limma topTable problem
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Jianping Jin ▴ 890
@jianping-jin-1212
Last seen 9.6 years ago
Dear BC list: I tried limma's lmFit and eBayes with my data set which consists 6 RG_U34A chips, 3 of them as condition 1 and the other 3 as condition 2. What I did was as the following: > data <- ReadAffy() > eset <- gcrma(data) Computing affinities.Done. Adjusting for optical effect......Done. Adjusting for non-specific binding......Done. Normalizing Calculating Expression > design <- model.matrix(~ -1+factor(c(1,1,1,2,2,2))) > colnames(design) <- c("Diff","Prolif") > fit <- lmFit(eset,design) > fit2 <- eBayes(fit) > topTable(fit2,adjust="fdr") ID M A t P.Value B 1742 J01435cds#4_s_at 15.69638 15.78457 374.0793 1.514150e-12 22.64603 8022 X14671cds_s_at 14.58179 14.56121 356.7313 1.514150e-12 22.58357 3700 rc_AA849038_at 14.58663 14.47957 344.0524 1.514150e-12 22.53258 5919 rc_AI237836_at 15.01864 14.98568 338.1369 1.514150e-12 22.50706 8209 X57529cds_s_at 14.96041 14.89656 330.1616 1.514150e-12 22.47075 3655 rc_AA818069_f_at 15.04516 15.02714 325.2206 1.514150e-12 22.44709 8219 X58200mRNA_at 14.45639 14.41961 322.4039 1.514150e-12 22.43318 8281 X62145cds_at 13.81953 13.83622 322.0119 1.514150e-12 22.43121 7941 X06423_g_at 15.00450 14.93952 321.4805 1.514150e-12 22.42855 8225 X58465mRNA_g_at 13.19960 13.18034 320.3176 1.514150e-12 22.42267 ## I liked to see how many genes with adjusted p-value < 0.05 > dim(fit2) [1] 8799 2 > table <- topTable(fit2, number=8799, adjust.method="fdr") > sum(table[,5]<0.05) [1] 8788 It was unbelievable that 8788 out of 8799 genes are significantly expressed. Therefore I tried to look at p-values before eBayes: > topTable(fit,adjust.method="fdr") Error in array(x, c(length(x), 1), if (!is.null(names(x))) list(names(x), : attempt to set an attribute on NULL I am not familiar with lmFit and eBayes and don't know if it is appropriate to make a gene list based on adjusted p-values. Is it B value better? I'll appreciate anyone who can help me out! Jianping xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx x Jianping Jin Ph.D. x x Bioinformatics scientist x x Center for bioinformatics x x 3133 Bioinformatics Building x x CB# 7104 x x University of North Carolina x x Chapel Hill, NC 27599 x x Tel: (919)843-6105 x x Fax: (919)843-3103 x x E-mail: jjin at email.unc.edu x xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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Jenny Drnevich ★ 2.2k
@jenny-drnevich-382
Last seen 9.6 years ago
Hi Jianping, I have just been learning how to use limma, and I almost stumbled into your problem. Because of the way your design matrix is laid out, you need to specify a contrast matrix before running the eBayes function. See page 31 in the Limma manual for what to do. Cheers, Jenny At 03:07 PM 9/28/2005, you wrote: >Dear BC list: > >I tried limma's lmFit and eBayes with my data set which consists 6 RG_U34A >chips, 3 of them as condition 1 and the other 3 as condition 2. What I did >was as the following: > > > data <- ReadAffy() > > eset <- gcrma(data) >Computing affinities.Done. >Adjusting for optical effect......Done. >Adjusting for non-specific binding......Done. >Normalizing >Calculating Expression > > design <- model.matrix(~ -1+factor(c(1,1,1,2,2,2))) > > colnames(design) <- c("Diff","Prolif") > > fit <- lmFit(eset,design) > > fit2 <- eBayes(fit) > > topTable(fit2,adjust="fdr") > ID M A t P.Value B >1742 J01435cds#4_s_at 15.69638 15.78457 374.0793 1.514150e-12 22.64603 >8022 X14671cds_s_at 14.58179 14.56121 356.7313 1.514150e-12 22.58357 >3700 rc_AA849038_at 14.58663 14.47957 344.0524 1.514150e-12 22.53258 >5919 rc_AI237836_at 15.01864 14.98568 338.1369 1.514150e-12 22.50706 >8209 X57529cds_s_at 14.96041 14.89656 330.1616 1.514150e-12 22.47075 >3655 rc_AA818069_f_at 15.04516 15.02714 325.2206 1.514150e-12 22.44709 >8219 X58200mRNA_at 14.45639 14.41961 322.4039 1.514150e-12 22.43318 >8281 X62145cds_at 13.81953 13.83622 322.0119 1.514150e-12 22.43121 >7941 X06423_g_at 15.00450 14.93952 321.4805 1.514150e-12 22.42855 >8225 X58465mRNA_g_at 13.19960 13.18034 320.3176 1.514150e-12 22.42267 > >## I liked to see how many genes with adjusted p-value < 0.05 > > > dim(fit2) >[1] 8799 2 > > table <- topTable(fit2, number=8799, adjust.method="fdr") > > sum(table[,5]<0.05) >[1] 8788 > >It was unbelievable that 8788 out of 8799 genes are significantly >expressed. Therefore I tried to look at p-values before eBayes: > > > topTable(fit,adjust.method="fdr") >Error in array(x, c(length(x), 1), if (!is.null(names(x))) list(names(x), >: > attempt to set an attribute on NULL > >I am not familiar with lmFit and eBayes and don't know if it is appropriate >to make a gene list based on adjusted p-values. Is it B value better? > >I'll appreciate