[BioC] Loop design - biological, technical replication

Maciej Jończyk mjonczyk at biol.uw.edu.pl
Mon Mar 8 09:37:32 CET 2010


Dear dr Smith and list members,

lines l and h are biologically independent.

I think there are three levels of variability:

line (l and h);

temperature (c and k)

and isolation.

I've thought that I can include line and temperature as a fixed effects
and treat isolation as random effect.

I can figure out that I should get into account also array effect.

My main pursues are to get contrasts as I specified and account for
technical replication (isolation).

I think that I should include all of this effects.

I'll try to use maanova package.

Thank you,

Best regards,

Maciej

PS.
Are my previous codes for single channel analysis makes any sense? If I
want to include line and temperature effects only would it be correct? I
just want to make sure, so please write if it is completely wrong.


From: Gordon K Smyth <smyth at ...>
Subject: Re: Loop design - biological, technical replication
Newsgroups: gmane.science.biology.informatics.conductor
Date: 2010-03-07 07:03:29 GMT (1 day, 1 hour and 46 minutes ago)

Dear Maciej,

You don't say, but I assume that lines l and h must be biologically
independent.  If this is true, then your experiment has 3 levels of
variability: line, isolation and array.  limma can only handle 2 levels.
You could analyse data this in limma, treating biol_rep as a blocking
variable, as in Section 8.2 of the User's Guide, but that would ignore
the
fact that h and l are biologically separate.  Otherwise, try the maanova
package.

Best wishes
Gordon

-----------------------------------------------
Associate Professor Gordon K Smyth,
NHMRC Senior Research Fellow,
Bioinformatics Division,
Walter and Eliza Hall Institute of Medical Research,
1G Royal Parade, Parkville, Vic 3052, Australia.
Fax (03) 9347 0852,
smyth at ...
http://www.wehi.edu.au
http://www.statsci.org/smyth

On Sat, 6 Mar 2010, Maciej Jończyk wrote:

