Dear Xiayu,
I don't quite see the problem. It all seems straightforward. All the
contrasts you have proposed seem simple and sensible. There is no
need
nor possible advantage in subsetting the data.
Best wishes
Gordon
PS. I haven't included you original post in my reply because there
were so
many non-standard characters imbedded in it.
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:4}}
Hi, Gordon
Thank you for letting me know. As Jim suggested, I would just include
everything in one command as below to make it simple. I now understand
that the difference between testing for changed gene over time (the
trend) and testing for diff genes between two exact time points is
(1) to make different contrasts and
(2) to use topTableF(fit) to extract the gene list for the former and
to use topTable(fit, coef=1 or any other number) for the later.
(Correct me if I am wrong, thank you)
contrast <- makeContrasts("mu.0hr-wt.0hr", "mu.6hr-wt.6hr", "mu.24hr-
wt.24hr","wt.6hr-wt.0hr", "wt.24hr-wt.6hr", "wt.24hr-wt.0hr","mu.6hr-
mu.0hr", "mu.24hr-mu.6hr", "mu.24hr-mu.0hr",levels=design)
Thanks,
Xiayu
-----Original Message-----
From: Gordon K Smyth [mailto:smyth@wehi.EDU.AU]
Sent: Tuesday, July 22, 2014 5:26 PM
To: Rao,Xiayu
Cc: Bioconductor mailing list
Subject: time course experiment
Dear Xiayu,
I don't quite see the problem. It all seems straightforward. All the
contrasts you have proposed seem simple and sensible. There is no
need nor possible advantage in subsetting the data.
Best wishes
Gordon
PS. I haven't included you original post in my reply because there
were so many non-standard characters imbedded in it.
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:6}}
On Tue, 22 Jul 2014, Rao,Xiayu wrote:
> Hi, Gordon
>
> Thank you for letting me know. As Jim suggested, I would just
include
> everything in one command as below to make it simple.
It's just convenience. It can be done either way.
> I now understand that the difference between testing for changed
gene
> over time (the trend) and testing for diff genes between two exact
time
> points is
Actually there is no difference between the two from limma's point of
view. You simply compute any contrast of interest to you and then
test
for DE for that contrast.
> (1) to make different contrasts and
> (2) to use topTableF(fit) to extract the gene list for the former
and to
> use topTable(fit, coef=1 or any other number) for the later.
(Correct me
> if I am wrong, thank you)
Actually, given the way you have computed your contrasts, you probably
want to specify coef for any topTable.
Gordon
> contrast <- makeContrasts("mu.0hr-wt.0hr", "mu.6hr-wt.6hr",
> "mu.24hr-wt.24hr","wt.6hr-wt.0hr", "wt.24hr-wt.6hr",
> "wt.24hr-wt.0hr","mu.6hr-mu.0hr", "mu.24hr-mu.6hr",
> "mu.24hr-mu.0hr",levels=design)
>
> Thanks,
> Xiayu
>
>
>
> -----Original Message-----
> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> Sent: Tuesday, July 22, 2014 5:26 PM
> To: Rao,Xiayu
> Cc: Bioconductor mailing list
> Subject: time course experiment
>
> Dear Xiayu,
>
> I don't quite see the problem. It all seems straightforward. All
the
> contrasts you have proposed seem simple and sensible. There is no
need
> nor possible advantage in subsetting the data.
>
> Best wishes
> Gordon
>
> PS. I haven't included you original post in my reply because there
were
> so many non-standard characters imbedded in it.
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:4}}
Hi, Gordon
Thank you very much for information. I see what you meant now. I also
checked to see the difference between topTable and topTableF and
became more familiar with the output.
(1) topTableF has moderated F-statistics, whereas topTable uses
moderated t-statitics.
(2) The log2 fold changes for a specific comparison are the same (i.e.
both are -1.94 for wt.6h-wt.0h), and the average expression values are
the same for a probeset.
(3) Although for the 1st test only 2 contrasts were specified, the
topTableF(fit2,number=Inf,p.value=0.05) gene list should include all
the genes that are significantly different either between 0h and 6h,
or between 0h and 24h, or between 6h and 24h in the wt. That's why it
is said in the user guide that any two contrasts between the three
times would give the same result. Am I correct?
