edgeR: summary of differentially expressed genes or tags
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KJ Lim ▴ 420
@kj-lim-5288
Last seen 4.3 years ago
Finland
Dear edgeR community, Good day. I can learn summary of the up and down regulated genes/tags from >summary(de <- decideTestsDGE(lrt)) when the *coef *of *glmLRT*(the likelihood ratio test) is set to one degree of freedom. When the *coef* is set to i.e. 2:5; the decideTestsDGE doesn't work. It could be nice to see the summary of up and down regulated genes/tags when the *coef* is set i.e. 2:5. Thus, may I ask is there any method to learn the number of up and down regulated genes/tags when the *coef* of *glmLRT*(the likelihood ratio test) is set to all groups? Thank you very much for your guys time and help. Have a nice weekend. Best regards, KJ Lim [[alternative HTML version deleted]]
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@gordon-smyth
Last seen 2 hours ago
WEHI, Melbourne, Australia
Dear KJ Lim, When testing for multiple coefficients, the easiest way to learn the number of differentially expressed genes is by: FDR <- p.adjust(ltr$PValue, method="BH") sum(FDR < 0.05) There is however no unambiguous way to break this down by up and down genes. There is no unambiguous way to classify a gene as up or down with respect to multiple coefficients, because the coefficients may change in different directions for the same gene. Best wishes Gordon > Date: Sat, 2 Jun 2012 18:19:32 +0300 > From: KJ Lim <jinkeanlim at="" gmail.com=""> > To: Bioconductor mailing list <bioconductor at="" r-project.org=""> > Subject: [BioC] edgeR: summary of differentially expressed genes or > tags > > Dear edgeR community, > > Good day. > > I can learn summary of the up and down regulated genes/tags from > >summary(de <- decideTestsDGE(lrt)) > when the *coef *of *glmLRT*(the likelihood ratio test) is set to one degree > of freedom. > > When the *coef* is set to i.e. 2:5; the decideTestsDGE doesn't work. It > could be nice to see the summary of up and down regulated genes/tags when > the *coef* is set i.e. 2:5. > > Thus, may I ask is there any method to learn the number of up and down > regulated genes/tags when the *coef* of *glmLRT*(the likelihood ratio test) is > set to all groups? > > Thank you very much for your guys time and help. > > Have a nice weekend. > > Best regards, > KJ Lim ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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Dear Prof Gordon, Thanks for your suggestion and explanation. How could I never thought about the expression (up or down-regulated) of same genes may change when test on multiple coefficients! Thanks for your time and help. Have a nice day. Best regards, KJ Lim On 4 June 2012 04:11, Gordon K Smyth <smyth@wehi.edu.au> wrote: > Dear KJ Lim, > > When testing for multiple coefficients, the easiest way to learn the > number of differentially expressed genes is by: > > FDR <- p.adjust(ltr$PValue, method="BH") > sum(FDR < 0.05) > > There is however no unambiguous way to break this down by up and down > genes. There is no unambiguous way to classify a gene as up or down with > respect to multiple coefficients, because the coefficients may change in > different directions for the same gene. > > Best wishes > Gordon > > Date: Sat, 2 Jun 2012 18:19:32 +0300 >> From: KJ Lim <jinkeanlim@gmail.com> >> To: Bioconductor mailing list <bioconductor@r-project.org> >> Subject: [BioC] edgeR: summary of differentially expressed genes or >> tags >> >> Dear edgeR community, >> >> Good day. >> >> I can learn summary of the up and down regulated genes/tags from >> >summary(de <- decideTestsDGE(lrt)) >> when the *coef *of *glmLRT*(the likelihood ratio test) is set to one >> degree >> of freedom. >> >> When the *coef* is set to i.e. 2:5; the decideTestsDGE doesn't work. It >> could be nice to see the summary of up and down regulated genes/tags when >> the *coef* is set i.e. 2:5. >> >> Thus, may I ask is there any method to learn the number of up and down >> regulated genes/tags when the *coef* of *glmLRT*(the likelihood ratio >> test) is >> set to all groups? >> >> Thank you very much for your guys time and help. >> >> Have a nice weekend. >> >> Best regards, >> KJ Lim >> > > > ______________________________**______________________________**____ ______ > The information in this email is confidential and inte...{{dropped:10}}
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Page 51 of the edgeR User's Guide (4 May 2012) gives an example of this. Gordon On Mon, 4 Jun 2012, KJ Lim wrote: > Dear Prof Gordon, > > Thanks for your suggestion and explanation. > > How could I never thought about the expression (up or down- regulated) of > same genes may change when test on multiple coefficients! Thanks for your > time and help. Have a nice day. > > Best regards, > KJ Lim > > On 4 June 2012 04:11, Gordon K Smyth <smyth at="" wehi.edu.au=""> wrote: > >> Dear KJ Lim, >> >> When testing for multiple coefficients, the easiest way to learn the >> number of differentially expressed genes is by: >> >> FDR <- p.adjust(ltr$PValue, method="BH") >> sum(FDR < 0.05) >> >> There is however no unambiguous way to break this down by up and down >> genes. There is no unambiguous way to classify a gene as up or down with >> respect to multiple coefficients, because the coefficients may change in >> different directions for the same gene. >> >> Best wishes >> Gordon >> >> Date: Sat, 2 Jun 2012 18:19:32 +0300 >>> From: KJ Lim <jinkeanlim at="" gmail.com=""> >>> To: Bioconductor mailing list <bioconductor at="" r-project.org=""> >>> Subject: [BioC] edgeR: summary of differentially expressed genes or >>> tags >>> >>> Dear edgeR community, >>> >>> Good day. >>> >>> I can learn summary of the up and down regulated genes/tags from >>> >summary(de <- decideTestsDGE(lrt)) >>> when the *coef *of *glmLRT*(the likelihood ratio test) is set to one >>> degree >>> of freedom. >>> >>> When the *coef* is set to i.e. 2:5; the decideTestsDGE doesn't work. It >>> could be nice to see the summary of up and down regulated genes/tags when >>> the *coef* is set i.e. 2:5. >>> >>> Thus, may I ask is there any method to learn the number of up and down >>> regulated genes/tags when the *coef* of *glmLRT*(the likelihood ratio >>> test) is >>> set to all groups? >>> >>> Thank you very much for your guys time and help. >>> >>> Have a nice weekend. >>> >>> Best regards, >>> KJ Lim >>> >> >> >> ______________________________**______________________________**___ _______ >> The information in this email is confidential and intended solely for the >> addressee. >> You must not disclose, forward, print or use it without the permission of >> the sender. >> ______________________________**______________________________**___ _______ >> > ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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Correcting a typo in my previous post. Code should have been: FDR <- p.adjust(lrt$table$PValue, method="BH") sum(FDR < 0.05) Gordon ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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