>From reading the literature it seems that calculating the concordance
correlation coefficient between two normalized arrays is a good
measure of
success of the normalization procedure. Is there a Bioconductor
package that
calculates this?
Secondly, is there a bioconductor function that identifies outlier
spot
intensities among replicate arrays?
Appreciate your response.
Anjan
--
===================================
anjan purkayastha, phd.
research associate
fas center for systems biology,
harvard university
52 oxford street
cambridge ma 02138
phone-703.740.6939
===================================
[[alternative HTML version deleted]]
On Thu, Sep 23, 2010 at 12:44 PM, ANJAN PURKAYASTHA <
anjan.purkayastha@gmail.com> wrote:
> >From reading the literature it seems that calculating the
concordance
> correlation coefficient between two normalized arrays is a good
measure of
> success of the normalization procedure. Is there a Bioconductor
package
> that
> calculates this?
>
Hi, Anjan. The R cor() function can be used to calculate correlation.
> Secondly, is there a bioconductor function that identifies outlier
spot
> intensities among replicate arrays?
>
This is a little vague. However, there are numerous packages for
quality
assessment of microarrays. You might try looking at some of those to
see if
they meet your needs for your experimental setup.
Sean
[[alternative HTML version deleted]]
Correlation is not the same as "concordance correlation".
Correlation measures where two data vectors follow some sort of
straight
line.
Concordance measures whether they follow the identity line.
On 9/23/2010 11:50 AM, Sean Davis wrote:
> On Thu, Sep 23, 2010 at 12:44 PM, ANJAN PURKAYASTHA<
> anjan.purkayastha at gmail.com> wrote:
>
>> > From reading the literature it seems that calculating the
concordance
>> correlation coefficient between two normalized arrays is a good
measure of
>> success of the normalization procedure. Is there a Bioconductor
package
>> that
>> calculates this?
>>
> Hi, Anjan. The R cor() function can be used to calculate
correlation.
>
>
>> Secondly, is there a bioconductor function that identifies outlier
spot
>> intensities among replicate arrays?
>>
> This is a little vague. However, there are numerous packages for
quality
> assessment of microarrays. You might try looking at some of those
to see if
> they meet your needs for your experimental setup.
>
> Sean
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
http://news.gmane.org/gmane.science.biology.informatics.conductor
On Fri, Sep 24, 2010 at 11:21 AM, Kevin R. Coombes <
kevin.r.coombes@gmail.com> wrote:
> Correlation is not the same as "concordance correlation".
>
>
Good point.
>
> Correlation measures where two data vectors follow some sort of
straight
> line.
>
> Concordance measures whether they follow the identity line.
>
>
> On 9/23/2010 11:50 AM, Sean Davis wrote:
>
>> On Thu, Sep 23, 2010 at 12:44 PM, ANJAN PURKAYASTHA<
>> anjan.purkayastha@gmail.com> wrote:
>>
>> > From reading the literature it seems that calculating the
concordance
>>> correlation coefficient between two normalized arrays is a good
measure
>>> of
>>> success of the normalization procedure. Is there a Bioconductor
package
>>> that
>>> calculates this?
>>>
>>> Hi, Anjan. The R cor() function can be used to calculate
correlation.
>>
>>
>> Secondly, is there a bioconductor function that identifies outlier
spot
>>> intensities among replicate arrays?
>>>
>>> This is a little vague. However, there are numerous packages for
>> quality
>> assessment of microarrays. You might try looking at some of those
to see
>> if
>> they meet your needs for your experimental setup.
>>
>> Sean
>>
>> [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> Bioconductor mailing list
>> Bioconductor@stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
[[alternative HTML version deleted]]
Il Sep/23/10 6:44 PM, ANJAN PURKAYASTHA ha scritto:
>> From reading the literature it seems that calculating the
concordance
> correlation coefficient between two normalized arrays is a good
measure of
> success of the normalization procedure. Is there a Bioconductor
package that
> calculates this?
> Secondly, is there a bioconductor function that identifies outlier
spot
> intensities among replicate arrays?
> Appreciate your response.
> Anjan
>
Dear Anjan
I'd be interested to hear what literature that is.
If your statement were correct, then all normalisation methods should
just be replaced by ACE (as has indeed been proposed, see Pubmed-ID
14633397, Faller et al., Normalization of DNA-microarray data by
nonlinear correlation maximization.)
Best wishes
Wolfgang