Analysing multiple-platform gene expression data
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gabriel teku ▴ 80
@gabriel-teku-4427
Last seen 9.2 years ago
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HI All, I'm trying to analyse microarray experiment data in which two types of Affymetrix platforms were used. However, I don't know how to handle these. I'll be great if I could get a heads up right from the beginning in terms of statistics, etc. Thanx Gabriel [[alternative HTML version deleted]]
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Paul Geeleher ★ 1.3k
@paul-geeleher-2679
Last seen 10.2 years ago
Hey might be worth doing a search on pubmed or google to see if there are published studies that have a similar setup and just do what they've done. Possibilities might be to use brainarray custom CDFs to reduce both platforms to entrez gene ids, subset on ids common to both platforms then use something like rankproduct (which uses gene ranks rather than expression level) to compare between between the two types of arrays. Paul. On Mon, Jan 10, 2011 at 1:53 PM, gabriel teku <gabbyteku at="" gmail.com=""> wrote: > HI All, > I'm trying to analyse microarray experiment data in which two types of > Affymetrix platforms were used. However, I don't know how to handle these. > I'll be great if I could get a heads up right from the beginning in terms of > statistics, etc. > > Thanx > Gabriel > > ? ? ? ?[[alternative HTML version deleted]] > > _______________________________________________ > 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 > -- Paul Geeleher School of Mathematics, Statistics and Applied Mathematics National University of Ireland Galway Ireland -- www.bioinformaticstutorials.com
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@jordi-altirriba-gutierrez-682
Last seen 5.7 years ago
Dear Gabriel, We would need more information. What do you mean by different types of Affymetrix platforms? Platforms situated in different places, different machines, different Affymetix chips, etc, etc. Regards, Jordi Altirriba Message: 3 Date: Mon, 10 Jan 2011 15:53:43 +0200 From: gabriel teku <gabbyteku@gmail.com> To: bioconductor at r-project.org Subject: [BioC] Analysing multiple-platform gene expression data Message-ID: <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_ at="" mail.gmail.com=""> Content-Type: text/plain HI All, I'm trying to analyse microarray experiment data in which two types of Affymetrix platforms were used. However, I don't know how to handle these. I'll be great if I could get a heads up right from the beginning in terms of statistics, etc. Thanx Gabriel [[alternative HTML version deleted]]
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Hi Jordi, When I said multiple Affy platforms I meant different Affy chips, e.g. hgu133a, hgu133plus2. Is it OK and possible to remove probes not present in both platforms? What are the bilogical/statistical implications of doing this. Thanks in advance On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba <altirriba@hotmail.com>wrote: > > Dear Gabriel, > We would need more information. What do you mean by different types of > Affymetrix platforms? Platforms situated in different places, different > machines, different Affymetix chips, etc, etc. > Regards, > > Jordi Altirriba > > > Message: 3 > Date: Mon, 10 Jan 2011 15:53:43 +0200 > From: gabriel teku <gabbyteku@gmail.com> > To: bioconductor@r-project.org > Subject: [BioC] Analysing multiple-platform gene expression data > Message-ID: > <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_@mail.gmail.com> > Content-Type: text/plain > > HI All, > I'm trying to analyse microarray experiment data in which two types of > Affymetrix platforms were used. However, I don't know how to handle these. > I'll be great if I could get a heads up right from the beginning in terms > of > statistics, etc. > > Thanx > Gabriel > > [[alternative HTML version deleted]] [[alternative HTML version deleted]]
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Hi Gabriel, I would urge caution. Because even though "on paper" the different platforms might claim to be using many of the same probe sets, it is possible to actually measure differences that seem to be caused by nothing other than the fact that a given probeset was measured on one chip type vs another. Marc On 01/26/2011 01:25 AM, gabriel teku wrote: > Hi Jordi, > When I said multiple Affy platforms I meant different Affy chips, e.g. > hgu133a, hgu133plus2. > Is it OK and possible to remove probes not present in both platforms? > What are the bilogical/statistical implications of doing this. > > Thanks in advance > > On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba <altirriba at="" hotmail.com="">wrote: > > >> Dear Gabriel, >> We would need more information. What