Bioconductor Digest, Vol 41, Issue 4

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Gordon Smyth 52k

@gordon-smyth

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WEHI, Melbourne, Australia

>Date: Mon, 3 Jul 2006 09:52:44 -0400 >From: "Wang, Sue Jane" <suejane.wang at="" fda.hhs.gov=""> >Subject: [BioC] Reference for Volcano plot >To: bioconductor at stat.math.ethz.ch > >Dear Anthony Bosco, > >Have you found the reference for volcano plot? I am looking for such a >reference, too. Thanks. > >Sue-Jane Wang Jin, W., Riley, R. M., Wolfinger, R. D., White, K. P., Passador-Gurgel, G., and Gibson, G. (2001). The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nature Genetics 29, 389 - 395. Best wishes Gordon

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ADD COMMENT • link updated 18.4 years ago by Pedro López Romero ▴ 360 • written 18.4 years ago by Gordon Smyth 52k

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Pedro López Romero ▴ 360

@pedro-lopez-romero-1618

Last seen 10.3 years ago

Dear list I am trying to calculate the moderated t-statistic by hand for a given gene[i], and it is not equal to the moderated t value that eBayes ( ) gives.- After fitting my model I can recover the following values for gene [1] : > fit$stdev.unscaled[1] # from lmFit (...,) [1] 0.5774 > fit2$coeff[1] # from eBayes(...,) [1] -0.0468 > fit2$s2.post[1] [1] 0.5344 > fit2$t[1] [1] -0.1421 and *manually* the moderated t-statistic is: > fit2$coeff[1]/(fit$stdev.unscaled[1]*fit2$s2.post[1]) [1] -0.1517 Did I do something wrong? Thanks a lot.- Pedro

ADD COMMENT • link 18.4 years ago Pedro López Romero ▴ 360

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Hi Pedro, If you look at the code for 'ebayes', you'll see that the moderated t is calculated as: out$t <- coefficients/stdev.unscaled/sqrt(out$s2.post) However, when I check with the numbers you show, I don't get the same answer as your fit2$t[1] either, so I don't know what's going on with your data: > -0.0468 / 0.5774 / sqrt(0.5344) [1] -0.1108756 Could a rounding issue make the resulting value that far off? Best, Jenny At 06:32 AM 7/6/2006, Pedro L?pez Romero wrote: >Dear list > >I am trying to calculate the moderated t-statistic by hand for a given >gene[i], and it is not equal to the moderated t value that eBayes ( ) >gives.- > > >After fitting my model I can recover the following values for gene [1] : > > > fit$stdev.unscaled[1] # from lmFit (...,) >[1] 0.5774 > > > fit2$coeff[1] # from eBayes(...,) >[1] -0.0468 > > > fit2$s2.post[1] >[1] 0.5344 > > > fit2$t[1] >[1] -0.1421 > > >and *manually* the moderated t-statistic is: > > > fit2$coeff[1]/(fit$stdev.unscaled[1]*fit2$s2.post[1]) >[1] -0.1517 > > >Did I do something wrong? > >Thanks a lot.- > >Pedro > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor >Search the archives: >http://news.gmane.org/gmane.science.biology.informatics.conductor 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

ADD REPLY • link 18.4 years ago Jenny Drnevich ★ 2.2k

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Thanks Jenny for the replay.- I have figure out how the thinks work. Yes, first my *manual* computation was wrong, I was using the post variance ($s2.post) instead of the sqrt($s2.post). Moreover, I was using the unscaled std. deviation of the coefficient estimators (alphas) instead of the contrasts estimators (betas). Now things are ok.- Thanks, Another example: # my contrasts coefficients for gene[1] > fit2$coeff[1,] t0t2 t0t4 t0t6 t0t8 t0t12 t0t17 -1.0583707 -0.5563955 -0.1422278 -0.8344021 0.2376717 -0.2515570 # posterior variance for gene[1] > fit2$s2.post[1] GE102212 0.05001711 # unscaled std. deviations > head(fit$stdev.unscaled) ttoEFFw0 ttoEFFw2 ttoEFFw4 ttoEFFw6 ttoEFFw8 ttoEFFw12 ttoEFFw17 0.5773503 0.5773503 0.5773503 0.5773503 0.5773503 0.5773503 0.7071068 # moderated t-stat > fit2$coeff[1,]/fit2$stdev.unscaled[1]/sqrt(fit2$s2.post[1]) t0t2 t0t4 t0t6 t0t8 t0t12 t0t17 -5.7959432 -3.0469823 -0.7788807 -4.5694269 1.3015588 -1.3775986 # moderated t-stat > fit2$t[1,] t0t2 t0t4 t0t6 t0t8 t0t12 t0t17 -5.7959432 -3.0469823 -0.7788807 -4.5694269 1.3015588 -1.2321617 pedro.- -----Mensaje original----- De: Jenny Drnevich [mailto:drnevich at uiuc.edu] Enviado el: jueves, 06 de julio de 2006 18:26 Para: Pedro L?pez Romero; bioconductor at stat.math.ethz.ch Asunto: Re: [BioC] moderated t statistic in limma Hi Pedro, If you look at the code for 'ebayes', you'll see that the moderated t is calculated as: out$t <- coefficients/stdev.unscaled/sqrt(out$s2.post) However, when I check with the numbers you show, I don't get the same answer as your fit2$t[1] either, so I don't know what's going on with your data: > -0.0468 / 0.5774 / sqrt(0.5344) [1] -0.1108756 Could a rounding issue make the resulting value that far off? Best, Jenny At 06:32 AM 7/6/2006, Pedro L?pez Romero wrote: >Dear list > >I am trying to calculate the moderated t-statistic by hand for a given >gene[i], and it is not equal to the moderated t value that eBayes ( ) >gives.- > > >After fitting my model I can recover the following values for gene [1] : > > > fit$stdev.unscaled[1] # from lmFit (...,) >[1] 0.5774 > > > fit2$coeff[1] # from eBayes(...,) >[1] -0.0468 > > > fit2$s2.post[1] >[1] 0.5344 > > > fit2$t[1] >[1] -0.1421 > > >and *manually* the moderated t-statistic is: > > > fit2$coeff[1]/(fit$stdev.unscaled[1]*fit2$s2.post[1]) >[1] -0.1517 > > >Did I do something wrong? > >Thanks a lot.- > >Pedro > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor >Search the archives: >http://news.gmane.org/gmane.science.biology.informatics.conductor 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

ADD REPLY • link 18.4 years ago Pedro López Romero ▴ 360

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