> Dear dr Smith and list Members,
>
> I use single-channel analysis to deal with loop-design as suggested by
> Naomi in some of her posts.
>
> Here is my targets with number of biological replication (replication
of
> entire scheme). Technical replication is within each replicated
scheme.
> So within scheme all instances of each sample (samples: lc, lk, hc,
hk)
> is from the same isolation (i.e. in each loop each RNA is used three
> times in different hybridizations).
>
> So in my case technical replication include RNA samples, not
> hybridizations.
>
> lines: l, h
> temperaures: c(cold), k(control)
> That two are concatenated in target file.
>
> Scheme is as follows:
>
> lc ---- lk
> |        |
> hc ---- hk
>
> with two more hybridizations, lc vs hk and lk vs hc.
>
> This is my targets in original two-channel form (biol_rep states for
> biological replication):
>
> SlideNumber	FileName		Cy3	Cy5	biol_rep
> 93	c_093_DH_K_vs_DH_CHex.gpr	hk	hc	1
> 104	c_104_DH_CH_vs_DH_Kex.gpr	hc	hk	2
> 116	c_116_DHK_vs_DHCHex.gpr		hk	hc	3
> 16	c_016_DH_C_vs_DH_Kex.gpr	hc	hk	4
> 94	c_094_DH_K_vs_DL_Kex.gpr	hk	lk	1
> 105	c_105_DL_K_vs_DH_Kex.gpr	lk	hk	2
> 117	c_117_DHK_vs_DLKex.gpr		hk	lk	3
> 139	c_139_DL_K_vs_DH_Kex.gpr	lk	hk	4
> 92	c_092_DL_CH_vs_DL_Kex.gpr	lc	lk	1
> 106	c_106_DL_K_vs_DL_CHex.gpr	lk	lc	2
> 118	c_118_DLCH_vs_DLKex.gpr		lc	lk	3
> 23	c_023_DL_K_vs_DL_Cex.gpr	lk	lc	4
> 95	c_095_DL_CH_vs_DH_CHex.gpr	lc	hc	1
> 107	c_107_DH_CH_vs_DL_CHex.gpr	hc	lc	2
> 119	c_119_DLCH_vs_DHCHex.gpr	lc	hc	3
> 136	c_136_DH_C_vs_DL_Cex.gpr	hc	lc	4
> 101	c_101_DL_K_vs_DH_CHex.gpr	lk	hc	1
> 103	c_103_DH_CH_vs_DL_Kex.gpr	hc	lk	2
> 121	c_121_DLK_vs_DHCHex.gpr		lk	hc	3
> 15	c_015_DH_C_vs_DL_Kex.gpr	hc	lk	4
> 100	c_100_DH_K_vs_DL_CHex.gpr	hk	lc	1
> 102	c_102_DL_CH_vs_DH_Kex.gpr	lc	hk	2
> 120	c_120_DHK_vs_DLCHex.gpr		hk	lc	3
> 140	c_140_DL_C_vs_DH_Kex.gpr	lc	hk	4
>
> I hope it clarifies my design.
>
> Best regards,
>
>
> Gordon K Smyth <smyth at ...> nadawca :
>
>> Dear Maciej,
>>
>> I haven't been able to figure out from this or your previous post
>> exactly what
>> your experimental design is.  I suspect this is why you haven't got
>> replies
>> yet.  I can see that you have technical replicates, but I'm not quite
>> clear
>> that there is any biological replication.  It's also unclear to me
why
>> you need
>> a single channel analysis.  Perhaps you could explain your design a
>> bit more
>> explicitly, including a data.frame with separate factors indicating
>> temperature, maize line, biological rep, and any other factors you
>> need to take
>> into account?
>>
>> Best wishes
>> Gordon
>>
>>> Date: Tue, 02 Mar 2010 13:01:23 +0100
>>> From: mjonczyk at ...
>>> To: <bioconductor at ...>
>>> Cc: Maciej Jo?czyk <mjonczyk at ...>
>>> Subject: Re: [BioC] Loop design - biological, technical replication
>>> 	and contrasts
>>>>
>>> Hi again,
>>>>
>>> I apologise for replying to my own post, but it helps keep track if
>>> someone will be interested.
>>>>
>>> I analysed my data with single channel analysis in limma, according
>>> to
>>> Chapter 9. of limma usersguide.
>>>>
>>> I changed my targets file (to make it more condensed) and removed
>>> suffix
>>> which
>>> identified biological replication. So my targets looks like:
>>>>
>>>> nt_trg
>>>
>>>   SlideNumber                   FileName Cy3 Cy5
>>> 1           93  c_093_DH_K_vs_DH_CHex.gpr  hk  hc
>>> 2          104  c_104_DH_CH_vs_DH_Kex.gpr  hc  hk
>>> 3          116    c_116_DHK_vs_DHCHex.gpr  hk  hc
>>> 4           16   c_016_DH_C_vs_DH_Kex.gpr  hc  hk
>>> 5           94   c_094_DH_K_vs_DL_Kex.gpr  hk  lk
>>> 6          105   c_105_DL_K_vs_DH_Kex.gpr  lk  hk
>>> 7          117     c_117_DHK_vs_DLKex.gpr  hk  lk
>>> 8          139   c_139_DL_K_vs_DH_Kex.gpr  lk  hk
>>> 9           92  c_092_DL_CH_vs_DL_Kex.gpr  lc  lk
>>> 10         106  c_106_DL_K_vs_DL_CHex.gpr  lk  lc
>>> 11         118    c_118_DLCH_vs_DLKex.gpr  lc  lk
>>> 12          23   c_023_DL_K_vs_DL_Cex.gpr  lk  lc
