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Question: Average expression value from limma
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gravatar for Ekta Jain
4.6 years ago by
Ekta Jain50
Ekta Jain50 wrote:
Dear Bioconductor Mailing List, I have a microarray data which i normalised using 'gcrma' followed by limma for Mock vs Treated, 3 replicates in each group. The 'topTable' returns an average expression value for each probeset. How is this exactly calculated? Also i compared this with the average expression of each probeset for all samples, such as (Embedded image moved to file: pic17982.gif) The 'Avg.Expr.from.limma' has a very high value as compared to the ones obtained from the normalised data. Is there anything wrong? Much appreciate any comments please. Regards, Ekta Jain Research Analyst Biotechnology and Bio-resources Division The Energy and Resources Institute, India Habitat Centre Lodhi Road, New Delhi - 110033 #09958818853 ekta.jain at teri.res.in ---------------------------------------------------------------------- -------------------------------------- Disclaimer: The information contained in this e-mail is intended for the person or entity to which it is addressed, and it may contain confidential and/or privileged material. Any review or other use of this mail or taking any action based on it by persons or entities other than the intended recipient is strictly prohibited. If you receive this e-mail by mistake, please contact the sender, and delete all copies of this mail.This e-mail has been scanned and verified by McAfee SaaS Email Security, formerly MX Logic.
ADD COMMENTlink modified 4.6 years ago by Gordon Smyth32k • written 4.6 years ago by Ekta Jain50
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gravatar for Paul Geeleher
4.6 years ago by
Paul Geeleher1.3k
Paul Geeleher1.3k wrote:
Normally I think you'd expect that differentially expressed genes tend to have higher average intensity. Consider that your array is measuring approx 25,000 transcripts, this means that in your tissue type many of these will not even be expressed, thus are highly unlikely to be identified as differentially expressed. These probes will obviously have the lowest flourescence intensity levels, thus skewing the overall average flourescencce intensity level towards zero. On some platforms it is possible to identify and remove these probes, for example if you're using Affymetrix Exon arrays you can apply the DABG algorithm. You'd probably still want to provide some info on how big the difference is and what the array platform is though. Paul. On Mon, May 20, 2013 at 6:15 AM, Ekta Jain <ekta.jain at="" teri.res.in=""> wrote: > > Dear Bioconductor Mailing List, > I have a microarray data which i normalised using 'gcrma' followed by limma > for Mock vs Treated, 3 replicates in each group. The 'topTable' returns an > average expression value for each probeset. How is this exactly calculated? > > Also i compared this with the average expression of each probeset for all > samples, such as > (Embedded image moved to file: pic17982.gif) > > The 'Avg.Expr.from.limma' has a very high value as compared to the ones > obtained from the normalised data. Is there anything wrong? > > Much appreciate any comments please. > > Regards, > Ekta Jain > Research Analyst > Biotechnology and Bio-resources Division > The Energy and Resources Institute, India Habitat Centre > Lodhi Road, New Delhi - 110033 > #09958818853 > ekta.jain at teri.res.in > > > -------------------------------------------------------------------- ---------------------------------------- > > Disclaimer: > > The information contained in this e-mail is intended f...{{dropped:26}}
ADD COMMENTlink written 4.6 years ago by Paul Geeleher1.3k
0
gravatar for Ekta Jain
4.6 years ago by
Ekta Jain50
Ekta Jain50 wrote:
Dear Paul, Thanks very much for your reply. My data is from rice and its an affymetrix array with 57,000 probes. The genes from limma show a high 'average expressio' for contrast of mock vs treated having 3 replicates in each group. When i do an average of the expression values of each of the three replicates from the gcrma normalised files, the value is much lower as compared to the one obtained from limma. I am unable to understand why is this so maybe becauase i do not know how limma calculates this average. Thank you, Ekta -----Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: ----- ======================= To: Ekta Jain <ekta.jain at="" teri.res.in=""> From: Paul Geeleher <paulgeeleher at="" gmail.com=""> Date: 05/20/2013 07:37PM cc: "bioconductor at r-project.org list" <bioconductor at="" r-project.org=""> Subject: Re: [BioC] Average expression value from limma ======================= Normally I think you'd expect that differentially expressed genes tend to have higher average