do you mean by different types of >> Affymetrix platforms? Platforms situated in different places, different >> machines, different Affymetix chips, etc, etc. >> Regards, >> >> Jordi Altirriba >> >> >> Message: 3 >> Date: Mon, 10 Jan 2011 15:53:43 +0200 >> From: gabriel teku <gabbyteku at="" gmail.com=""> >> To: bioconductor at r-project.org >> Subject: [BioC] Analysing multiple-platform gene expression data >> Message-ID: >> <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_ at="" mail.gmail.com=""> >> Content-Type: text/plain >> >> HI All, >> I'm trying to analyse microarray experiment data in which two types of >> Affymetrix platforms were used. However, I don't know how to handle these. >> I'll be great if I could get a heads up right from the beginning in terms >> of >> statistics, etc. >> >> Thanx >> Gabriel >> >> [[alternative HTML version deleted]] >> > [[alternative HTML version deleted]] > > _______________________________________________ > 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 >
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Hi Gabriel, You can have a look here: http://bmbolstad.com/misc/mixtureCDF/MixtureCDF.html In the CC I have also included Ben Bolstad (the author), who is very nice and probably can help you more in detail. Good luck! Jordi Altirriba Date: Wed, 26 Jan 2011 11:25:40 +0200 Subject: Re: Analysing multiple-platform gene expression data From: gabbyteku@gmail.com To: altirriba@hotmail.com CC: bioconductor@stat.math.ethz.ch Hi Jordi, When I said multiple Affy platforms I meant different Affy chips, e.g. hgu133a, hgu133plus2. Is it OK and possible to remove probes not present in both platforms? What are the bilogical/statistical implications of doing this. Thanks in advance On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba <altirriba@hotmail.com> wrote: Dear Gabriel, We would need more information. What do you mean by different types of Affymetrix platforms? Platforms situated in different places, different machines, different Affymetix chips, etc, etc. Regards, Jordi Altirriba Message: 3 Date: Mon, 10 Jan 2011 15:53:43 +0200 From: gabriel teku <gabbyteku@gmail.com> To: bioconductor@r-project.org Subject: [BioC] Analysing multiple-platform gene expression data Message-ID: <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_@mail.gmail.com> Content-Type: text/plain HI All, I'm trying to analyse microarray experiment data in which two types of Affymetrix platforms were used. However, I don't know how to handle these. I'll be great if I could get a heads up right from the beginning in terms of statistics, etc. Thanx Gabriel [[alternative HTML version deleted]] [[alternative HTML version deleted]]
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@matthew-mccall-4459
Last seen 5.5 years ago
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Max, You can certainly use the z-scores from the barcode function to combine hgu133a and hgu133plus2 data. Since the z-scores are based on platform-specific null distributions, they have the same meaning (number of sd's above the unexpressed mean) on all platforms. To gain robustness to batch effects, you might consider going further and using the actual barcode values (zeros and ones), but obviously this depends on what downstream analysis you want to do. Best, Matt On Thu, Jan 27, 2011 at 8:04 AM, Harris A. Jaffee <hj at="" jhu.edu=""> wrote: > > > Begin forwarded message: > >> From: Kauer Max <maximilian.kauer at="" ccri.at=""> >> Date: January 27, 2011 4:29:50 AM EST >> To: Marc Carlson <mcarlson at="" fhcrc.org="">, bioconductor at r-project.org >> Subject: Re: [BioC] Analysing multiple-platform gene expression data >> >> >> Hi, >> along the same lines I wondered if one can take the z-scores from the >> barcode() function in the frma package. From my understanding these scores >> give a "distance" from the empirically defined value of no expression >> (separately for hgu133a and hgu133plus2), so in theory these could be >> comparable between platforms (?) >> Does anybody have an opinion on that? >> >> Best, >> Max >> >> >> >> -----Urspr?ngliche Nachricht----- >> Von: bioconductor-bounces at r-project.org im Auftrag von Marc Carlson >> Gesendet: Mi 26.01.2011 18:45 >> An: bioconductor at r-project.org >> Betreff: Re: [BioC] Analysing multiple-platform gene expression data >> >> Hi Gabriel, >> >> I would urge caution. ?Because even though "on paper" the different >> platforms might claim to be using many of the same probe sets, it is >> possible to actually measure differences that seem to be caused by >> nothing other than the fact that a given probeset was measured on one >> chip type vs another. >> >> >> ?Marc >> >> >> On 01/26/2011 01:25 AM, gabriel teku wrote: >>> >>> Hi Jordi, >>> When I said multiple Affy platforms I meant