Entering edit mode
Eduardo Andrés León
▴
90
@eduardo-andres-leon-5963
Last seen 9.6 years ago
Dear all, I'm trying to analyse an experiment from Small RNASeq (miRNA
Seq).
In this experiment I have 2 different types of mice (MT and WT) and a
treatment variables (treated or cD and untreated or sD). So there will
be 4 types of data : WTcD (treated WT), WTsD (untreated WT), MTcD
(Treated Mutant) and MTsD (Untreated Mutant)
So, my design is something likes this :
> design
(Intercept) MouseWT TreatmentUntreated
WTsD_1_9.5 1 1 1
WTsD_2_9.5 1 1 1
WTsD_3_9.5 1 1 1
WTcD_1_9.5 1 1 0
WTcD_2_9.5 1 1 0
WTcD_3_9.5 1 1 0
MTsD_2_9.5 1 0 1
MTsD_3_9.5 1 0 1
MTcD_1_9.5 1 0 0
MTcD_2_9.5 1 0 0
MTcD_3_9.5 1 0 0
attr(,"assign")
[1] 0 1 2
attr(,"contrasts")
attr(,"contrasts")$Mouse
[1] "contr.treatment"
attr(,"contrasts")$Treatment
[1] "contr.treatment"
I have 3 replicates for every mouse, but the MTsD_1 seems to be an
outlayer.
So following the userguide by the edgeR packages (Section 4.4), I run
the following commands :
rawdata<-read.delim(file="ALL_MTcD_9.5",header=TRUE,row.names=1)
y<-DGEList(counts=rawdata[,c(1,2,3,4,5,6,8,9,10,11,12)],genes=rawdata[
,0])
y<-calcNormFactors(y)
plotMDS(y,xlab="Mouse factor",ylab="Treatment
Factor",xlim=c(-0.4,0.4),ylim=c(-0.4,0.4))
Mouse<-factor(c("WT","WT","WT","WT","WT","WT","MT","MT","MT","MT","MT"
))
Treatment<-factor(c("Untreated","Untreated","Untreated","Treated","Tre
ated","Treated","Untreated","Untreated","Treated","Treated","Treated")
)
data.frame(Sample=colnames(y),Mouse,Treatment)
design<-model.matrix(~Mouse+Treatment)
rownames(design)<-colnames(y)
#Overall dispersion of the dataset
y<-estimateGLMCommonDisp(y,design,verbose=TRUE)
#Estimation of the gene-wise dispersion
y<-estimateGLMTrendedDisp(y,design)
y<-estimateGLMTagwiseDisp(y,design)
#Diff expresion
fit<-glmFit(y,design)
lrt<-glmLRT(fit)
topTags(ltr)
But it stops at the estimateGLMTrendedDisp steps .
The output is the following :
> library(limma)
> library(edgeR)
> rawdata<-read.delim(file="ALL_MTcD_9.5",header=TRUE,row.names=1)
> y<-DGEList(counts=rawdata[,c(1,2,3,4,5,6,8,9,10,11,12)],genes=rawdat
a[,0])
Calculating library sizes from column totals.
> y<-calcNormFactors(y)
> plotMDS(y,xlab="Mouse factor",ylab="Treatment
Factor",xlim=c(-0.4,0.4),ylim=c(-0.4,0.4))
>
> Mouse<-factor(c("WT","WT","WT","WT","WT","WT","MT","MT","MT","MT","M
T"))
> Treatment<-factor(c("Untreated","Untreated","Untreated","Treated","T
reated","Treated","Untreated","Untreated","Treated","Treated","Treated
"))
> data.frame(Sample=colnames(y),Mouse,Treatment)
Sample Mouse Treatment
1 WTsD_1_9.5 WT Untreated
2 WTsD_2_9.5 WT Untreated
3 WTsD_3_9.5 WT Untreated
4 WTcD_1_9.5 WT Treated
5 WTcD_2_9.5 WT Treated
6 WTcD_3_9.5 WT Treated
7 MTsD_2_9.5 MT Untreated
8 MTsD_3_9.5 MT Untreated
9 MTcD_1_9.5 MT Treated
10 MTcD_2_9.5 MT Treated
11 MTcD_3_9.5 MT Treated
> design<-model.matrix(~Mouse+Treatment)
> rownames(design)<-colnames(y)
>
> #Overall dispersion of the dataset
> y<-estimateGLMCommonDisp(y,design,verbose=TRUE)
Disp = 0.02052 , BCV = 0.1432
> #Estimation of the gene-wise dispersion
> y<-estimateGLMTrendedDisp(y,design)
Warning messages:
1: In binGLMDispersion(y, design, min.n = min.n, offset = offset,
method = method.bin, :
With 1273 genes and setting the parameter minimum number (min.n) of
genes per bin to 500, there should technically be fewer than 2 bins.
To make estimation of trended dispersions possible we set the number
of bins to be 2.
2: In binGLMDispersion(y, design, min.n = min.n, offset = offset,
method = method.bin, :
With 1273 genes and setting the parameter minimum number (min.n) of
genes per bin to 500, there are only 2 bins. Using 2 bins here means
that the minimum number of genes in each of the 2 bins is in fact 302.
This number of bins and minimum number of genes per bin may not be
sufficient for reliable estimation of a trend on the dispersions.
> y<-estimateGLMTagwiseDisp(y,design)
Warning message:
In movingAverageByCol(apl[o, ], width = 1000) :
reducing moving average width to nrow(x)
> #Diff expresion
> fit<-glmFit(y,design)
> lrt<-glmLRT(fit)
Error in array(x, c(length(x), 1L), if (!is.null(names(x)))
list(names(x), :
dims [product 0] do not match the length of object [14]
and ... I don't know what to do.
Any help would be very appreciated
My session info is :
> sessionInfo()
R version 2.15.1 (2012-06-22)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] splines stats graphics grDevices utils datasets
methods base
other attached packages:
[1] edgeR_2.6.12 limma_3.12.3 DESeq_1.8.3
locfit_1.5-9 AnnotationDbi_1.18.4 Biobase_2.16.0
BiocGenerics_0.2.0
loaded via a namespace (and not attached):
[1] annotate_1.34.1 DBI_0.2-5 genefilter_1.38.0
geneplotter_1.34.0 grid_2.15.1 IRanges_1.14.4
lattice_0.20-15 RColorBrewer_1.0-5
[9] RSQLite_0.11.2 stats4_2.15.1 survival_2.37-4
tools_2.15.1 XML_3.96-1.1 xtable_1.7-1
Thanks in advanced
===================================================
Eduardo Andrés León
Tlfn: (+34) 91 732 80 00 / 91 224 69 00 (ext 5054/3063)
e-mail: eandres@cnio.es Fax: (+34) 91 224 69 76
Unidad de Bioinformática Bioinformatics Unit
Centro Nacional de Investigaciones Oncológicas
C.P.: 28029 Zip Code: 28029
C/. Melchor Fernández Almagro, 3 Madrid (Spain)
http://bioinfo.cnio.es http://bioinfo.cnio.es/people/eandres
===================================================
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