intensity. Consider that your array is measuring approx 25,000 transcripts, this means that in your tissue type many of these will not even be expressed, thus are highly unlikely to be identified as differentially expressed. These probes will obviously have the lowest flourescence intensity levels, thus skewing the overall average flourescencce intensity level towards zero. On some platforms it is possible to identify and remove these probes, for example if you're using Affymetrix Exon arrays you can apply the DABG algorithm. You'd probably still want to provide some info on how big the difference is and what the array platform is though. Paul. On Mon, May 20, 2013 at 6:15 AM, Ekta Jain <ekta.jain at="" teri.res.in=""> wrote: > > Dear Bioconductor Mailing List, > I have a microarray data which i normalised using 'gcrma' followed by limma > for Mock vs Treated, 3 replicates in each group. The 'topTable' returns an > average expression value for each probeset. How is this exactly calculated? > > Also i compared this with the average expression of each probeset for all > samples, such as > (Embedded image moved to file: pic17982.gif) > > The 'Avg.Expr.from.limma' has a very high value as compared to the ones > obtained from the normalised data. Is there anything wrong? > > Much appreciate any comments please. > > Regards, > Ekta Jain > Research Analyst > Biotechnology and Bio-resources Division > The Energy and Resources Institute, India Habitat Centre > Lodhi Road, New Delhi - 110033 > #09958818853 > ekta.jain at teri.res.in > > > -------------------------------------------------------------------- ---------------------------------------- > > Disclaimer: > > The information contained in this e-mail is intended for the person or entity > to which it is addressed, and it may contain confidential and/or privileged > material. Any review or other use of this mail or taking any action based on it > by persons or entities other than the intended recipient is strictly prohibited. > If you receive this e-mail by mistake, please contact the sender, and delete all > copies of this mail.This e-mail has been scanned and verified by McAfee SaaS > Email Security, formerly MX Logic. > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Dr. Paul Geeleher, PhD (Bioinformatics) Section of Hematology-Oncology Department of Medicine The University of Chicago 900 E. 57th St., KCBD, Room 7144 Chicago, IL 60637 -- www.bioinformaticstutorials.com ---------------------------------------------------------------------- -------------------------------------- Disclaimer: The information contained in this e-mail is intended for the person or entity to which it is addressed, and it may contain confidential and/or privileged material. Any review or other use of this mail or taking any action based on it by persons or entities other than the intended recipient is strictly prohibited. If you receive this e-mail by mistake, please contact the sender, and delete all copies of this mail.This e-mail has been scanned and verified by McAfee SaaS Email Security, formerly MX Logic.
ADD COMMENTlink written 4.6 years ago by Ekta Jain50
Oh I may have misunderstood your question. There's no reason the average expression values (for any particular probe) should differ between limma or when you calculate them manually (assuming you aren't doing any additional normalization). You may have to provide code for somebody to be able to figure out the problem. Paul. On Mon, May 20, 2013 at 11:51 AM, Ekta Jain <ekta.jain at="" teri.res.in=""> wrote: > Dear Paul, > Thanks very much for your reply. My data is from rice and its an affymetrix array with 57,000 probes. The genes from limma show a high 'average expressio' for contrast of mock vs treated having 3 replicates in each group. When i do an average of the expression values of each of the three replicates from the gcrma normalised files, the value is much lower as compared to the one obtained from limma. > > I am unable to understand why is this so maybe becauase i do not know how limma calculates this average. > > Thank you, > Ekta > > > -----Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: ----- > > ======================= > To: Ekta Jain <ekta.jain at="" teri.res.in=""> > From: Paul Geeleher <paulgeeleher at="" gmail.com=""> > Date: 05/20/2013 07:37PM > cc: "bioconductor at r-project.org list" <bioconductor at="" r-project.org=""> > Subject: Re: [BioC] Average expression value from limma > ======================= > > Normally I think you'd expect that differentially expressed genes tend > to have higher average intensity. Consider that your array is > measuring approx 25,000 transcripts, this means that in your tissue > type many of these will not even be expressed, thus are highly > unlikely to be identified as differentially expressed. These probes > will obviously have the lowest flourescence intensity levels, thus > skewing the overall average flourescencce intensity level towards > zero. > > On some platforms it is possible to identify and remove these probes, > for example if you're using Affymetrix Exon arrays you can apply the > DABG algorithm. > > You'd probably still want to provide some info on how big the > difference is and what the array platform is though. > > Paul. > > > > On Mon, May 20, 2013 at 6:15 AM, Ekta Jain <ekta.jain at="" teri.res.in=""> wrote: >> >> Dear Bioconductor Mailing List, >> I have a microarray data which i normalised using 'gcrma' followed by limma >> for Mock vs Treated, 3 replicates in each group. The 'topTable' returns an >> average expression value for each probeset. How is this exactly calculated? >> >> Also i compared this with the average expression of each probeset for all >> samples, such as >> (Embedded image moved to file: pic17982.gif) >> >> The 'Avg.Expr.from.limma' has a very high value as compared to the ones >> obtained from the normalised data. Is there anything wrong? >> >> Much appreciate any comments please. >> >> Regards, >> Ekta Jain >> Research Analyst >> Biotechnology and Bio-resources Division >> The Energy and Resources Institute, India Habitat Centre >> Lodhi Road, New Delhi - 110033 >> #09958818853 >> ekta.jain at teri.res.in >> >> >> ------------------------------------------------------------------- ----------------------------------------- >> >> Disclaimer: >> >> The information contained in this e-mail is intended for the person or entity >> to which it is addressed, and it may contain confidential and/or privileged >> material. Any review or other use of this mail or taking any action based on it >> by persons or entities other than the intended recipient is strictly prohibited. >> If you receive this e-mail by mistake, please contact the sender, and delete all >> copies of this mail.This e-mail has been scanned and verified by McAfee SaaS >> Email Security, formerly MX Logic. >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > -- > Dr. Paul Geeleher, PhD (Bioinformatics) > Section of Hematology-Oncology > Department of Medicine > The University of Chicago > 900 E. 57th St., > KCBD, Room 7144 > Chicago, IL 60637 > -- > www.bioinformaticstutorials.com > > > > > -------------------------------------------------------------------- ---------------------------------------- > > Disclaimer: > > The information contained in this e-mail is intended for the person or entity > to which it is addressed, and it may contain confidential and/or privileged > material. Any review or other use of this mail or taking any action based on it > by persons or entities other than the intended recipient is strictly prohibited. > If you receive this e-mail by mistake, please contact the sender, and delete all > copies of this mail.This e-mail has been scanned and verified by McAfee SaaS > Email Security, formerly MX Logic. -- Dr. Paul Geeleher, PhD (Bioinformatics) Section of Hematology-Oncology Department of Medicine The University of Chicago 900 E. 57th St., KCBD, Room 7144 Chicago, IL 60637 -- www.bioinformaticstutorials.com
ADD REPLYlink written 4.6 years ago by Paul Geeleher1.3k
0
gravatar for Gordon Smyth
4.6 years ago by
Gordon Smyth32k
Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Gordon Smyth32k wrote:
Dear Ekta, The AveExpr in the topTable from limma is the ordinary arithmetic average of the log2-expression values for the probe, across all arrays in the experiment. This is exactly as described in the documentation. There is no quantity called "Ave.Expr.from.limma" in any limma output. Best wishes Gordon > Date: Mon, 20 May 2013 16:45:03 +0530 > From: Ekta Jain <ekta.jain at="" teri.res.in=""> > To: bioconductor at r-project.org > Subject: [BioC] Average expression value from limma > > Dear Bioconductor Mailing List, > I have a microarray data which i normalised using 'gcrma' followed by limma > for Mock vs Treated, 3 replicates in each group. The 'topTable' returns an > average expression value for each probeset. How is this exactly calculated? > > Also i compared this with the average expression of each probeset for all > samples, such as > (Embedded image moved to file: pic17982.gif) > > The 'Avg.Expr.from.limma' has a very high value as compared to the ones > obtained from the normalised data. Is there anything wrong? > > Much appreciate any comments please. > > Regards, > Ekta Jain > Research Analyst > Biotechnology and Bio-resources Division > The Energy and Resources Institute, India Habitat Centre > Lodhi Road, New Delhi - 110033 > #09958818853 > ekta.jain at teri.res.in > ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
ADD COMMENTlink written 4.6 years ago by Gordon Smyth32k
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