LIMMA with beta distributed data
1
0
Entering edit mode
Steve Shen ▴ 330
@steve-shen-3743
Last seen 10.3 years ago
Hello list, Can LIMMA work with beta distributed interval(0,1) data? Thanks, Steve [[alternative HTML version deleted]]
limma limma • 1.8k views
ADD COMMENT
0
Entering edit mode
@sunny-srivastava-3793
Last seen 10.3 years ago
Hi Steve: I am sure Prof. Smyth and others will have better insights but here is my $0.02. I would transform the data using the logit transform, that is, x_ij goes to log (x_ij / ( 1 - x_ij) ) ## with boundary value correction when x_ij = 0 or 1 And then use LIMMA. This makes sure that the data you are working with lies in [-Inf, Inf] interval. Thx, S. On Tue, Mar 29, 2011 at 8:44 PM, Steve Shen <sshen@bu.edu> wrote: > Hello list, > > Can LIMMA work with beta distributed interval(0,1) data? Thanks, > > Steve > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]
ADD COMMENT
0
Entering edit mode
Hi Sunny, Thanks so much for your input. Then, how to deal with inf or missing value after logit, because the data I am dealing with have lots of zeros in many samples. Any opinion? I wish that LIMMA can provide some link/family type of arguments just like GLM does. Thanks a lot. Steve On Wed, Mar 30, 2011 at 6:46 AM, Sunny Srivastava <research.baba@gmail.com>wrote: > Hi Steve: > > I am sure Prof. Smyth and others will have better insights but here is my > $0.02. > > I would transform the data using the logit transform, that is, > > x_ij goes to log (x_ij / ( 1 - x_ij) ) ## with boundary value correction > when x_ij = 0 or 1 > > And then use LIMMA. > > This makes sure that the data you are working with lies in [-Inf, Inf] > interval. > > Thx, > S. > > On Tue, Mar 29, 2011 at 8:44 PM, Steve Shen <sshen@bu.edu> wrote: > >> Hello list, >> >> Can LIMMA work with beta distributed interval(0,1) data? Thanks, >> >> Steve >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > [[alternative HTML version deleted]]
ADD REPLY
0
Entering edit mode
Hi Steve: I think LIMMA does the right thing by not having any link/family because it is meant *only* for log normal intensities. Using it for anything else is not correct. However, as you say you have a lot of 0s -- I would ignore them because you are trying to extract information where it is not available. You can do better by something like a zero-inflated modeling. But LIMMA is not meant for that purpose. I must say -- I am surprised you are modelling microarray data and you have zeros and observation between 0 and 1. Thanks, S. On Wed, Mar 30, 2011 at 11:55 AM, Steve Shen <sshen@bu.edu> wrote: > Hi Sunny, > > Thanks so much for your input. Then, how to deal with inf or missing value > after logit, because the data I am dealing with have lots of zeros in many > samples. Any opinion? I wish that LIMMA can provide some link/family type of > arguments just like GLM does. Thanks a lot. > > Steve > > > On Wed, Mar 30, 2011 at 6:46 AM, Sunny Srivastava <research.baba@gmail.com> > wrote: > >> Hi Steve: >> >> I am sure Prof. Smyth and others will have better insights but here is my >> $0.02. >> >> I would transform the data using the logit transform, that is, >> >> x_ij goes to log (x_ij / ( 1 - x_ij) ) ## with boundary value correction >> when x_ij = 0 or 1 >> >> And then use LIMMA. >> >> This makes sure that the data you are working with lies in [-Inf, Inf] >> interval. >> >> Thx, >> S. >> >> On Tue, Mar 29, 2011 at 8:44 PM, Steve Shen <sshen@bu.edu> wrote: >> >>> Hello list, >>> >>> Can LIMMA work with beta distributed interval(0,1) data? Thanks, >>> >>> Steve >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor@r-project.org >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >> >> > [[alternative HTML version deleted]]
ADD REPLY
0
Entering edit mode
Hi Sunny, Thanks so much. I am not using LIMMA for microarray data in this case. I like LIMMA because of its capability of modeling and ebays function. It will be a big plus if LIMMA can deal with other type of data. Thanks again and much appreciated. Speaking zero in this case, it is the true observations, not null value. I am not sure how can I ignore them. Steve On Wed, Mar 30, 2011 at 2:01 PM, Sunny Srivastava <research.baba@gmail.com>wrote: > Hi Steve: > > I think LIMMA does the right thing by not having any link/family because it > is meant *only* for log normal intensities. Using it for anything else is > not correct. > > However, as you say you have a lot of 0s -- I would ignore them because you > are trying to extract information where it is not available. You can do > better by something like a zero-inflated modeling. But LIMMA is not meant > for that purpose. > > I must say -- I am surprised you are modelling microarray data and you have > zeros and observation between 0 and 1. > > Thanks, > S. > > > > On Wed, Mar 30, 2011 at 11:55 AM, Steve Shen <sshen@bu.edu> wrote: > >> Hi Sunny, >> >> Thanks so much for your input. Then, how to deal with inf or missing value >> after logit, because the data I am dealing with have lots of zeros in many >> samples. Any opinion? I wish that LIMMA can provide some link/family type of >> arguments just like GLM does. Thanks a lot. >> >> Steve >> >> >> On Wed, Mar 30, 2011 at 6:46 AM, Sunny Srivastava < >> research.baba@gmail.com> wrote: >> >>> Hi Steve: >>> >>> I am sure Prof. Smyth and others will have better insights but here is my >>> $0.02. >>> >>> I would transform the data using the logit transform, that is, >>> >>> x_ij goes to log (x_ij / ( 1 - x_ij) ) ## with boundary value correction >>> when x_ij = 0 or 1 >>> >>> And then use LIMMA. >>> >>> This makes sure that the data you are working with lies in [-Inf, Inf] >>> interval. >>> >>> Thx, >>> S. >>> >>> On Tue, Mar 29, 2011 at 8:44 PM, Steve Shen <sshen@bu.edu> wrote: >>> >>>> Hello list, >>>> >>>> Can LIMMA work with beta distributed interval(0,1) data? Thanks, >>>> >>>> Steve >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> _______________________________________________ >>>> Bioconductor mailing list >>>> Bioconductor@r-project.org >>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>> Search the archives: >>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>> >>> >>> >> > [[alternative HTML version deleted]]
ADD REPLY

Login before adding your answer.

Traffic: 688 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6