Hi, I am trying to run my microarray data through ComBat(in sva packge).Below is my sampleinfo file. When I run it with these commands batch = sampleinfo$Batch mod = model.matrix(~as.factor(Covariate), data=sampleinfo) combat_edata = ComBat(dat=edata, batch=batch, mod=mod, par.prior=TRUE, prior.plots=FALSE) I dont get any error and it runs with this message. Found 10 batches Found 3 categorical covariate(s) Standardizing Data across genes Fitting L/S model and finding priors Finding parametric adjustments Adjusting the Data But the problem is I have 4 covariate not three. I even ran the example dataset in SVA package ## Load data library(bladderbatch) data(bladderdata) ## Obtain phenotypic data pheno = pData(bladderEset) edata = exprs(bladderEset) batch = pheno$batch mod = model.matrix(~as.factor(cancer), data=pheno) ## Correct for batch using ComBat combat_edata = ComBat(dat=edata, batch=batch, mod=mod, par.prior=TRUE, prior.plots=FALSE) This also give Found 2 categorical covariate(s) when there are three covariates in this dataset. Please help, Thank you, Gayatri Array name Sample name Batch Covariate C3D1 1 1 1 C3D2 2 1 1 C3D3 3 1 1 C3D5 4 2 1 C3D14 5 6 1 C3D15 6 6 1 C3D16 7 7 1 C3D17 8 7 1 C3D18 9 7 1 S3D7 10 3 2 S3D8 11 4 2 S3D9 12 4 2 S3D10 13 4 2 S3D11 14 5 2 S3D12 15 5 2 S3D19 16 8 2 S3D20 17 8 2 S3D21 18 9 2 S3D22 19 9 2 S3D23 20 10 2 S3D24 21 10 2 C25D1 22 1 3 C25D2 23 1 3 C25D3 24 2 3 C25D5 25 3 3 C25D14 26 6 3 C25D15 27 6 3 C25D16 28 7 3 C25D17 29 7 3 C25D18 30 8 3 S25D7 31 3 4 S25D8 32 4 4 S25D9 33 4 4 S25D10 34 5 4 S25D11 35 5 4 S25D12 36 5 4 S25D19 37 8 4 S25D21 38 9 4 S25D23 39 10 4 [[alternative HTML version deleted]]

Hi Gayatri, Following the example on the ComBat man page as you have done, I see 2 covariates, not 3. The model matrix shows 'cancer' and 'normal' covariates: > head(mod) (Intercept) as.factor(cancer)Cancer as.factor(cancer)Normal GSM71019.CEL 1 0 1 GSM71020.CEL 1 0 1 ... ... The intercept is not considered a categorical covariate. I've cc'd the package authors in case they have something else to add. Valerie On 01/03/2013 01:31 PM, Gayatri Iyer wrote: > Hi, > I am trying to run my microarray data through ComBat(in sva packge).Below > is my sampleinfo file. > When I run it with these commands > > batch = sampleinfo$Batch > mod = model.matrix(~as.factor(Covariate), data=sampleinfo) > combat_edata = ComBat(dat=edata, batch=batch, mod=mod, par.prior=TRUE, > prior.plots=FALSE) > I dont get any error and it runs with this message. > Found 10 batches > Found 3 categorical covariate(s) > Standardizing Data across genes > Fitting L/S model and finding priors > Finding parametric adjustments > Adjusting the Data > > But the problem is I have 4 covariate not three. > > I even ran the example dataset in SVA package > ## Load data > library(bladderbatch) > data(bladderdata) > > ## Obtain phenotypic data > pheno = pData(bladderEset) > edata = exprs(bladderEset) > batch = pheno$batch > mod = model.matrix(~as.factor(cancer), data=pheno) > > ## Correct for batch using ComBat > combat_edata = ComBat(dat=edata, batch=batch, mod=mod, par.prior=TRUE, > prior.plots=FALSE) > This also give > Found 2 categorical covariate(s) when there are three covariates in this > dataset. > > > Please help, > Thank you, > Gayatri > > Array name Sample name Batch Covariate C3D1 1 1 1 C3D2 2 1 1 C3D3 3 1 1 > C3D5 4 2 1 C3D14 5 6 1 C3D15 6 6 1 C3D16 7 7 1 C3D17 8 7 1 C3D18 9 7 1 > S3D7 10 3 2 S3D8 11 4 2 S3D9 12 4 2 S3D10 13 4 2 S3D11 14 5 2 S3D12 15 > 5 2 S3D19 16 8 2 S3D20 17 8 2 S3D21 18 9 2 S3D22 19 9 2 S3D23 20 10 2 > S3D24 21 10 2 C25D1 22 1 3 C25D2 23 1 3 C25D3 24 2 3 C25D5 25 3 3 > C25D14 26 6 3 C25D15 27 6 3 C25D16 28 7 3 C25D17 29 7 3 C25D18 30 8 3 > S25D7 31 3 4 S25D8 32 4 4 S25D9 33 4 4 S25D10 34 5 4 S25D11 35 5 4 > S25D12 36 5 4 S25D19 37 8 4 S25D21 38 9 4 > > S25D23 > 39 10 > > 4 > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

