Hi Laya,
Please don't take questions off-list.
On 3/19/13 7:36 AM, Laya Rose wrote:
> Sir
> I met with a problem regarding the gene name of the data that i
have
> done using R/Biocondutor. The answer that i got by doing the program
is
> ##chronic stress effect on pheripheral blood monocyte(raw data from
NCBI)
> > library(limma)
> > library(affy)
> > eset.rma <- justRMA(celfile.path="/media/Computational
> Science/Intern/cel")
> > pData(eset.rma)
> sample
> GSM194153.CEL 1
> GSM194154.CEL 2
> GSM194155.CEL 3
> GSM194156.CEL 4
> GSM194157.CEL 5
> GSM194158.CEL 6
> GSM194159.CEL 7
> GSM194160.CEL 8
> GSM194161.CEL 9
> GSM194162.CEL 10
> GSM194163.CEL 11
> GSM194164.CEL 12
> GSM194165.CEL 13
> GSM194166.CEL 14
> GSM194167.CEL 15
> GSM194168.CEL 16
> GSM194169.CEL 17
> GSM194170.CEL 18
> GSM194171.CEL 19
> GSM194172.CEL 20
> GSM194173.CEL 21
> > design <- model.matrix(~factor(rep(1:2, c(11,10))))
> > colnames(design) <- c("caregiver","caregivervscontrol")
> > colnames(design)
> [1] "caregiver" "caregivervscontrol"
> > design
> caregiver caregivervscontrol
> 1 1 0
> 2 1 0
> 3 1 0
> 4 1 0
> 5 1 0
> 6 1 0
> 7 1 0
> 8 1 0
> 9 1 0
> 10 1 0
> 11 1 0
> 12 1 1
> 13 1 1
> 14 1 1
> 15 1 1
> 16 1 1
> 17 1 1
> 18 1 1
> 19 1 1
> 20 1 1
> 21 1 1
> attr(,"assign")
> [1] 0 1
> attr(,"contrasts")
> attr(,"contrasts")$`factor(rep(1:2, c(11, 10)))`
> [1] "contr.treatment"
>
> > fit <- lmFit(eset.rma, design)
> > fit <- eBayes(fit)
> > result <- topTable(fit, number=20, sort.by <http: sort.by="">="B",
> adjust="BH", p.value=0.05)
Here you are asking for all genes where any coefficient is different
from zero. But your first coefficient estimates the mean of the
caregiver samples, which will almost always be significantly different
from zero, and is an uninteresting result.
Instead, you want to find genes where the caregiver vs control
comparison is different from zero, which is your second coefficient.
To
do that you need to include coef=2 in your call to topTable().
Best,
Jim
> > result
> ID caregiver caregivervscontrol AveExpr
F
> 216526_x_at 216526_x_at 13.291805 -0.1096321979 13.23960
85050.91
> 39854_r_at 39854_r_at 10.419915 -0.0372112598 10.40220
70391.77
> 38710_at 38710_at 9.192459 -0.0847969308 9.15208
65091.16
> 220960_x_at 220960_x_at 11.918361 -0.0693425839 11.88534
65000.11
> 211445_x_at 211445_x_at 11.331780 -0.0567108618 11.30477
63663.77
> 221798_x_at 221798_x_at 13.799294 -0.0051424692 13.79684
61259.71
> 201254_x_at 201254_x_at 13.120118 -0.0304201074 13.10563
60370.97
> 212869_x_at 212869_x_at 14.520910 -0.1448694710 14.45192
57874.70
> 207783_x_at 207783_x_at 13.569484 -0.1153729885 13.51454
56273.48
> 208768_x_at 208768_x_at 12.592456 -0.0001313416 12.59239
55726.09
> 206559_x_at 206559_x_at 14.147763 0.0375752743 14.16566
55517.79
> 200633_at 200633_at 13.460864 -0.0234022819 13.44972
55009.06
> 221775_x_at 221775_x_at 12.553841 0.0014125408 12.55451
54692.55
> 37278_at 37278_at 7.759139 0.0130228855 7.76534
54635.93
> 214327_x_at 214327_x_at 12.139203 -0.0623833002 12.10950
52902.17
> 212284_x_at 212284_x_at 13.952524 -0.0919405644 13.90874
52445.88
> 214351_x_at 214351_x_at 11.728144 0.0246027780 11.73986
51781.39
> 213477_x_at 213477_x_at 13.402430 0.0108312076 13.40759
51214.20
> 214317_x_at 214317_x_at 12.384605 0.0130429357 12.39082
50957.53
> 200926_at 200926_at 13.343766 0.0218536588 13.35417
50901.69
> P.Value adj.P.Val
> 216526_x_at 2.959633e-42 6.594950e-38
> 39854_r_at 2.214834e-41 2.467657e-37
> 38710_at 5.094160e-41 2.874272e-37
> 220960_x_at 5.170593e-41 2.874272e-37
> 211445_x_at 6.449472e-41 2.874272e-37
> 221798_x_at 9.713637e-41 3.607483e-37
> 201254_x_at 1.134763e-40 3.612275e-37
> 212869_x_at 1.778350e-40 4.953372e-37
> 207783_x_at 2.396915e-40 5.223307e-37
> 208768_x_at 2.659599e-40 5.223307e-37
> 206559_x_at 2.767701e-40 5.223307e-37
> 200633_at 3.052481e-40 5.223307e-37
> 221775_x_at 3.245743e-40 5.223307e-37
> 37278_at 3.281708e-40 5.223307e-37
> 214327_x_at 4.624818e-40 6.870321e-37
> 212284_x_at 5.071294e-40 7.062728e-37
> 214351_x_at 5.808078e-40 7.139702e-37
> 213477_x_at 6.530111e-40 7.139702e-37
> 214317_x_at 6.888655e-40 7.139702e-37
> 200926_at 6.969475e-40 7.139702e-37
> like this. But when comparing with the gene names from the result
and
> the gene names specified in the corresponding paper
> are entirely different. Why there is such a huge difference? i
> enclosed the raw data with this mail. Can't able to identify the
problem.
