R 2.5.0 on openSUSE 10.2 x86_64.
Hi,
I'm using the arrayQuality package to analyse 3 44k Agilent CGH arrays
with the
aim of identifying regions of gain/loss.
With the HTML report generated using the agQuality function i'm not
getting the
coloured loess curve on the MA plot for raw M. Additionally i'm only
getting 1
value for the dot plot of controls normalized M values (-)3xLv1
(n=330) and
likewise for the control A values. Alternatively when I run the
maQualityPlots
function on my mraw object created in marray I get these but don't
get the
comparative box plot.
Firstly is this important as I'm unsure of how useful the comparative
boxplots
are as some values are NA? Secondly is this an appropriate tool to use
and are
there any others that may be of more use both for quality control and
for
analysis further down the line? Thankyou kindly for any input.
Regards
John
jhs1jjm at leeds.ac.uk wrote:
> R 2.5.0 on openSUSE 10.2 x86_64.
>
> Hi,
>
> I'm using the arrayQuality package to analyse 3 44k Agilent CGH
arrays with the
> aim of identifying regions of gain/loss.
>
> With the HTML report generated using the agQuality function i'm not
getting the
> coloured loess curve on the MA plot for raw M. Additionally i'm only
getting 1
> value for the dot plot of controls normalized M values (-)3xLv1
(n=330) and
> likewise for the control A values. Alternatively when I run the
maQualityPlots
> function on my mraw object created in marray I get these but don't
get the
> comparative box plot.
>
> Firstly is this important as I'm unsure of how useful the
comparative boxplots
> are as some values are NA? Secondly is this an appropriate tool to
use and are
> there any others that may be of more use both for quality control
and for
> analysis further down the line? Thankyou kindly for any input.
Hi, John. Are these CGH arrays or expression arrays? The two
probably
need some different treatment. You imply you are using CGH arrays in
looking for regions of gain/loss. Is this the case?
Sean
Sean Davis wrote:
> jhs1jjm at leeds.ac.uk wrote:
>> R 2.5.0 on openSUSE 10.2 x86_64.
>>
>> Hi,
>>
>> I'm using the arrayQuality package to analyse 3 44k Agilent CGH
arrays with the
>> aim of identifying regions of gain/loss.
>>
>> With the HTML report generated using the agQuality function i'm not
getting the
>> coloured loess curve on the MA plot for raw M. Additionally i'm
only getting 1
>> value for the dot plot of controls normalized M values (-)3xLv1
(n=330) and
>> likewise for the control A values. Alternatively when I run the
maQualityPlots
>> function on my mraw object created in marray I get these but don't
get the
>> comparative box plot.
>>
>> Firstly is this important as I'm unsure of how useful the
comparative boxplots
>> are as some values are NA? Secondly is this an appropriate tool to
use and are
>> there any others that may be of more use both for quality control
and for
>> analysis further down the line? Thankyou kindly for any input.
>
> Hi, John. Are these CGH arrays or expression arrays? The two
probably
> need some different treatment. You imply you are using CGH arrays
in
> looking for regions of gain/loss. Is this the case?
And, then, of course, there is the subject, "Agilent CGH data"--SORRY!
In this case, you do not want to rely on loess or other non-linear
normalization methods. Also, the MA plots for the best arrays DO show
a
positive slope--this is totally expected and sought after. In other
words, with higher M-values, we expect higher A-values.
We have found that a pretty good measure of quality of CGH arrays is
the
dlrs:
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)
}
Run this on the Log ratios (ordered by chromosome and position). Good
values are less than 0.2 or so, but even some slightly higher can be
used.
As for analysis, you may want to look into the snapCGH package, as it
allows multiple analyses to be run with the same data structures.
Sean
Quoting Sean Davis <sdavis2 at="" mail.nih.gov=""> on Tue 25 Sep 2007
17:50:10 BST:
> Sean Davis wrote:
> > jhs1jjm at leeds.ac.uk wrote:
> >> R 2.5.0 on openSUSE 10.2 x86_64.
> >>
> >> Hi,
> >>
> >> I'm using the arrayQuality package to analyse 3 44k Agilent CGH
arrays
> with the
> >> aim of identifying regions of gain/loss.
> >>
> >> With the HTML report generated using the agQuality function i'm
not
> getting the
> >> coloured loess curve on the MA plot for raw M. Additionally i'm
only
> getting 1
> >> value for the dot plot of controls normalized M values (-)3xLv1
(n=330)
> and
> >> likewise for the control A values. Alternatively when I run the
> maQualityPlots
> >> function on my mraw object created in marray I get these but
don't get
> the
> >> comparative box plot.
> >>
> >> Firstly is this important as I'm unsure of how useful the
comparative
> boxplots
> >> are as some values are NA? Secondly is this an appropriate tool
to use and
> are
> >> there any others that may be of more use both for quality control
and for
> >> analysis further down the line? Thankyou kindly for any input.
> >
> > Hi, John. Are these CGH arrays or expression arrays? The two
probably
> > need some different treatment. You imply you are using CGH arrays
in
> > looking for regions of gain/loss. Is this the case?
>
> And, then, of course, there is the subject, "Agilent CGH data"--
SORRY!
>
> In this case, you do not want to rely on loess or other non-linear
> normalization methods. Also, the MA plots for the best arrays DO
show a
> positive slope--this is totally expected and sought after. In other
> words, with higher M-values, we expect higher A-values.
>
> We have found that a pretty good measure of quality of CGH arrays is
the
> dlrs:
>
> 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)
> }
>
> Run this on the Log ratios (ordered by chromosome and position).