anyone who can help me out! > >Jianping > >xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx >x Jianping Jin Ph.D. x >x Bioinformatics scientist x >x Center for bioinformatics x >x 3133 Bioinformatics Building x >x CB# 7104 x >x University of North Carolina x >x Chapel Hill, NC 27599 x >x Tel: (919)843-6105 x >x Fax: (919)843-3103 x >x E-mail: jjin at email.unc.edu x >xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor Jenny Drnevich, Ph.D. Functional Genomics Bioinformatics Specialist W.M. Keck Center for Comparative and Functional Genomics Roy J. Carver Biotechnology Center University of Illinois, Urbana-Champaign 330 ERML 1201 W. Gregory Dr. Urbana, IL 61801 USA ph: 217-244-7355 fax: 217-265-5066 e-mail: drnevich at uiuc.edu
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Thanks a lot Jenny for helping me out! Do you have any idea about the error I got when I tried to get p-value after lmFit? > topTable(fit,adjust.method="fdr") Error in array(x, c(length(x), 1), if (!is.null(names(x))) list(names(x), : attempt to set an attribute on NULL best regards! Jianping --On Wednesday, September 28, 2005 3:24 PM -0500 Jenny Drnevich <drnevich at="" uiuc.edu=""> wrote: > Hi Jianping, > > I have just been learning how to use limma, and I almost stumbled into > your problem. Because of the way your design matrix is laid out, you need > to specify a contrast matrix before running the eBayes function. See page > 31 in the Limma manual for what to do. > > Cheers, > Jenny > > > At 03:07 PM 9/28/2005, you wrote: >> Dear BC list: >> >> I tried limma's lmFit and eBayes with my data set which consists 6 >> RG_U34A chips, 3 of them as condition 1 and the other 3 as condition 2. >> What I did was as the following: >> >> > data <- ReadAffy() >> > eset <- gcrma(data) >> Computing affinities.Done. >> Adjusting for optical effect......Done. >> Adjusting for non-specific binding......Done. >> Normalizing >> Calculating Expression >> > design <- model.matrix(~ -1+factor(c(1,1,1,2,2,2))) >> > colnames(design) <- c("Diff","Prolif") >> > fit <- lmFit(eset,design) >> > fit2 <- eBayes(fit) >> > topTable(fit2,adjust="fdr") >> ID M A t P.Value B >> 1742 J01435cds#4_s_at 15.69638 15.78457 374.0793 1.514150e-12 22.64603 >> 8022 X14671cds_s_at 14.58179 14.56121 356.7313 1.514150e-12 22.58357 >> 3700 rc_AA849038_at 14.58663 14.47957 344.0524 1.514150e-12 22.53258 >> 5919 rc_AI237836_at 15.01864 14.98568 338.1369 1.514150e-12 22.50706 >> 8209 X57529cds_s_at 14.96041 14.89656 330.1616 1.514150e-12 22.47075 >> 3655 rc_AA818069_f_at 15.04516 15.02714 325.2206 1.514150e-12 22.44709 >> 8219 X58200mRNA_at 14.45639 14.41961 322.4039 1.514150e-12 22.43318 >> 8281 X62145cds_at 13.81953 13.83622 322.0119 1.514150e-12 22.43121 >> 7941 X06423_g_at 15.00450 14.93952 321.4805 1.514150e-12 22.42855 >> 8225 X58465mRNA_g_at 13.19960 13.18034 320.3176 1.514150e-12 22.42267 >> >>## I liked to see how many genes with adjusted p-value < 0.05 >> >> > dim(fit2) >> [1] 8799 2 >> > table <- topTable(fit2, number=8799, adjust.method="fdr") >> > sum(table[,5]<0.05) >> [1] 8788 >> >> It was unbelievable that 8788 out of 8799 genes are significantly >> expressed. Therefore I tried to look at p-values before eBayes: >> >> > topTable(fit,adjust.method="fdr") >> Error in array(x, c(length(x), 1), if (!is.null(names(x))) list(names(x), >> : >> attempt to set an attribute on NULL >> >> I am not familiar with lmFit and eBayes and don't know if it is >> appropriate to make a gene list based on adjusted p-values. Is it B >> value better? >> >> I'll appreciate anyone who can help me out! >> >> Jianping >> >> xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx >> x Jianping Jin Ph.D. x >> x Bioinformatics scientist x >> x Center for bioinformatics x >> x 3133 Bioinformatics Building x >> x CB# 7104 x >> x University of North Carolina x >> x Chapel Hill, NC 27599 x >> x Tel: (919)843-6105 x >> x Fax: (919)843-3103 x >> x E-mail: jjin at email.unc.edu x >> xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor > > Jenny Drnevich, Ph.D. > > Functional Genomics Bioinformatics Specialist > W.M. Keck Center for Comparative and Functional Genomics > Roy J. Carver Biotechnology Center > University of Illinois, Urbana-Champaign > > 330 ERML > 1201 W. Gregory Dr. > Urbana, IL 61801 > USA > > ph: 217-244-7355 > fax: 217-265-5066 > e-mail: drnevich at uiuc.edu xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx x Jianping Jin Ph.D. x x Bioinformatics scientist x x Center for bioinformatics x x 3133 Bioinformatics Building x x CB# 7104 x x University of North Carolina x x Chapel Hill, NC 27599 x x Tel: (919)843-6105 x x Fax: (919)843-3103 x x E-mail: jjin at email.unc.edu x xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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