###1. Test for gene change over time in wt
> cont.129 <- makeContrasts("wt.6h-wt.0h"," wt.24h-
wt.6h",levels=design)
> fit2 <- contrasts.fit(fit, cont.129)
> fit2 <- eBayes(fit2)
> topTableF(fit2)
PROBEID SYMBOL GENENAME
ENTREZID wt.6h-wt.0h wt.24h-wt.6h AveExpr F P.Value
adj.P.Val
1436717_x_at Hbb-y hemoglobin Y, beta-like embryonic chain 15135
-1.94629866 -6.329636145 11.0091773 2601.286661
3.95E-16 6.07E-12
###2. Test for gene change between 2 time points
> cont.all <- makeContrasts("mu.0h-wt.0h"," mu.6h-wt.6h"," mu.24h-
wt.24h"," wt.6h-wt.0h"," wt.24h-wt.6h","mu.6h-mu.0h"," mu.24h-
mu.6h",levels=design)
> fit2 <- contrasts.fit(fit, cont.all)
> fit2 <- eBayes(fit2)
> topTable(fit2,coef=4)
PROBEID SYMBOL GENENAME
ENTREZID logFC AveExpr t P.Value adj.P.Val B
1436717_x_at Hbb-y hemoglobin Y, beta-like embryonic chain 15135
-1.94629866 11.0091773 -16.22147355 2.45E-09
8.47E-07 12.0412676
> topTable(fit2,coef=5)
PROBEID SYMBOL GENENAME
ENTREZID logFC AveExpr t P.Value adj.P.Val B
1436717_x_at Hbb-y hemoglobin Y, beta-like embryonic chain 15135
-6.329636145 11.0091773 -52.75450649 3.39E-15
5.14E-11 20.36773133
Thank you for your sharing! I am willing to learn.
Xiayu
-----Original Message-----
From: Gordon K Smyth [mailto:smyth@wehi.EDU.AU]
Sent: Tuesday, July 22, 2014 6:04 PM
To: Rao,Xiayu
Cc: Bioconductor mailing list
Subject: RE: time course experiment
On Tue, 22 Jul 2014, Rao,Xiayu wrote:
> Hi, Gordon
>
> Thank you for letting me know. As Jim suggested, I would just
include
> everything in one command as below to make it simple.
It's just convenience. It can be done either way.
> I now understand that the difference between testing for changed
gene
> over time (the trend) and testing for diff genes between two exact
> time points is
Actually there is no difference between the two from limma's point of
view. You simply compute any contrast of interest to you and then
test for DE for that contrast.
> (1) to make different contrasts and
> (2) to use topTableF(fit) to extract the gene list for the former
and
> to use topTable(fit, coef=1 or any other number) for the later.
> (Correct me if I am wrong, thank you)
Actually, given the way you have computed your contrasts, you probably
want to specify coef for any topTable.
Gordon
> contrast <- makeContrasts("mu.0hr-wt.0hr", "mu.6hr-wt.6hr",
> "mu.24hr-wt.24hr","wt.6hr-wt.0hr", "wt.24hr-wt.6hr",
> "wt.24hr-wt.0hr","mu.6hr-mu.0hr", "mu.24hr-mu.6hr",
> "mu.24hr-mu.0hr",levels=design)
>
> Thanks,
> Xiayu
>
>
>
> -----Original Message-----
> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> Sent: Tuesday, July 22, 2014 5:26 PM
> To: Rao,Xiayu
> Cc: Bioconductor mailing list
> Subject: time course experiment
>
> Dear Xiayu,
>
> I don't quite see the problem. It all seems straightforward. All
the
> contrasts you have proposed seem simple and sensible. There is no
> need nor possible advantage in subsetting the data.
>
> Best wishes
> Gordon
>
> PS. I haven't included you original post in my reply because there
> were so many non-standard characters imbedded in it.
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:6}}
That's right.
Gordon
On Wed, 23 Jul 2014, Rao,Xiayu wrote:
> Hi, Gordon
>
> Thank you very much for information. I see what you meant now. I
also checked to see the difference between topTable and topTableF and
became more familiar with the output.
> (1) topTableF has moderated F-statistics, whereas topTable uses
moderated t-statitics.
> (2) The log2 fold changes for a specific comparison are the same
(i.e. both are -1.94 for wt.6h-wt.0h), and the average expression
values are the same for a probeset.
