Question: microarray analysis of a dose response * strain experiment
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gravatar for Kimpel, Mark W
13.0 years ago by
Kimpel, Mark W890 wrote:
My group is writing a grant with a proposed dose response experiment on two different rat strains that I have been tasked to provide an analysis method for. Briefly, we have two rat strains that have different preferences for alcohol (one drinks, the other doesn't). We are going to give each line injections for alcohol to see if gene expression in the brain is differentially affected between the 3 strains. We don't, however, know which of several possible doses of alcohol will provide the greatest effect on each of the thousands of genes on our Affy chipset. So, we are proposing to give each line one of 4 doses (zero, 0.5, 1.0, and 2.0 mg/kg). For any gene, we have no way of knowing a priori what shape the dose response curve will take. We are, for screening purposes, not really interested in the shape of the curve, only that it is not a line with a slope of zero (i.e. no response). We are also, for screening purposed, only interested to know, for each gene, if the response of strain A is different from strain B. In other words, what we want to know is the interaction between strain and dose response. I have searched the literature and the Bioconductor mailing list and cannot find a reference to an experiment of this sort. Can anyone provide some advice? Thanks, Mark Mark W. Kimpel MD ? Official Business Address: ? Department of Psychiatry Indiana University School of Medicine PR M116 Institute of Psychiatric Research 791 Union Drive Indianapolis, IN 46202 ? Preferred Mailing Address: ? 15032 Hunter Court Westfield, IN? 46074 ? (317) 490-5129 Work, & Mobile ? (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX
affy dose brain • 636 views
ADD COMMENTlink modified 13.0 years ago by Sean Davis21k • written 13.0 years ago by Kimpel, Mark W890
Answer: microarray analysis of a dose response * strain experiment
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gravatar for Sean Davis
13.0 years ago by
Sean Davis21k
United States
Sean Davis21k wrote:
On Saturday 04 November 2006 13:20, Kimpel, Mark William wrote: > My group is writing a grant with a proposed dose response experiment on two > different rat strains that I have been tasked to provide an analysis method > for. Briefly, we have two rat strains that have different preferences for > alcohol (one drinks, the other doesn't). We are going to give each line > injections for alcohol to see if gene expression in the brain is > differentially affected between the 3 strains. We don't, however, know > which of several possible doses of alcohol will provide the greatest effect > on each of the thousands of genes on our Affy chipset. So, we are proposing > to give each line one of 4 doses (zero, 0.5, 1.0, and 2.0 mg/kg). For any > gene, we have no way of knowing a priori what shape the dose response curve > will take. We are, for screening purposes, not really interested in the > shape of the curve, only that it is not a line with a slope of zero (i.e. > no response). We are also, for screening purposed, only interested to know, > for each gene, if the response of strain A is different from strain B. In > other words, what we want to know is the interaction between strain and > dose response. > > I have searched the literature and the Bioconductor mailing list and cannot > find a reference to an experiment of this sort. Can anyone provide some > advice? This can't be handled with a linear model? Sean
ADD COMMENTlink written 13.0 years ago by Sean Davis21k
Sean, Perhaps it will have to be, I can think of two ways to do that and neither seems entirely satisfactory. Firstly, one could assume that the response (for responding genes) would be linearly related to the dose or the log of the dose, but this might not be the case. So regressing by dose in a linear model might not be correct for all or even most of the affected genes. Secondly, one could simply assume that the dose is a factor with 4 non-ordered levels and look at contrasts and interactions for each level. This would be the approach I am most familiar with using Limma. This would, however, seem to be throwing information away regarding the relationship of the doses to one another. Mark Mark W. Kimpel MD (317) 490-5129 Work, & Mobile (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX -----Original Message----- From: Sean Davis [mailto:sdavis2@mail.nih.gov] Sent: Saturday, November 04, 2006 1:39 PM To: bioconductor at stat.math.ethz.ch Cc: Kimpel, Mark William; McBride, William J. Subject: Re: [BioC] microarray analysis of a dose response * strain experiment On