Good
> values are less than 0.2 or so, but even some slightly higher can be
used.
>
> As for analysis, you may want to look into the snapCGH package, as
it
> allows multiple analyses to be run with the same data structures.
>
> Sean
>
Hi Sean,
I'd been using the loess method with the marray package, I was going
by a paper
i'd read regarding Agilent feature extraction software vs other pre
processing
methods (Zahurak et al 2007 I think). The MA plot for the raw
intensities does
show a positive slope, in this case which normalization method should
I use?
I ran dlrs and got the following:
> qual <- dlrs(CNA.object[,3])
> qual
[1] 0.5586258
> qual2 <- dlrs(CNA.object[,4])
> qual2
[1] 0.5778217
> qual3 <- dlrs(CNA.object[,5])
> qual3
[1] 0.5625572
As you can see I used the CNA.object for which you kindly provided a
function to
separate the ch from location and order them. Having done that I
realized that
the log to ratios I'd used are from the mnorm object (mnorm at maM), I
went back
and created a second CNA.object as follows:
> CNA.object2 <-
CNA(logratio,agilentInfo$chromosome,agilentInfo$location,data.type="lo
gratio")
and then got the following:
> qual <- dlrs(CNA.object2[,3])
> qual
[1] 0.5802947
> qual2 <- dlrs(CNA.object2[,4])
> qual2
[1] 0.6258332
> qual3 <- dlrs(CNA.object2[,5])
> qual3
[1] 0.5925305
Does this mean the quality of the arrays is poor? How would I go about
referencing this (for my dissertation)?
Thanks again
John
Quoting jhs1jjm at leeds.ac.uk on Tue 25 Sep 2007 20:55:53 BST:
> Quoting Sean Davis <sdavis2 at="" mail.nih.gov=""> on Tue 25 Sep 2007
17:50:10 BST:
>
> > Sean Davis wrote:
> > > jhs1jjm at leeds.ac.uk wrote:
> > >> R 2.5.0 on openSUSE 10.2 x86_64.
> > >>
> > >> Hi,
> > >>
> > >> I'm using the arrayQuality package to analyse 3 44k Agilent CGH
arrays
> > with the
> > >> aim of identifying regions of gain/loss.
> > >>
> > >> With the HTML report generated using the agQuality function i'm
not
> > getting the
> > >> coloured loess curve on the MA plot for raw M. Additionally i'm
only
> > getting 1
> > >> value for the dot plot of controls normalized M values (-)3xLv1
(n=330)
> > and
> > >> likewise for the control A values. Alternatively when I run the
> > maQualityPlots
> > >> function on my mraw object created in marray I get these but
don't get
> > the
> > >> comparative box plot.
> > >>
> > >> Firstly is this important as I'm unsure of how useful the
comparative
> > boxplots
> > >> are as some values are NA? Secondly is this an appropriate tool
to use
> and
> > are
> > >> there any others that may be of more use both for quality
control and
> for
> > >> analysis further down the line? Thankyou kindly for any input.
> > >
> > > Hi, John. Are these CGH arrays or expression arrays? The two
probably
> > > need some different treatment. You imply you are using CGH
arrays in
> > > looking for regions of gain/loss. Is this the case?
> >
> > And, then, of course, there is the subject, "Agilent CGH data"--
SORRY!
> >
> > In this case, you do not want to rely on loess or other non-linear
> > normalization methods. Also, the MA plots for the best arrays DO
show a
> > positive slope--this is totally expected and sought after. In
other
> > words, with higher M-values, we expect higher A-values.
> >
> > We have found that a pretty good measure of quality of CGH arrays
is the
> > dlrs:
> >
> > 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)
> > }
> >
> > Run this on the Log ratios (ordered by chromosome and position).
Good
> > values are less than 0.2 or so, but even some slightly higher can
be used.
> >
> > As for analysis, you may want to look into the snapCGH package, as
it
> > allows multiple analyses to be run with the same data structures.
> >
> > Sean
> >
> Hi Sean,
>
> I'd been using the loess method with the marray package, I was going
by a
> paper
> i'd read regarding Agilent feature extraction software vs other pre
> processing
> methods (Zahurak et al 2007 I think). The MA plot for the raw
intensities
> does
> show a positive slope, in this case which normalization method
should I use?
>
> I ran dlrs and got the following:
>
> > qual <- dlrs(CNA.object[,3])
> > qual
> [1] 0.5586258
> > qual2 <- dlrs(CNA.object[,4])
> > qual2
> [1] 0.5778217
> > qual3 <- dlrs(CNA.object[,5])
> > qual3
> [1] 0.5625572
>
> As you can see I used the CNA.object for which you kindly provided a
function
> to
> separate the ch from location and order them. Having done that I
realized
> that
> the log to ratios I'd used are from the mnorm object (mnorm at maM),
I went back
> and created a second CNA.object as follows:
>
> > CNA.object2 <-
> CNA(logratio,agilentInfo$chromosome,agilentInfo$location,data.type="
logratio")
>
> and then got the following:
>
> > qual <- dlrs(CNA.object2[,3])
> > qual
> [1] 0.5802947
> > qual2 <- dlrs(CNA.object2[,4])
> > qual2
> [1] 0.6258332
> > qual3 <- dlrs(CNA.object2[,5])
> > qual3
> [1] 0.5925305
>
> Does this mean the quality of the arrays is poor? How would I go
about
> referencing this (for my dissertation)?
>
> Thanks again
>
> John
>
> _______________________________________________
> 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
>
Sean,
Don't worry about the normalization question. I've seen that this is
dealt with
in the snapCGH vignette so will look at that.
Regards
John
