On 5/3/2012 9:48 AM, Steve Lianoglou wrote: > Hi, > > On Thu, May 3, 2012 at 3:59 AM, chris Jhon<cjhon217 at="" gmail.com=""> wrote: >> Hi All, >> >> I read the manual of glmFit and fitLRT functions but i would appreciate if >> any one can explain or (send me a tutorial) about the basics of fitting >> binomial generalized linear model to a data. > Is it the "negative binomial" part, or the "glm" part that you are > curious about learning? Or are you curious about how one actually > "fits" a model to data? > > This is a hard question to answer because there's just so much to know > and it's unclear what you mean by "the basics" since ... well ... > depending on your background it's not all that basic ;-) > > Have you read through: > http://en.wikipedia.org/wiki/Generalized_linear_model > > Lots of refs there including a link to McCullagh& Nelder Textbook if OMG McCullagh & Nelder please make it stop... Save yourself while you still can... <dies under="" a="" pile="" of="" greek="" letters=""> > that's what you're interested in. There's also lots of things that pop > up when you google "fit glm" (it's not just R help pages, either ;-) > > -steve > -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099

Dear All, Thank you very much. Regards, Chris On Sun, May 6, 2012 at 9:10 AM, Gordon K Smyth <smyth@wehi.edu.au> wrote: > Dear Chris, > > Steve has asked you some highly relevant questions and suggested a > reference on glms. I will clarify some other issues. > > I assume you are actually refering to the glmFit() and glmLRT() functions > in the edgeR package (I admit that I have myself written fitLRT instead of > glmLRT on occasion.) These functions fit negative binomial rather than > binomial glms. And they do this in a parallelized fashion to multiple > response vectors. > > The algorithm and strategy of the glmFit() function is outlined in the > publication: > > McCarthy et al "Differential expression analysis of multifactor > RNA-Seq experiments with respect to biological variation", > Nucleic Acids Research 2012 > http://www.ncbi.nlm.nih.gov/**pubmed/22287627<http: www.ncbi.nlm.n="" ih.gov="" pubmed="" 22287627=""> > > I have also updated the documentation page for these functions in the past > few days to give better points to the lower level functions that they call. > > However you should not expect an elementary tutorial on these algorithms, > because they are not elementary by any stretch of the imagination, or at > least so it seems to me. Indeed, the whole intention of the edgeR package > is that it should give biological researchers access to statistically > advanced algorithms without their having to worry too much about the > numerics under the hood. > > Best wishes > Gordon > > Date: Thu, 3 May 2012 09:48:03 -0400 >> From: Steve Lianoglou <mailinglist.honeypot@gmail.**com<mailinglist.honeypot@gmail.com> >> > >> To: chris Jhon <cjhon217@gmail.com> >> Cc: bioconductor@r-project.org >> Subject: Re: [BioC] basics of GLMFit >> >> Hi, >> >> On Thu, May 3, 2012 at 3:59 AM, chris Jhon <cjhon217@gmail.com> wrote: >> >>> Hi All, >>> >>> I read the manual of glmFit and fitLRT functions but i would appreciate >>> if >>> any one can explain or (send me a tutorial) about the basics of fitting >>> binomial generalized linear model to a data. >>> >>> Thank you. >>> Regards, >>> Chris >>> >> >> Is it the "negative binomial" part, or the "glm" part that you are >> curious about learning? Or are you curious about how one actually >> "fits" a model to data? >> >> This is a hard question to answer because there's just so much to know >> and it's unclear what you mean by "the basics" since ... well ... >> depending on your background it's not all that basic ;-) >> >> Have you read through: >> http://en.wikipedia.org/wiki/**Generalized_linear_model<http: en.w="" ikipedia.org="" wiki="" generalized_linear_model=""> >> >> Lots of refs there including a link to McCullagh & Nelder Textbook if >> that's what you're interested in. There's also lots of things that pop >> up when you google "fit glm" (it's not just R help pages, either ;-) >> >> -steve >> >> -- >> Steve Lianoglou >> Graduate Student: Computational Systems Biology >> ?| Memorial Sloan-Kettering Cancer Center >> ?| Weill Medical College of Cornell University >> Contact Info: http://cbio.mskcc.org/~lianos/**contact<http: cbio.m="" skcc.org="" ~lianos="" contact=""> >> > > ______________________________**______________________________**____ ______ > The information in this email is confidential and inte...{{dropped:10}}