>>> 13          95 c_095_DL_CH_vs_DH_CHex.gpr  lc  hc
>>> 14         107 c_107_DH_CH_vs_DL_CHex.gpr  hc  lc
>>> 15         119   c_119_DLCH_vs_DHCHex.gpr  lc  hc
>>> 16         136   c_136_DH_C_vs_DL_Cex.gpr  hc  lc
>>> 17         101  c_101_DL_K_vs_DH_CHex.gpr  lk  hc
>>> 18         103  c_103_DH_CH_vs_DL_Kex.gpr  hc  lk
>>> 19         121    c_121_DLK_vs_DHCHex.gpr  lk  hc
>>> 20          15   c_015_DH_C_vs_DL_Kex.gpr  hc  lk
>>> 21         100  c_100_DH_K_vs_DL_CHex.gpr  hk  lc
>>> 22         102  c_102_DL_CH_vs_DH_Kex.gpr  lc  hk
>>> 23         120    c_120_DHK_vs_DLCHex.gpr  hk  lc
>>> 24         140   c_140_DL_C_vs_DH_Kex.gpr  lc  hk
>>>>
>>>>
>>> I transform it to apropriate form:
>>>> tgr_sc=targetsA2C(nt_trg)
>>>> tgr_sc
>>>
>>>     channel.col SlideNumber                   FileName Target
>>> 1.1            1          93  c_093_DH_K_vs_DH_CHex.gpr     hk
>>> 1.2            2          93  c_093_DH_K_vs_DH_CHex.gpr     hc
>>> 2.1            1         104  c_104_DH_CH_vs_DH_Kex.gpr     hc
>>> 2.2            2         104  c_104_DH_CH_vs_DH_Kex.gpr     hk
>>> 3.1            1         116    c_116_DHK_vs_DHCHex.gpr     hk
>>> 3.2            2         116    c_116_DHK_vs_DHCHex.gpr     hc
>>> 4.1            1          16   c_016_DH_C_vs_DH_Kex.gpr     hc
>>> 4.2            2          16   c_016_DH_C_vs_DH_Kex.gpr     hk
>>> 5.1            1          94   c_094_DH_K_vs_DL_Kex.gpr     hk
>>> 5.2            2          94   c_094_DH_K_vs_DL_Kex.gpr     lk
>>> 6.1            1         105   c_105_DL_K_vs_DH_Kex.gpr     lk
>>> 6.2            2         105   c_105_DL_K_vs_DH_Kex.gpr     hk
>>> 7.1            1         117     c_117_DHK_vs_DLKex.gpr     hk
>>> 7.2            2         117     c_117_DHK_vs_DLKex.gpr     lk
>>> 8.1            1         139   c_139_DL_K_vs_DH_Kex.gpr     lk
>>> 8.2            2         139   c_139_DL_K_vs_DH_Kex.gpr     hk
>>> 9.1            1          92  c_092_DL_CH_vs_DL_Kex.gpr     lc
>>> 9.2            2          92  c_092_DL_CH_vs_DL_Kex.gpr     lk
>>> 10.1           1         106  c_106_DL_K_vs_DL_CHex.gpr     lk
>>> 10.2           2         106  c_106_DL_K_vs_DL_CHex.gpr     lc
>>> 11.1           1         118    c_118_DLCH_vs_DLKex.gpr     lc
>>> 11.2           2         118    c_118_DLCH_vs_DLKex.gpr     lk
>>> 12.1           1          23   c_023_DL_K_vs_DL_Cex.gpr     lk
>>> 12.2           2          23   c_023_DL_K_vs_DL_Cex.gpr     lc
>>> 13.1           1          95 c_095_DL_CH_vs_DH_CHex.gpr     lc
>>> 13.2           2          95 c_095_DL_CH_vs_DH_CHex.gpr     hc
>>> 14.1           1         107 c_107_DH_CH_vs_DL_CHex.gpr     hc
>>> 14.2           2         107 c_107_DH_CH_vs_DL_CHex.gpr     lc
>>> 15.1           1         119   c_119_DLCH_vs_DHCHex.gpr     lc
>>> 15.2           2         119   c_119_DLCH_vs_DHCHex.gpr     hc
>>> 16.1           1         136   c_136_DH_C_vs_DL_Cex.gpr     hc
>>> 16.2           2         136   c_136_DH_C_vs_DL_Cex.gpr     lc
>>> 17.1           1         101  c_101_DL_K_vs_DH_CHex.gpr     lk
>>> 17.2           2         101  c_101_DL_K_vs_DH_CHex.gpr     hc
>>> 18.1           1         103  c_103_DH_CH_vs_DL_Kex.gpr     hc
>>> 18.2           2         103  c_103_DH_CH_vs_DL_Kex.gpr     lk
>>> 19.1           1         121    c_121_DLK_vs_DHCHex.gpr     lk
>>> 19.2           2         121    c_121_DLK_vs_DHCHex.gpr     hc
>>> 20.1           1          15   c_015_DH_C_vs_DL_Kex.gpr     hc
>>> 20.2           2          15   c_015_DH_C_vs_DL_Kex.gpr     lk
>>> 21.1           1         100  c_100_DH_K_vs_DL_CHex.gpr     hk
>>> 21.2           2         100  c_100_DH_K_vs_DL_CHex.gpr     lc
>>> 22.1           1         102  c_102_DL_CH_vs_DH_Kex.gpr     lc
>>> 22.2           2         102  c_102_DL_CH_vs_DH_Kex.gpr     hk
>>> 23.1           1         120    c_120_DHK_vs_DLCHex.gpr     hk
>>> 23.2           2         120    c_120_DHK_vs_DLCHex.gpr     lc
>>> 24.1           1         140   c_140_DL_C_vs_DH_Kex.gpr     lc
>>> 24.2           2         140   c_140_DL_C_vs_DH_Kex.gpr     hk