different Affy chips, e.g. >>> hgu133a, hgu133plus2. >>> Is it OK and possible to remove probes not present in both platforms? >>> What are the bilogical/statistical implications of doing this. >>> >>> Thanks in advance >>> >>> On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba >>> <altirriba at="" hotmail.com="">wrote: >>> >>> >>>> Dear Gabriel, >>>> We would need more information. What do you mean by different types of >>>> Affymetrix platforms? Platforms situated in different places, different >>>> machines, different Affymetix chips, etc, etc. >>>> Regards, >>>> >>>> Jordi Altirriba >>>> >>>> >>>> Message: 3 >>>> Date: Mon, 10 Jan 2011 15:53:43 +0200 >>>> From: gabriel teku <gabbyteku at="" gmail.com=""> >>>> To: bioconductor at r-project.org >>>> Subject: [BioC] Analysing multiple-platform gene expression data >>>> Message-ID: >>>> <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_ at="" mail.gmail.com=""> >>>> Content-Type: text/plain >>>> >>>> HI All, >>>> I'm trying to analyse microarray experiment data in which two types of >>>> Affymetrix platforms were used. However, I don't know how to handle >>>> these. >>>> I'll be great if I could get a heads up right from the beginning in >>>> terms >>>> of >>>> statistics, etc. >>>> >>>> Thanx >>>> Gabriel >>>> >>>> [[alternative HTML version deleted]] >>>> >>> ? ? ? ?[[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> 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 >>> >> >> _______________________________________________ >> 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 >> >> _______________________________________________ >> 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 > > -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880
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Max Kauer ▴ 140
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Last seen 8.2 years ago
Hi, along the same lines I wondered if one can take the z-scores from the barcode() function in the frma package. From my understanding these scores give a "distance" from the empirically defined value of no expression (separately for hgu133a and hgu133plus2), so in theory these could be comparable between platforms (?) Does anybody have an opinion on that? Best, Max -----Urspr?ngliche Nachricht----- Von: bioconductor-bounces at r-project.org im Auftrag von Marc Carlson Gesendet: Mi 26.01.2011 18:45 An: bioconductor at r-project.org Betreff: Re: [BioC] Analysing multiple-platform gene expression data Hi Gabriel, I would urge caution. Because even though "on paper" the different platforms might claim to be using many of the same probe sets, it is possible to actually measure differences that seem to be caused by nothing other than the fact that a given probeset was measured on one chip type vs another. Marc On 01/26/2011 01:25 AM, gabriel teku wrote: > Hi Jordi, > When I said multiple Affy platforms I meant different Affy chips, e.g. > hgu133a, hgu133plus2. > Is it OK and possible to remove probes not present in both platforms? > What are the bilogical/statistical implications of doing this. > > Thanks in advance > > On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba <altirriba at="" hotmail.com="">wrote: > > >> Dear Gabriel, >> We would need more information. What do you mean by different types of >> Affymetrix platforms? Platforms situated in different places, different >> machines, different Affymetix chips, etc, etc. >> Regards, >> >> Jordi Altirriba >> >> >> Message: 3 >> Date: Mon, 10 Jan 2011 15:53:43 +0200 >> From: gabriel teku <gabbyteku at="" gmail.com=""> >> To: bioconductor at r-project.org >> Subject: [BioC] Analysing multiple-platform gene expression data >> Message-ID: >> <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_ at="" mail.gmail.com=""> >> Content-Type: text/plain >> >> HI All, >> I'm trying to analyse microarray experiment data in which two types of >> Affymetrix platforms were used. However, I don't know how to handle these. >> I'll be great if I could get a heads up right from the beginning in terms >> of >> statistics, etc. >> >> Thanx >> Gabriel >> >> [[alternative HTML version deleted]] >> > [[alternative HTML version deleted]] > > _______________________________________________ > 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 > _______________________________________________ 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
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Max Kauer ▴ 140
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Last seen 8.2 years ago
