Hi,
Thanks for the reply. I've typed in what you suggested for more
information. Done with and without background correction. I don't know
what you are looking for - but hope this helps.
After using RG=backgroundCorrect(RG, method="minimum")
summary(MAmin2$M)
QCmouse..CD4.depl.day.7..260803...590.530..liver.
Min. :0
1st Qu.:0
Median :0
Mean :0
3rd Qu.:0
Max. :0
QCmouse..CD4.depl.day.8..10903.II....590.550..liver.4
Min. :0
1st Qu.:0
Median :0
Mean :0
3rd Qu.:0
Max. :0
QCmouse.liver..CD4.depl..1.6.ug..day.8..670.530..240703
Min. :0
1st Qu.:0
Median :0
Mean :0
3rd Qu.:0
Max. :0
QCmouse.liver.CD4.depl.day.8..10903.I....590.540..
Min. : NA
1st Qu.: NA
Median : NA
Mean : NaN
3rd Qu.: NA
Max. : NA
NA's :31200
>
summary(MAmin2$weights)
QCmouse..CD4.depl.day.7..260803...590.530..liver.
Min. :0.0000
1st Qu.:1.0000
Median :1.0000
Mean :0.9873
3rd Qu.:1.0000
Max. :1.0000
QCmouse..CD4.depl.day.8..10903.II....590.550..liver.4
Min. :0.000
1st Qu.:1.000
Median :1.000
Mean :0.986
3rd Qu.:1.000
Max. :1.000
QCmouse.liver..CD4.depl..1.6.ug..day.8..670.530..240703
Min. :0.0000
1st Qu.:1.0000
Median :1.0000
Mean :0.9762
3rd Qu.:1.0000
Max. :1.0000
QCmouse.liver.CD4.depl.day.8..10903.I....590.540..
Min. :0.0000
1st Qu.:1.0000
Median :1.0000
Mean :0.9878
3rd Qu.:1.0000
Max. :1.0000
>
> summary(cor$cor.genes)
Length Class Mode
0 NULL NULL
>
And not using background correct
> summary(MA1$M)
QCmouse..CD4.depl.day.7..260803...590.530..liver.
Min. :-5.188e+00
1st Qu.:-2.813e-01
Median :-1.425e-02
Mean : 2.424e-02
3rd Qu.: 2.949e-01
Max. : 5.752e+00
NA's : 1.326e+04
QCmouse..CD4.depl.day.8..10903.II....590.550..liver.4
Min. : -5.25729
1st Qu.: -0.24996
Median : -0.03117
Mean : 0.09563
3rd Qu.: 0.35874
Max. : 6.01569
NA's :8209.00000
QCmouse.liver..CD4.depl..1.6.ug..day.8..670.530..240703
Min. :-7.200e+00
1st Qu.:-2.703e-01
Median : 4.189e-03
Mean : 3.571e-02
3rd Qu.: 3.068e-01
Max. : 1.293e+01
NA's : 1.611e+04
QCmouse.liver.CD4.depl.day.8..10903.I....590.540..
Min. :-7.880e+00
1st Qu.:-2.729e-01
Median :-5.434e-04
Mean : 8.506e-02
3rd Qu.: 3.162e-01
Max. : 1.025e+01
NA's : 1.808e+04
>
> summary(MA1$weights)
QCmouse..CD4.depl.day.7..260803...590.530..liver.
Min. :0.0000
1st Qu.:1.0000
Median :1.0000
Mean :0.9873
3rd Qu.:1.0000
Max. :1.0000
QCmouse..CD4.depl.day.8..10903.II....590.550..liver.4
Min. :0.000
1st Qu.:1.000
Median :1.000
Mean :0.986
3rd Qu.:1.000
Max. :1.000
QCmouse.liver..CD4.depl..1.6.ug..day.8..670.530..240703
Min. :0.0000
1st Qu.:1.0000
Median :1.0000
Mean :0.9762
3rd Qu.:1.0000
Max. :1.0000
QCmouse.liver.CD4.depl.day.8..10903.I....590.540..
Min. :0.0000
1st Qu.:1.0000
Median :1.0000
Mean :0.9878
3rd Qu.:1.0000
Max. :1.0000
>
> summary(cor$cor.genes)
Length Class Mode
0 NULL NULL
Thanks,
Helen
-----Original Message-----
From: Gordon Smyth [mailto:smyth@wehi.edu.au]
Sent: 16 April 2004 00:18
To: Helen Cattan
Cc: bioconductor@stat.math.ethz.ch
Subject: Re: [BioC] limma - dupcor.series
At 01:59 AM 16/04/2004, Helen Cattan wrote:
>Hi,
>
>-using Bioconductor v1.8.1 and limma v1.6.1
>When I use backgroundCorrect(minimum) and then dupcor.series I don't
get
>a correlation value (NaN), if I don't use the backgroundCorrect
method
I
>get a value but with a warning message. Does anyone have any
suggestions
>as to what is happening here and how I can sort it out please? (I
>realize the experimental design is hopeless but I have to work with
what
>I'm given). I don't have any missing/blank values but obviously have
>negative values after background subtraction. Code and warning are
given
>below.
>Thanks,
>
>Helen
>
> > files=dir(pattern="*\\.gpr")
> > RG=read.maimages(files, columns=list(Rf="F635 Median", Gf="F532
>Median", Rb="B635 Median", Gb="B532 Median"), wt.fun=wtflags(0))
> > names(RG)
> > RG$genes=readGAL()
> > RG$printer=getLayout(RG$genes)
> > samples=read.table("sampleinformationa.txt", header=TRUE,
sep="\t",
>as.is=TRUE)
> > samples
> > spottypes=readSpotTypes()
> > RG$genes$Status=controlStatus(spottypes, RG)
> > RGmin=backgroundCorrect(RG, method="minimum")
> > MAmin=normalizeWithinArrays(RGmin, RG$printer)
No need to type 'RG$printer', the function will find it automatically.
> > MAmin2=normalizeBetweenArrays(MAmin)
> > design=c(1,1,1,1)
> > cor=dupcor.series(MAmin2$M, design, ndups=2, spacing=1)
>Loading required package: statmod
>
>Attaching package 'statmod':
>
>
> The following object(s) are masked from package:limma :
>
> matvec vecmat
>
> > cor$cor
>[1] NaN
I don't know what the problem is, presumably it is a problem with
method="minimum". Can you please type summary(MAmin2$M),
summary(MAmin2$weights) and summary(cor$cor.genes) to give more
information?
> > MAdef=normalizeWithinArrays(RG, RG$printer)
> > MAdef2=normalizeBetweenArrays(MAdef)
> > design=c(1,1,1,1)
> > cor=dupcor.series(MAdef2$M, design, ndups=2, spacing=1)
>Warning messages:
>1: Too much damping - convergence tolerance not achievable in:
>glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace =
>trace)
>2: Too much damping - convergence tolerance not achievable in:
>glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace =
>trace)
>3: Too much damping - convergence tolerance not achievable in:
>glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace =
>trace)
>[1] 0.7891024
The warnings are no problem.
Gordon