Question: edgeR: design matrix
0
gravatar for KJ Lim
7.3 years ago by
KJ Lim420
Finland
KJ Lim420 wrote:
I'm sorry to trouble you guys. I have a doubt about my design matrix. I have RNA-seq data for 2 different genotype of trees with 0hour(control) and after treatment 3hours,24hours,and 48hours. The experiment design like following: Treatment Tree H1 Ctrl 3hrs 24hrs 48hrs Tree H2 Ctrl 3hrs 24hrs 48hrs Tree L1 Ctrl 3hrs 24hrs 48hrs Tree L2 Ctrl 3hrs 24hrs 48hrs I have assigned 2 factor vectors as: "tree" --> vector for the trees. "trtTime" --> vector for the control and after treatment time. I would like to study which genes/tags that are differential expressed in these H and L trees across the after treatment time points. Can I assign my design matrix in this way: design <- model.matrix(~trtTime+tree) OR design <-model.matrix(~tree+trtTime) I may wrong in this case as I'm not a statistician nor R programming geek. Thus, could someone kindly please light me? I appreciate very much for your help. Best regards, KJ Lim [[alternative HTML version deleted]]
assign • 658 views
ADD COMMENTlink modified 7.3 years ago by Gordon Smyth38k • written 7.3 years ago by KJ Lim420
Answer: edgeR: design matrix
0
gravatar for KJ Lim
7.3 years ago by
KJ Lim420
Finland
KJ Lim420 wrote:
An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20120526="" 2fcc5dfb="" attachment-0001.pl="">
ADD COMMENTlink written 7.3 years ago by KJ Lim420
Answer: edgeR: design matrix
0
gravatar for KJ Lim
7.3 years ago by
KJ Lim420
Finland
KJ Lim420 wrote:
I'm sorry to trouble you guys. I have a doubt about my design matrix. I have RNA-seq data for 2 different genotype of trees with 0hour(control) and after treatment 3hours,24hours,and 48hours. The experiment design like following: Treatment Tree H1 Ctrl 3hrs 24hrs 48hrs Tree H2 Ctrl 3hrs 24hrs 48hrs Tree L1 Ctrl 3hrs 24hrs 48hrs Tree L2 Ctrl 3hrs 24hrs 48hrs I have assigned 2 factor vectors as: "tree" --> vector for the trees. "trtTime" --> vector for the control and after treatment time. I would like to study which genes/tags that are differential expressed in these H and L trees across the after treatment time points. Can I assign my design matrix in this way: design <- model.matrix(~trtTime+tree) OR design <-model.matrix(~tree+trtTime) I may wrong in this case as I'm not a statistician nor R programming geek. Thus, could someone kindly please light me? I appreciate very much for your help. Best regards, KJ Lim [[alternative HTML version deleted]]
ADD COMMENTlink written 7.3 years ago by KJ Lim420
Answer: edgeR: design matrix
0
gravatar for Gordon Smyth
7.3 years ago by
Gordon Smyth38k
Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Gordon Smyth38k wrote:
Dear KJ Lim, You seem to have posted almost the same question to this list on three separate occasions a week apart, and it isn't clear whether you've taken much notice of the help you got from Mark Robinson the first time. So it is indeed troubling to us guys. Rather than trying to design a complete analysis for you, can I refer you to advice I gave to another poster recently: https://www.stat.math.ethz.ch/pipermail/bioconductor/2012-May/045700.h tml I suggest that you try using the "longer method", explained in the second half of my message to that poster, to setup your design matrix, after which you will be to draw any comparisons between the treatments that seem sensible to you. Of course you will need to adapt it somewhat to your data. This is probably better than trying to use model formula in R that might not be clear to you. Best wishes Gordon > Date: Sat, 26 May 2012 14:06:29 +0300 > From: KJ Lim <jinkeanlim at="" gmail.com=""> > To: bioconductor at r-project.org > Cc: bioconductor at stat.math.ethz.ch > Subject: [BioC] edgeR: design matrix > > I'm sorry to trouble you guys. I have a doubt about my design matrix. > > I have RNA-seq data for 2 different genotype of trees with > 0hour(control) and after treatment 3hours,24hours,and 48hours. The > experiment design like following: > > Treatment > Tree H1 Ctrl 3hrs 24hrs 48hrs > Tree H2 Ctrl 3hrs 24hrs 48hrs > Tree L1 Ctrl 3hrs 24hrs 48hrs > Tree L2 Ctrl 3hrs 24hrs 48hrs > > I have assigned 2 factor vectors as: > "tree" --> vector for the trees. > "trtTime" --> vector for the control and after treatment time. > > I would like to study which genes/tags that are differential expressed > in these H and L trees across the after treatment time points. > > Can I assign my design matrix in this way: > > design <- model.matrix(~trtTime+tree) OR design <-model.matrix(~tree+trtTime) > > I may wrong in this case as I'm not a statistician nor R programming > geek. Thus, could someone kindly please light me? > > I appreciate very much for your help. > > Best regards, > KJ Lim ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
ADD COMMENTlink written 7.3 years ago by Gordon Smyth38k
Dear Prof Gordon Smyth, I'm sorry for the triple postings. I may have configured wrongly for my mailing list setting as I don't see my post was in mailing list loop. Thus, I resubmitted my post again. I subscribing this mailing list via Gmane tool. The suggestion of Prof Mark Robinson is helpful and I appreciated. I will have a look on the post you have referred to. Thanks for your time and suggestion. Once again, I'm sorry for the triple postings. I'm sorry for any inconvenience caused. Best regards, KJ Lim On 28 May 2012 12:02, Gordon K Smyth <smyth@wehi.edu.au> wrote: > Dear KJ Lim, > > You seem to have posted almost the same question to this list on three > separate occasions a week apart, and it isn't clear whether you've taken > much notice of the help you got from Mark Robinson the first time. So it > is indeed troubling to us guys. > > Rather than trying to design a complete analysis for you, can I refer you > to advice I gave to another poster recently: > > https://www.stat.math.ethz.ch/**pipermail/bioconductor/2012-** > May/045700.html<https: www.stat.math.ethz.ch="" pipermail="" bioconductor="" 2012-may="" 045700.html=""> > > I suggest that you try using the "longer method", explained in the second > half of my message to that poster, to setup your design matrix, after which > you will be to draw any comparisons between the treatments that seem > sensible to you. Of course you will need to adapt it somewhat to your > data. This is probably better than trying to use model formula in R that > might not be clear to you. > > Best wishes > Gordon > > Date: Sat, 26 May 2012 14:06:29 +0300 >> From: KJ Lim <jinkeanlim@gmail.com> >> To: bioconductor@r-project.org >> Cc: bioconductor@stat.math.ethz.ch >> Subject: [BioC] edgeR: design matrix >> >> I'm sorry to trouble you guys. I have a doubt about my design matrix. >> >> I have RNA-seq data for 2 different genotype of trees with >> 0hour(control) and after treatment 3hours,24hours,and 48hours. The >> experiment design like following: >> >> Treatment >> Tree H1 Ctrl 3hrs 24hrs 48hrs >> Tree H2 Ctrl 3hrs 24hrs 48hrs >> Tree L1 Ctrl 3hrs 24hrs 48hrs >> Tree L2 Ctrl 3hrs 24hrs 48hrs >> >> I have assigned 2 factor vectors as: >> "tree" --> vector for the trees. >> "trtTime" --> vector for the control and after treatment time. >> >> I would like to study which genes/tags that are differential expressed >> in these H and L trees across the after treatment time points. >> >> Can I assign my design matrix in this way: >> >> design <- model.matrix(~trtTime+tree) OR design >> <-model.matrix(~tree+trtTime) >> >> I may wrong in this case as I'm not a statistician nor R programming >> geek. Thus, could someone kindly please light me? >> >> I appreciate very much for your help. >> >> Best regards, >> KJ Lim >> > > ______________________________**______________________________**____ ______ > The information in this email is confidential and inte...{{dropped:10}}
ADD REPLYlink written 7.3 years ago by KJ Lim420
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 231 users visited in the last hour