Thanks Matt! Great! Actually I have two more questions for frma: 1) could one use frma also for hgu133a2 arrays (with the null- distribution vectors for hgu133a arrays)? I guess not, but I thought I'd ask anyway 2) could I somewhere access the expression-distribution (not only the null-distribution) for all genes, i.e. the data matrices that you used to construct these distributions? Thanks! max -----Urspr?ngliche Nachricht----- Von: Matthew McCall [mailto:mccallm at gmail.com] Gesendet: Do 27.01.2011 14:39 An: bioconductor at r-project.org; Kauer Max Betreff: Re: [BioC] Analysing multiple-platform gene expression data Max, You can certainly use the z-scores from the barcode function to combine hgu133a and hgu133plus2 data. Since the z-scores are based on platform-specific null distributions, they have the same meaning (number of sd's above the unexpressed mean) on all platforms. To gain robustness to batch effects, you might consider going further and using the actual barcode values (zeros and ones), but obviously this depends on what downstream analysis you want to do. Best, Matt On Thu, Jan 27, 2011 at 8:04 AM, Harris A. Jaffee <hj at="" jhu.edu=""> wrote: > > > Begin forwarded message: > >> From: Kauer Max <maximilian.kauer at="" ccri.at=""> >> Date: January 27, 2011 4:29:50 AM EST >> To: Marc Carlson <mcarlson at="" fhcrc.org="">, bioconductor at r-project.org >> Subject: Re: [BioC] Analysing multiple-platform gene expression data >> >> >> Hi, >> along the same lines I wondered if one can take the z-scores from the >> barcode() function in the frma package. From my understanding these scores >> give a "distance" from the empirically defined value of no expression >> (separately for hgu133a and hgu133plus2), so in theory these could be >> comparable between platforms (?) >> Does anybody have an opinion on that? >> >> Best, >> Max >> >> >> >> -----Urspr?ngliche Nachricht----- >> Von: bioconductor-bounces at r-project.org im Auftrag von Marc Carlson >> Gesendet: Mi 26.01.2011 18:45 >> An: bioconductor at r-project.org >> Betreff: Re: [BioC] Analysing multiple-platform gene expression data >> >> Hi Gabriel, >> >> I would urge caution. ?Because even though "on paper" the different >> platforms might claim to be using many of the same probe sets, it is >> possible to actually measure differences that seem to be caused by >> nothing other than the fact that a given probeset was measured on one >> chip type vs another. >> >> >> ?Marc >> >> >> On 01/26/2011 01:25 AM, gabriel teku wrote: >>> >>> Hi Jordi, >>> When I said multiple Affy platforms I meant different Affy chips, e.g. >>> hgu133a, hgu133plus2. >>> Is it OK and possible to remove probes not present in both platforms? >>> What are the bilogical/statistical implications of doing this. >>> >>> Thanks in advance >>> >>> On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba >>> <altirriba at="" hotmail.com="">wrote: >>> >>> >>>> Dear Gabriel, >>>> We would need more information. What do you mean by different types of >>>> Affymetrix platforms? Platforms situated in different places, different >>>> machines, different Affymetix chips, etc, etc. >>>> Regards, >>>> >>>> Jordi Altirriba >>>> >>>> >>>> Message: 3 >>>> Date: Mon, 10 Jan 2011 15:53:43 +0200 >>>> From: gabriel teku <gabbyteku at="" gmail.com=""> >>>> To: bioconductor at r-project.org >>>> Subject: [BioC] Analysing multiple-platform gene expression data >>>> Message-ID: >>>> <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_ at="" mail.gmail.com=""> >>>> Content-Type: text/plain >>>> >>>> HI All, >>>> I'm trying to analyse microarray experiment data in which two types of >>>> Affymetrix platforms were used. However, I don't know how to handle >>>> these. >>>> I'll be great if I could get a heads up right from the beginning in >>>> terms >>>> of >>>> statistics, etc. >>>> >>>> Thanx >>>> Gabriel >>>> >>>> [[alternative HTML version deleted]] >>>> >>> ? ? ? ?[[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> 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 >>> >> >> _______________________________________________ >> 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 >> >> _______________________________________________ >> 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 > > -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880
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Max, 1) I've explored this with mixed results. There are certainly differences in the behavior of the same probe across different platforms. But if you want to try it out for yourself, take a look at the hgu133a2ASaFrma function in the frmaTools package. Just be cautious in your interpretation of the results. 