Saturday 04 November 2006 13:20, Kimpel, Mark William wrote: > My group is writing a grant with a proposed dose response experiment on two > different rat strains that I have been tasked to provide an analysis method > for. Briefly, we have two rat strains that have different preferences for > alcohol (one drinks, the other doesn't). We are going to give each line > injections for alcohol to see if gene expression in the brain is > differentially affected between the 3 strains. We don't, however, know > which of several possible doses of alcohol will provide the greatest effect > on each of the thousands of genes on our Affy chipset. So, we are proposing > to give each line one of 4 doses (zero, 0.5, 1.0, and 2.0 mg/kg). For any > gene, we have no way of knowing a priori what shape the dose response curve > will take. We are, for screening purposes, not really interested in the > shape of the curve, only that it is not a line with a slope of zero (i.e. > no response). We are also, for screening purposed, only interested to know, > for each gene, if the response of strain A is different from strain B. In > other words, what we want to know is the interaction between strain and > dose response. > > I have searched the literature and the Bioconductor mailing list and cannot > find a reference to an experiment of this sort. Can anyone provide some > advice? This can't be handled with a linear model? Sean
ADD REPLYlink written 13.0 years ago by Kimpel, Mark W890
Hi Mark I recommend you to have a look to the maSigPro package and the corresponding publication (Bioinformatics 2006 22(9):1096-1102). The methodology has been designed for decting genes that change between experimental conditions on a data series, normally this would be different treatments along the time component, but could also be different strains along a increasing dose value. You can model different type of responses (linear, quadratic or more sophisticated) although the method finnaly finds the model most suited for each gene. The method does not focus on pair-wise comparisons, but rather detects differences in expression patterns between conditons (thus, strain- dose interactions) or genes that significantly change "somewhere". I hope this package suits your analysis needs Best regards Ana On Sat, 4 Nov 2006 14:45:37 -0500, Kimpel, Mark William wrote > Sean, > > Perhaps it will have to be, I can think of two ways to do that and > neither seems entirely satisfactory. Firstly, one could assume that the > response (for responding genes) would be linearly related to the > dose or the log of the dose, but this might not be the case. So > regressing by dose in a linear model might not be correct for all or > even most of the affected genes. Secondly, one could simply assume > that the dose is a factor with 4 non-ordered levels and look at > contrasts and interactions for each level. This would be the > approach I am most familiar with using Limma. This would, however, > seem to be throwing information away regarding the relationship of > the doses to one another. > > Mark > > Mark W. Kimpel MD > > (317) 490-5129 Work, & Mobile > > (317) 663-0513 Home (no voice mail please) > > 1-(317)-536-2730 FAX > > -----Original Message----- > From: Sean Davis [mailto:sdavis2 at mail.nih.gov] > Sent: Saturday, November 04, 2006 1:39 PM > To: bioconductor at stat.math.ethz.ch > Cc: Kimpel, Mark William; McBride, William J. > Subject: Re: [BioC] microarray analysis of a dose response * strain > experiment > > On Saturday 04 November 2006 13:20, Kimpel, Mark William wrote: > > My group is writing a grant with a proposed dose response experiment > on two > > different rat strains that I have been tasked to provide an analysis > method > > for. Briefly, we have two rat strains that have different preferences > for > > alcohol (one drinks, the other doesn't). We are going to give each > line > > injections for alcohol to see if gene expression in the brain is > > differentially affected between the 3 strains. We don't, however, know > > which of several possible doses of alcohol will provide the greatest > effect > > on each of the thousands of genes on our Affy chipset. So, we are > proposing > > to give each line one of 4 doses (zero, 0.5, 1.0, and 2.0 mg/kg). For > any > > gene, we have no way of knowing a priori what shape the dose response > curve > > will take. We are, for screening purposes, not really interested in > the > > shape of the curve, only that it is not a line with a slope of zero > (i.e. > > no response). We are also, for screening purposed, only interested to > know, > > for each gene, if the response of strain A is different from strain B. > In > > other words, what we want to know is the interaction between strain > and > > dose response. > > > > I have searched the literature and the Bioconductor mailing list and > cannot > > find a reference to an experiment of this sort. Can anyone provide > some > > advice? > > This can't be handled with a linear model? > > Sean > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- IVIA (http://www.ivia.es) Open WebMail Project (http://openwebmail.org) Debian Project (http://www.debian.org)