Hello, On 01/07/2013 10:39 AM, Gayatri Iyer wrote: > Hi, > Thank you for the reply. > My question was when I run the example data set > ## Not run: > > ## Load data > library(sva) > library(bladderbatch) > data(bladderdata) > > ## Obtain phenotypic data > pheno = pData(bladderEset) > edata = exprs(bladderEset) > batch = pheno$batch > mod = model.matrix(~as.factor(cancer), data=pheno) > And when I type pheno.I see Cancer,Normal and Biopsy in the cancer > column.So I considered the number of Covariates in (cancer) were 3 not 2. I'm not an expert on the model.matrix but I believe this is the classic dimension reduction representation. It takes n-1 variables to represent n variables. You can see this by looking at the contrasts in the 'cancer' column. > contrasts(pheno$cancer) Cancer Normal Biopsy 0 0 Cancer 1 0 Normal 0 1 In the model.matrix the combination of 00 (i.e., Cancer=0 and Normal=0) represent the Biopsy samples. > mod <- model.matrix(~ cancer, data=pheno) > tail(mod) (Intercept) cancerCancer cancerNormal GSM71072.CEL 1 0 0 GSM71073.CEL 1 0 0 GSM71074.CEL 1 0 0 GSM71075.CEL 1 0 0 GSM71076.CEL 1 0 0 GSM71077.CEL 1 0 0 Valerie > And when I run > combat_edata = ComBat(dat=edata, batch=batch, mod=mod, par.prior=TRUE, > prior.plots=FALSE) > I see > Found 5 batches > Found 2 categorical covariate(s) > So why is this bias. > I am sorry for not being precise in my previous email. > Thank you, > Gayatri > > > > On Mon, Jan 7, 2013 at 12:22 PM, Valerie Obenchain <vobencha at="" fhcrc.org=""> <mailto:vobencha at="" fhcrc.org="">> wrote: > > Hi Gayatri, > > Following the example on the ComBat man page as you have done, I see > 2 covariates, not 3. > > The model matrix shows 'cancer' and 'normal' covariates: > > head(mod) > > (Intercept) as.factor(cancer)Cancer > as.factor(cancer)Normal > GSM71019.CEL 1 0 1 > GSM71020.CEL 1 0 1 > ... > ... > > The intercept is not considered a categorical covariate. > > I've cc'd the package authors in case they have something else to add. > > Valerie > > > > On 01/03/2013 01:31 PM, Gayatri Iyer wrote: > > Hi, > I am trying to run my microarray data through ComBat(in sva > packge).Below > is my sampleinfo file. > When I run it with these commands > > batch = sampleinfo$Batch > mod = model.matrix(~as.factor(__Covariate), data=sampleinfo) > combat_edata = ComBat(dat=edata, batch=batch, mod=mod, > par.prior=TRUE, > prior.plots=FALSE) > I dont get any error and it runs with this message. > Found 10 batches > Found 3 categorical covariate(s) > Standardizing Data across genes > Fitting L/S model and finding priors > Finding parametric adjustments > Adjusting the Data > > But the problem is I have 4 covariate not three. > > I even ran the example dataset in SVA package > ## Load data > library(bladderbatch) > data(bladderdata) > > ## Obtain phenotypic data > pheno = pData(bladderEset) > edata = exprs(bladderEset) > batch = pheno$batch > mod = model.matrix(~as.factor(__cancer), data=pheno) > > ## Correct for batch using ComBat > combat_edata = ComBat(dat=edata, batch=batch, mod=mod, > par.prior=TRUE, > prior.plots=FALSE) > This also give > Found 2 categorical covariate(s) when there are three > covariates in this > dataset. > > > Please help, > Thank you, > Gayatri > > Array name Sample name Batch Covariate C3D1 1 1 1 C3D2 2 1 > 1 C3D3 3 1 1 > C3D5 4 2 1 C3D14 5 6 1 C3D15 6 6 1 C3D16 7 7 1 C3D17 8 7 1 > C3D18 9 7 1 > S3D7 10 3 2 S3D8 11 4 2 S3D9 12 4 2 S3D10 13 4 2 S3D11 14 5 > 2 S3D12 15 > 5 2 S3D19 16 8 2 S3D20 17 8 2 S3D21 18 9 2 S3D22 19 9 2 > S3D23 20 10 2 > S3D24 21 10 2 C25D1 22 1 3 C25D2 23 1 3 C25D3 24 2 3 C25D5 > 25 3 3 > C25D14 26 6 3 C25D15 27 6 3 C25D16 28 7 3 C25D17 29 7 3 > C25D18 30 8 3 > S25D7 31 3 4 S25D8 32 4 4 S25D9 33 4 4 S25D10 34 5 4 S25D11 > 35 5 4 > S25D12 36 5 4 S25D19 37 8 4 S25D21 38 9 4 > > S25D23 > 39 10 > > 4 > > [[alternative HTML version deleted]] > > _________________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org <mailto:bioconductor at="" r-project.org=""> > https://stat.ethz.ch/mailman/__listinfo/bioconductor > <https: stat.ethz.ch="" mailman="" listinfo="" bioconductor=""> > Search the archives: > http://news.gmane.org/gmane.__science.biology.informatics.__conductor > <http: news.gmane.org="" gmane.science.biology.informatics.conductor=""> > > >