> On Fri, Mar 15, 2013 at 10:20 AM, Laya Rose <roselaya98 at="" gmail.com=""> <mailto:roselaya98 at="" gmail.com="">> wrote:
>
> Sir,
> Thank you for the help. Got answer for my problem. Will surely
> read limma user's guide.
>
>
> On Thu, Mar 14, 2013 at 9:15 PM, James W. MacDonald
> <jmacdon at="" uw.edu="" <mailto:jmacdon="" at="" uw.edu="">> wrote:
>
> Hi Laya,
> Please don't take things off list.
> I would highly recommend reading the limma user's guide,
which
> has examples that show exactly what you should be doing
here.
> But note that it is simple to create the design matrix using
> the model.matrix() function:
> design <- model.matrix(~factor(rep(1:2, c(11,10)))
> colnames(design) <- c("caregiver","caregivervscontrol")
> Best,
> Jim
>
>
> On Thu, Mar 14, 2013 at 2:17 AM, Laya Rose
> <roselaya98 at="" gmail.com="" <mailto:roselaya98="" at="" gmail.com="">>
wrote:
>
> Sir
> Thank you for your reply. Actually R/Bioconductor is
new
> to me. So very difficult for me to sort out the errors.
> Because of that i can't able to move on to next step.
> Files from GSM194164.CEL to GSM194173.CEL are the
samples
> of control. Then how can the issue of no controls in the
> rownames of phenodata can occur.
>
> On Thu, Mar 14, 2013 at 2:02 AM, James W. MacDonald
> <jmacdon at="" uw.edu="" <mailto:jmacdon="" at="" uw.edu="">> wrote:
>
> Hi Laya,
>
>
>
> On 3/13/13 4:40 AM, Laya Rose wrote:
>
> Hello,
> An issue was reported when I was doing the
> following commands.
>
> library(limma)
> library(affy)
> eset.rma <-
> justRMA(celfile.path="/media/Computational
>
> Science/Intern/cel")
>
> pData(eset.rma)
>
> sample
> GSM194153.CEL 1
> GSM194154.CEL 2
> GSM194155.CEL 3
> GSM194156.CEL 4
> GSM194157.CEL 5
> GSM194158.CEL 6
> GSM194159.CEL 7
> GSM194160.CEL 8
> GSM194161.CEL 9
> GSM194162.CEL 10
> GSM194163.CEL 11
> GSM194164.CEL 12
> GSM194165.CEL 13
> GSM194166.CEL 14
> GSM194167.CEL 15
> GSM194168.CEL 16
> GSM194169.CEL 17
> GSM194170.CEL 18
> GSM194171.CEL 19
> GSM194172.CEL 20
> GSM194173.CEL 21
>
> a<-rep(0,length(pData(eset.rma)$sample))
> a[grep("control", rownames(pData(eset.rma)),
> ignore.case=T)] <-1
> a
>
> [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
>
>
> There are no controls in the row.names of your
> phenoData, so you are getting all zeros. You need to
> fix this step so you have a 1 for each control.
>
> Best,
>
> Jim
>
>
> design <- cbind(caregiver=1,
controlVscaregiver=a)
> design
>
> caregiver controlVscaregiver
> [1,] 1 0
> [2,] 1 0
> [3,] 1 0
> [4,] 1 0
> [5,] 1 0
> [6,] 1 0
> [7,] 1 0
> [8,] 1 0
> [9,] 1 0
> [10,] 1 0
> [11,] 1 0
> [12,] 1 0
> [13,] 1 0
> [14,] 1 0
> [15,] 1 0
> [16,] 1 0
> [17,] 1 0
> [18,] 1 0
> [19,] 1 0
> [20,] 1 0
> [21,] 1 0
>
> fit <- lmFit(eset.rma, design)
>
> Coefficients not estimable: controlVscaregiver
> Warning message:
> Partial NA coefficients for 22283 probe(s)
>
> Is this issue has reported because of the
> coefficients i have selected.
> I don't know how to resolve this issue. Thanks
in
> advance for any help.
>
> -
> *Laya Rose*
>
> [[alternative HTML version deleted]]
>
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>
>
>
>
> --
> *Laya Rose*
>
>
>
>
>
> --
> *Laya Rose*
>
>
>
>
> --
> *Laya Rose*
>