> (3) Although for the 1st test only 2 contrasts were specified, the
topTableF(fit2,number=Inf,p.value=0.05) gene list should include all
the genes that are significantly different either between 0h and 6h,
or between 0h and 24h, or between 6h and 24h in the wt. That's why it
is said in the user guide that any two contrasts between the three
times would give the same result. Am I correct?
>
> ###1. Test for gene change over time in wt
>> cont.129 <- makeContrasts("wt.6h-wt.0h"," wt.24h-
wt.6h",levels=design)
>> fit2 <- contrasts.fit(fit, cont.129)
>> fit2 <- eBayes(fit2)
>> topTableF(fit2)
> PROBEID SYMBOL GENENAME
ENTREZID wt.6h-wt.0h wt.24h-wt.6h AveExpr F P.Value
adj.P.Val
> 1436717_x_at Hbb-y hemoglobin Y, beta-like embryonic chain 15135
-1.94629866 -6.329636145 11.0091773 2601.286661
3.95E-16 6.07E-12
>
> ###2. Test for gene change between 2 time points
>> cont.all <- makeContrasts("mu.0h-wt.0h"," mu.6h-wt.6h"," mu.24h-
wt.24h"," wt.6h-wt.0h"," wt.24h-wt.6h","mu.6h-mu.0h"," mu.24h-
mu.6h",levels=design)
>> fit2 <- contrasts.fit(fit, cont.all)
>> fit2 <- eBayes(fit2)
>> topTable(fit2,coef=4)
> PROBEID SYMBOL GENENAME
ENTREZID logFC AveExpr t P.Value adj.P.Val B
> 1436717_x_at Hbb-y hemoglobin Y, beta-like embryonic chain 15135
-1.94629866 11.0091773 -16.22147355 2.45E-09
8.47E-07 12.0412676
>
>> topTable(fit2,coef=5)
> PROBEID SYMBOL GENENAME
ENTREZID logFC AveExpr t P.Value adj.P.Val B
> 1436717_x_at Hbb-y hemoglobin Y, beta-like embryonic chain 15135
-6.329636145 11.0091773 -52.75450649 3.39E-15
5.14E-11 20.36773133
>
>
> Thank you for your sharing! I am willing to learn.
>
> Xiayu
>
>
>
>
>
>
>
> -----Original Message-----
> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> Sent: Tuesday, July 22, 2014 6:04 PM
> To: Rao,Xiayu
> Cc: Bioconductor mailing list
> Subject: RE: time course experiment
>
> On Tue, 22 Jul 2014, Rao,Xiayu wrote:
>
>> Hi, Gordon
>>
>> Thank you for letting me know. As Jim suggested, I would just
include
>> everything in one command as below to make it simple.
>
> It's just convenience. It can be done either way.
>
>> I now understand that the difference between testing for changed
gene
>> over time (the trend) and testing for diff genes between two exact
>> time points is
>
> Actually there is no difference between the two from limma's point
of view. You simply compute any contrast of interest to you and then
test for DE for that contrast.
>
>> (1) to make different contrasts and
>
>> (2) to use topTableF(fit) to extract the gene list for the former
and
>> to use topTable(fit, coef=1 or any other number) for the later.
>> (Correct me if I am wrong, thank you)
>
> Actually, given the way you have computed your contrasts, you
probably want to specify coef for any topTable.
>
> Gordon
>
>> contrast <- makeContrasts("mu.0hr-wt.0hr", "mu.6hr-wt.6hr",
>> "mu.24hr-wt.24hr","wt.6hr-wt.0hr", "wt.24hr-wt.6hr",
>> "wt.24hr-wt.0hr","mu.6hr-mu.0hr", "mu.24hr-mu.6hr",
>> "mu.24hr-mu.0hr",levels=design)
>>
>> Thanks,
>> Xiayu
>>
>>
>>
>> -----Original Message-----
>> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
>> Sent: Tuesday, July 22, 2014 5:26 PM
>> To: Rao,Xiayu
>> Cc: Bioconductor mailing list
>> Subject: time course experiment
>>
>> Dear Xiayu,
>>
>> I don't quite see the problem. It all seems straightforward. All
the
>> contrasts you have proposed seem simple and sensible. There is no
>> need nor possible advantage in subsetting the data.
>>
>> Best wishes
>> Gordon
>>
>> PS. I haven't included you original post in my reply because there
>> were so many non-standard characters imbedded in it.
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:4}}