>>>>
>>> Next, I made design matrix
>>>>
>>>> u=unique(tgr_sc$Target)
>>>> f=factor(tgr_sc$Target,levels=u)
>>>> design=model.matrix(~0+f)
>>>> colnames(design)=u
>>>> design
>>>
>>>   hk hc lk lc
>>> 1   1  0  0  0
>>> 2   0  1  0  0
>>> 3   0  1  0  0
>>> 4   1  0  0  0
>>> 5   1  0  0  0
>>> 6   0  1  0  0
>>> 7   0  1  0  0
>>> 8   1  0  0  0
>>> 9   1  0  0  0
>>> 10  0  0  1  0
>>> 11  0  0  1  0
>>> 12  1  0  0  0
>>> 13  1  0  0  0
>>> 14  0  0  1  0
>>> 15  0  0  1  0
>>> 16  1  0  0  0
>>> 17  0  0  0  1
>>> 18  0  0  1  0
>>> 19  0  0  1  0
>>> 20  0  0  0  1
>>> 21  0  0  0  1
>>> 22  0  0  1  0
>>> 23  0  0  1  0
>>> 24  0  0  0  1
>>> 25  0  0  0  1
>>> 26  0  1  0  0
>>> 27  0  1  0  0
>>> 28  0  0  0  1
>>> 29  0  0  0  1
>>> 30  0  1  0  0
>>> 31  0  1  0  0
>>> 32  0  0  0  1
>>> 33  0  0  1  0
>>> 34  0  1  0  0
>>> 35  0  1  0  0
>>> 36  0  0  1  0
>>> 37  0  0  1  0
>>> 38  0  1  0  0
>>> 39  0  1  0  0
>>> 40  0  0  1  0
>>> 41  1  0  0  0
>>> 42  0  0  0  1
>>> 43  0  0  0  1
>>> 44  1  0  0  0
>>> 45  1  0  0  0
>>> 46  0  0  0  1
>>> 47  0  0  0  1
>>> 48  1  0  0  0
>>> attr(,"assign")
>>> [1] 1 1 1 1
>>> attr(,"contrasts")
>>> attr(,"contrasts")$f
>>> [1] "contr.treatment"
>>>>
>>> *Is it correct form my design? I see, that it simply identifies what
>>> RNA
>>> was hybridized on each array.
>>>>
>>>> corfit=intraspotCorrelation(nt_img_lA,design)
>>>> corfit$consensus
>>> [1] 0.7341876
>>>> fit=lmscFit(nt_img_lAq,design,correlation=corfit$consensus)
>>>>
>>> I want to get contrasts "hc - hk", "lc - lk", "hc - lc", "hk - lk"
>>> and also test effect of line and temperature. To do that I write
>>> this
>>> command:
>>>>
>>>>
>>>
>>>
>>
contr.matrix=makeContrasts(hc-hk,lc-lk,hc-lc,hk-lk,linia=(hc+hk-lc-lk)/2,temp=(hc+lc-hk-lk)/2,inter=(hc-lc)-(hk-lk),levels=design)
>>>>
>>> * I'm not 100% sure that it's correct.
>>>>
>>>> contr.fit=contrasts.fit(fit,contr.matrix)
>>>> contr.fit=eBayes(contr.fit)
>>>>
>>>
>>>
>>
wynik=decideTests(contr.fit,method="global",adjust.method="BH",p.value=0.05)
>>>> summary(wynik)
>>>   hc - hk lc - lk hc - lc hk - lk linia  temp inter
>>> -1    5865    5039    3014    2685  3931  7382  1113
>>> 0    30922   33433   37177   38480 35896 28364 40776
>>> 1     6594    4909    3190    2216  3554  7635  1492
>>>>
>>> From that it seem that there is a lot of differentially expressed
>>> genes.
>>> I feel that it isn't optimal design, here technical and biological
>>> replications
>>> are treated in the same manner, aren't they?
>>>>
>>> I've read about "duplicateCorrelation" command, is it possible to
>>> combine it with single channel analysis?
>>> Or I should rewrite target file (add number of replication) and
>>> rewrite
>>> contrasts
>>> (e.g. hc-hk change to "((hc1+hc2+hc3+hc4)-(hk1+hk2+hk3+hk4))/4
>>> )?
>>>>
>>> And if I want to include a dye effect, I should only add column with
>>> 1's
>>> to my design, right?
>>>>
>>> Thank you for reading of my post.
>>> I'd be very grateful for help. I've tried to analyse this data for a
>>> along time
>>> and I think limma is the best choice.
>>>>
>>> Yours sincerely,
>>>>
>>> Maciej Jo?czyk
>>>>
>>> Maciej Jo?czyk
>>> Department of Plant Molecular Ecophysiology
>>> Institute of Plant Experimental Biology
>>> Faculty of Biology, University of Warsaw
>>> 02-096 Warszawa, Miecznikowa 1
>>
>>
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>
>
> Maciej Jończyk
> Department of Plant Molecular Ecophysiology
> Institute of Plant Experimental Biology
> Faculty of Biology, University of Warsaw
> 02-096 Warszawa, Miecznikowa 1
>
>
>
> ___________________________________
> NOCC, http://nocc.sourceforge.net



Maciej Jończyk
Department of Plant Molecular Ecophysiology
Institute of Plant Experimental Biology
Faculty of Biology, University of Warsaw
02-096 Warszawa, Miecznikowa 1



___________________________________
NOCC, http://nocc.sourceforge.net



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