edgeR: DE summary of decideTestsDGE
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KJ Lim ▴ 420
@kj-lim-5288
Last seen 4.3 years ago
Finland
Dear edgeR and R community, Good day. I'm using the edgeR to analysis my RNA-Seq data which contained 2 genotype (HS,LS) and different time points (0H, 3H, 24H, 96H). The differential analysis was carried out based on the guide of the latest edgeR user's guide (Chapter 3, section 3.3). May I ask it that common to obtain the summary of differentially express (DE) genes like below? The number of DE genes seemed very little in my case, HS vs LS at 24H > summary(dt.hvsl24h <- decideTestsDGE(lrt.hvsl24h, adjust.method="BH", p.value=0.05)) [,1] -1 3 0 46997 1 4 The summary of DE genes was none when I carried out the decideTestDGE for the HS vs LS at 96H. May I ask is that common or I have done something wrong in between? Thank you very much for your time and advice. Have a nice day. Best regards, KJ Lim
edgeR edgeR • 2.9k views
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Yunshun Chen ▴ 900
@yunshun-chen-5451
Last seen 28 days ago
Australia
Dear KJ, I cannot tell whether you have done something wrong without more detail of your analysis. Presumably you used the GLM approach and the likelihood ratio test for identifying DE genes, and if you followed the users guide then the results should be correct. I think it is just because those samples are not very different from each other, which is possible for some RNA-Seq data sets. One way to look at the difference between those samples visually is to plot the Smear plots (see case studies in the users guide), and see whether you have a lot of genes with large logFC. Best Wishes, Yunshun Chen > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 13 Aug 2012 13:54:09 +0300 > From: KJ Lim<jinkeanlim at="" gmail.com=""> > To: Bioconductor mailing list<bioconductor at="" r-project.org=""> > Subject: [BioC] edgeR: DE summary of decideTestsDGE > Message-ID: > <cadu1pczupg6g24-27m_h3h-cwelfw415emjhk+-hqwjgxaxiyq at="" mail.gmail.com=""> > Content-Type: text/plain; charset=UTF-8 > > Dear edgeR and R community, > > Good day. > > I'm using the edgeR to analysis my RNA-Seq data which contained 2 > genotype (HS,LS) and different time points (0H, 3H, 24H, 96H). The > differential analysis was carried out based on the guide of the latest > edgeR user's guide (Chapter 3, section 3.3). > > May I ask it that common to obtain the summary of differentially > express (DE) genes like below? The number of DE genes seemed very > little in my case, HS vs LS at 24H > > > summary(dt.hvsl24h<- decideTestsDGE(lrt.hvsl24h, > adjust.method="BH", p.value=0.05)) > [,1] > -1 3 > 0 46997 > 1 4 > > The summary of DE genes was none when I carried out the decideTestDGE > for the HS vs LS at 96H. May I ask is that common or I have done > something wrong in between? > > Thank you very much for your time and advice. > > Have a nice day. > > Best regards, > KJ Lim > > -- Yunshun Chen, PhD Student, Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Vic 3052, Australia. yuchen at wehi.edu.au http://www.wehi.edu.au ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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Dear YunShun, Thanks for your replied. I'm using the GLM approach and the likelihood ratio test to get the DE genes as suggested in the user's guide. The high value of BCV for my RNA-Seq data set hints me that my samples are properly not very much different with each other. Thank you for your time and suggestion. Have a nice weekend. Best regards, KJ Lim On 16 August 2012 08:04, Yunshun Chen <yuchen@wehi.edu.au> wrote: > Dear KJ, > > I cannot tell whether you have done something wrong without more detail of > your analysis. > Presumably you used the GLM approach and the likelihood ratio test for > identifying DE genes, and if you followed the users guide then the results > should be correct. > I think it is just because those samples are not very different from each > other, which is possible for some RNA-Seq data sets. > One way to look at the difference between those samples visually is to > plot the Smear plots (see case studies in the users guide), and see whether > you have a lot of genes with large logFC. > > Best Wishes, > Yunshun Chen > > ------------------------------**------------------------------** >> ---------- >> >> Message: 1 >> Date: Mon, 13 Aug 2012 13:54:09 +0300 >> From: KJ Lim<jinkeanlim@gmail.com> >> To: Bioconductor mailing list<bioconductor@r-project.**org<bioconductor@r-project.org> >> > >> Subject: [BioC] edgeR: DE summary of decideTestsDGE >> Message-ID: >> <cadu1pczupg6g24-27m_h3h-**cwelfw415emjhk+-hqwjgxaxiyq@**>> mail.gmail.com<cadu1pczupg6g24-27m_h3h-cwelfw415emjhk%2b- hqwjgxaxiyq@mail.gmail.com=""> >> > >> Content-Type: text/plain; charset=UTF-8 >> >> >> Dear edgeR and R community, >> >> Good day. >> >> I'm using the edgeR to analysis my RNA-Seq data which contained 2 >> genotype (HS,LS) and different time points (0H, 3H, 24H, 96H). The >> differential analysis was carried out based on the guide of the latest >> edgeR user's guide (Chapter 3, section 3.3). >> >> May I ask it that common to obtain the summary of differentially >> express (DE) genes like below? The number of DE genes seemed very >> little in my case, HS vs LS at 24H >> >> > summary(dt.hvsl24h<- decideTestsDGE(lrt.hvsl24h, >> adjust.method="BH", p.value=0.05)) >> [,1] >> -1 3 >> 0 46997 >> 1 4 >> >> The summary of DE genes was none when I carried out the decideTestDGE >> for the HS vs LS at 96H. May I ask is that common or I have done >> something wrong in between? >> >> Thank you very much for your time and advice. >> >> Have a nice day. >> >> Best regards, >> KJ Lim >> >> >> > > -- > Yunshun Chen, > PhD Student, > Bioinformatics Division, > Walter and Eliza Hall Institute of Medical Research, > 1G Royal Parade, Parkville, Vic 3052, Australia. > yuchen@wehi.edu.au > http://www.wehi.edu.au > > > ______________________________**______________________________**____ ______ > The information in this email is confidential and inte...{{dropped:10}}
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