() and traceback(), and 3) to post a complete code example.
 
 
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