ADD REPLYlink written 13.0 years ago by Ana Conesa140
Thanks Ana, I will take a look :) Mark Mark W. Kimpel MD (317) 490-5129 Work, & Mobile (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX -----Original Message----- From: Ana Conesa [mailto:aconesa@ivia.es] Sent: Saturday, November 04, 2006 4:04 PM To: Kimpel, Mark William; sdavis2 at mail.nih.gov; bioconductor at stat.math.ethz.ch Cc: McBride, William J. Subject: Re: [BioC] microarray analysis of a dose response * strain experiment Hi Mark I recommend you to have a look to the maSigPro package and the corresponding publication (Bioinformatics 2006 22(9):1096-1102). The methodology has been designed for decting genes that change between experimental conditions on a data series, normally this would be different treatments along the time component, but could also be different strains along a increasing dose value. You can model different type of responses (linear, quadratic or more sophisticated) although the method finnaly finds the model most suited for each gene. The method does not focus on pair-wise comparisons, but rather detects differences in expression patterns between conditons (thus, strain- dose interactions) or genes that significantly change "somewhere". I hope this package suits your analysis needs Best regards Ana On Sat, 4 Nov 2006 14:45:37 -0500, Kimpel, Mark William wrote > Sean, > > Perhaps it will have to be, I can think of two ways to do that and > neither seems entirely satisfactory. Firstly, one could assume that the > response (for responding genes) would be linearly related to the > dose or the log of the dose, but this might not be the case. So > regressing by dose in a linear model might not be correct for all or > even most of the affected genes. Secondly, one could simply assume > that the dose is a factor with 4 non-ordered levels and look at > contrasts and interactions for each level. This would be the > approach I am most familiar with using Limma. This would, however, > seem to be throwing information away regarding the relationship of > the doses to one another. > > Mark > > Mark W. Kimpel MD > > (317) 490-5129 Work, & Mobile > > (317) 663-0513 Home (no voice mail please) > > 1-(317)-536-2730 FAX > > -----Original Message----- > From: Sean Davis [mailto:sdavis2 at mail.nih.gov] > Sent: Saturday, November 04, 2006 1:39 PM > To: bioconductor at stat.math.ethz.ch > Cc: Kimpel, Mark William; McBride, William J. > Subject: Re: [BioC] microarray analysis of a dose response * strain > experiment > > On Saturday 04 November 2006 13:20, Kimpel, Mark William wrote: > > My group is writing a grant with a proposed dose response experiment > on two > > different rat strains that I have been tasked to provide an analysis > method > > for. Briefly, we have two rat strains that have different preferences > for > > alcohol (one drinks, the other doesn't). We are going to give each > line > > injections for alcohol to see if gene expression in the brain is > > differentially affected between the 3 strains. We don't, however, know > > which of several possible doses of alcohol will provide the greatest > effect > > on each of the thousands of genes on our Affy chipset. So, we are > proposing > > to give each line one of 4 doses (zero, 0.5, 1.0, and 2.0 mg/kg). For > any > > gene, we have no way of knowing a priori what shape the dose response > curve > > will take. We are, for screening purposes, not really interested in > the > > shape of the curve, only that it is not a line with a slope of zero > (i.e. > > no response). We are also, for screening purposed, only interested to > know, > > for each gene, if the response of strain A is different from strain B. > In > > other words, what we want to know is the interaction between strain > and > > dose response. > > > > I have searched the literature and the Bioconductor mailing list and > cannot > > find a reference to an experiment of this sort. Can anyone provide > some > > advice? > > This can't be handled with a linear model? > > Sean > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- IVIA (http://www.ivia.es) Open WebMail Project (http://openwebmail.org) Debian Project (http://www.debian.org)
ADD REPLYlink written 13.0 years ago by Kimpel, Mark W890
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