2) Everything that we've made publicly available from the barcode work is on this website: http://rafalab.jhsph.edu/barcode/. We don't have the entire data matrices available to download (these are huge files), but we do have the annotation files listing all the publicly available data we used. If you want the data matrices, simply download all of the CEL files listed in the annotation, preprocess them with frma, and you'll have it. Best, Matt On Mon, Jan 31, 2011 at 7:31 AM, Kauer Max <maximilian.kauer at="" ccri.at=""> wrote: > Thanks Matt! > Great! Actually I have two more questions for frma: > 1) could one use frma also for hgu133a2 arrays (with the null- distribution vectors for hgu133a arrays)? I guess not, but I thought I'd ask anyway > 2) could I somewhere access the expression-distribution (not only the null-distribution) for all genes, i.e. the data matrices that you used to construct these distributions? > > Thanks! > max > > > > > > > -----Urspr?ngliche Nachricht----- > Von: Matthew McCall [mailto:mccallm at gmail.com] > Gesendet: Do 27.01.2011 14:39 > An: bioconductor at r-project.org; Kauer Max > Betreff: Re: [BioC] Analysing multiple-platform gene expression data > > Max, > > You can certainly use the z-scores from the barcode function to > combine hgu133a and hgu133plus2 data. Since the z-scores are based on > platform-specific null distributions, they have the same meaning > (number of sd's above the unexpressed mean) on all platforms. To gain > robustness to batch effects, you might consider going further and > using the actual barcode values (zeros and ones), but obviously this > depends on what downstream analysis you want to do. > > Best, > Matt > > On Thu, Jan 27, 2011 at 8:04 AM, Harris A. Jaffee <hj at="" jhu.edu=""> wrote: >> >> >> Begin forwarded message: >> >>> From: Kauer Max <maximilian.kauer at="" ccri.at=""> >>> Date: January 27, 2011 4:29:50 AM EST >>> To: Marc Carlson <mcarlson at="" fhcrc.org="">, bioconductor at r-project.org >>> Subject: Re: [BioC] Analysing multiple-platform gene expression data >>> >>> >>> Hi, >>> along the same lines I wondered if one can take the z-scores from the >>> barcode() function in the frma package. From my understanding these scores >>> give a "distance" from the empirically defined value of no expression >>> (separately for hgu133a and hgu133plus2), so in theory these could be >>> comparable between platforms (?) >>> Does anybody have an opinion on that? >>> >>> Best, >>> Max >>> >>> >>> >>> -----Urspr?ngliche Nachricht----- >>> Von: bioconductor-bounces at r-project.org im Auftrag von Marc Carlson >>> Gesendet: Mi 26.01.2011 18:45 >>> An: bioconductor at r-project.org >>> Betreff: Re: [BioC] Analysing multiple-platform gene expression data >>> >>> Hi Gabriel, >>> >>> I would urge caution. ?Because even though "on paper" the different >>> platforms might claim to be using many of the same probe sets, it is >>> possible to actually measure differences that seem to be caused by >>> nothing other than the fact that a given probeset was measured on one >>> chip type vs another. >>> >>> >>> ?Marc >>> >>> >>> On 01/26/2011 01:25 AM, gabriel teku wrote: >>>> >>>> Hi Jordi, >>>> When I said multiple Affy platforms I meant different Affy chips, e.g. >>>> hgu133a, hgu133plus2. >>>> Is it OK and possible to remove probes not present in both platforms? >>>> What are the bilogical/statistical implications of doing this. >>>> >>>> Thanks in advance >>>> >>>> On Mon, Jan 17, 2011 at 2:45 PM, Jordi Altirriba >>>> <altirriba at="" hotmail.com="">wrote: >>>> >>>> >>>>> Dear Gabriel, >>>>> We would need more information. What do you mean by different types of >>>>> Affymetrix platforms? Platforms situated in different places, different >>>>> machines, different Affymetix chips, etc, etc. >>>>> Regards, >>>>> >>>>> Jordi Altirriba >>>>> >>>>> >>>>> Message: 3 >>>>> Date: Mon, 10 Jan 2011 15:53:43 +0200 >>>>> From: gabriel teku <gabbyteku at="" gmail.com=""> >>>>> To: bioconductor at r-project.org >>>>> Subject: [BioC] Analysing multiple-platform gene expression data >>>>> Message-ID: >>>>> <aanlktinzi+n2a=d4nj_h3c4d4p7ruw3hf2bnksb=vjo_ at="" mail.gmail.com=""> >>>>> Content-Type: text/plain >>>>> >>>>> HI All, >>>>> I'm trying to analyse microarray experiment data in which two types of >>>>> Affymetrix platforms were used. However, I don't know how to handle >>>>> these. >>>>> I'll be great if I could get a heads up right from the beginning in >>>>> terms >>>>> of >>>>> statistics, etc. >>>>> >>>>> Thanx >>>>> Gabriel >>>>> >>>>> [[alternative HTML version deleted]] >>>>> >>>> ? ? ? ?[[alternative HTML version deleted]] >>>> >>>> _______________________________________________ >>>> 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 >>>> >>> >>> _______________________________________________ >>> 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 >>> >>> _______________________________________________ >>> 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 >> >> > > > > -- > Matthew N McCall, PhD > 112 Arvine Heights > Rochester, NY 14611 > Cell: 202-222-5880 > > > > -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880
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