Analyze miRNA experiment in Bioconductor
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Paul Geeleher ★ 1.3k
@paul-geeleher-2679
Last seen 10.3 years ago
Dear Members, I've inherited a bunch of GenePix files from an miRNA experiment. They are single color arrays, ( as opposed to 2 color as is the norm for GenePix I think). There is a subset of 7 arrays and I wish to compare a group of 4 of these to the other group of 3 and analyze differential expression between the two groups. I was hoping somebody could point me in the right direction of how I'd go about doing this with Bioconductor? Is it possible using the Limma package? Is there any code out there to assist me? I've experience in analyzing Affymetrix data using Limma and PUMA, but not GenePix, and the Limma Users Guide seems to focus on analyzing two dye experiments. I've uploaded one of the ".gpr" files to the net if anyone wants to have a look: http://frink.nuigalway.ie/~pat/2007-02-19_130_0532.gpr -Paul
miRNA GO limma puma miRNA GO limma puma • 1.8k views
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@deepayan-sarkar-1436
Last seen 14 months ago
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On 5/6/08, Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: > Dear Members, > > I've inherited a bunch of GenePix files from an miRNA experiment. They > are single color arrays, ( as opposed to 2 color as is the norm for > GenePix I think). There is a subset of 7 arrays and I wish to compare > a group of 4 of these to the other group of 3 and analyze differential > expression between the two groups. I was hoping somebody could point > me in the right direction of how I'd go about doing this with > Bioconductor? Is it possible using the Limma package? Is there any > code out there to assist me? > > I've experience in analyzing Affymetrix data using Limma and PUMA, but > not GenePix, and the Limma Users Guide seems to focus on analyzing two > dye experiments. Any analysis ultimately boils down to some sort of normalization, and the actual differential expression analysis. The second part in limma (lmFit, etc.) can work with any expression matrix, irrespective of whether it's 2-color or 1-color (or affy). We have been working with a miRNA array dataset recently, and we used limma to read in the GPR files and do the differential expression analysis (on one channel). For normalization, many of the standard microarray algorithms probably don't make much sense, but VSN seems to work fine. We don't really have code (beyond what's already in limma and vsn) that is generally useful; most of the work is in figuring out which rows are of interest (i.e., those representing human miRNAs), combining the replicates (you seem to have four of each), etc. I'm happy to give you more details if you are interested. -Deepayan
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Hi Deepayan, Thanks for your reply. I suppose my main concern is how I should read in the data initially in order to be able to use the normal tools to analyze the data. Reading the data normally like this: RG <- read.maimages( files, source="genepix") Gives the following error: Error in RG[[a]][, i] <- obj[, columns[[a]]] : number of items to replace is not a multiple of replacement length I'm assuming this is down to the fact that the files only contain intensity data for one color rather than two? How should I go about reading the data? Thanks alot, -Paul. On Tue, May 6, 2008 at 10:15 PM, Deepayan Sarkar <deepayan.sarkar at="" gmail.com=""> wrote: > On 5/6/08, Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: > > Dear Members, > > > > I've inherited a bunch of GenePix files from an miRNA experiment. They > > are single color arrays, ( as opposed to 2 color as is the norm for > > GenePix I think). There is a subset of 7 arrays and I wish to compare > > a group of 4 of these to the other group of 3 and analyze differential > > expression between the two groups. I was hoping somebody could point > > me in the right direction of how I'd go about doing this with > > Bioconductor? Is it possible using the Limma package? Is there any > > code out there to assist me? > > > > I've experience in analyzing Affymetrix data using Limma and PUMA, but > > not GenePix, and the Limma Users Guide seems to focus on analyzing two > > dye experiments. > > Any analysis ultimately boils down to some sort of normalization, and > the actual differential expression analysis. The second part in limma > (lmFit, etc.) can work with any expression matrix, irrespective of > whether it's 2-color or 1-color (or affy). > > We have been working with a miRNA array dataset recently, and we used > limma to read in the GPR files and do the differential expression > analysis (on one channel). For normalization, many of the standard > microarray algorithms probably don't make much sense, but VSN seems to > work fine. > > We don't really have code (beyond what's already in limma and vsn) > that is generally useful; most of the work is in figuring out which > rows are of interest (i.e., those representing human miRNAs), > combining the replicates (you seem to have four of each), etc. I'm > happy to give you more details if you are interested. > > -Deepayan >
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You can specify your red channel like this: RG <- read.maimages(files,source="genepix", columns=list(R="F635 Median",G="F532 Median",Rb="B635",Gb="B532")) I will suggest you read limma guide. But I think your have data from Imagene package which gives one file for each channel, you can: files <- targets[,c("FileNameCy3","FileNameCy5")] RG <- read.maimages(files, source="imagene") Hope, this helps Narendra >>> "Paul Geeleher" <paulgeeleher at="" gmail.com=""> 07/05/2008 13:24:01 >>> Hi Deepayan, Thanks for your reply. I suppose my main concern is how I should read in the data initially in order to be able to use the normal tools to analyze the data. Reading the data normally like this: RG <- read.maimages( files, source="genepix") Gives the following error: Error in RG[[a]][, i] <- obj[, columns[[a]]] : number of items to replace is not a multiple of replacement length I'm assuming this is down to the fact that the files only contain intensity data for one color rather than two? How should I go about reading the data? Thanks alot, -Paul. On Tue, May 6, 2008 at 10:15 PM, Deepayan Sarkar <deepayan.sarkar at="" gmail.com=""> wrote: > On 5/6/08, Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: > > Dear Members, > > > > I've inherited a bunch of GenePix files from an miRNA experiment. They > > are single color arrays, ( as opposed to 2 color as is the norm for > > GenePix I think). There is a subset of 7 arrays and I wish to compare > > a group of 4 of these to the other group of 3 and analyze differential > > expression between the two groups. I was hoping somebody could point > > me in the right direction of how I'd go about doing this with > > Bioconductor? Is it possible using the Limma package? Is there any > > code out there to assist me? > > > > I've experience in analyzing Affymetrix data using Limma and PUMA, but > > not GenePix, and the Limma Users Guide seems to focus on analyzing two > > dye experiments. > > Any analysis ultimately boils down to some sort of normalization, and > the actual differential expression analysis. The second part in limma > (lmFit, etc.) can work with any expression matrix, irrespective of > whether it's 2-color or 1-color (or affy). > > We have been working with a miRNA array dataset recently, and we used > limma to read in the GPR files and do the differential expression > analysis (on one channel). For normalization, many of the standard > microarray algorithms probably don't make much sense, but VSN seems to > work fine. > > We don't really have code (beyond what's already in limma and vsn) > that is generally useful; most of the work is in figuring out which > rows are of interest (i.e., those representing human miRNAs), > combining the replicates (you seem to have four of each), etc. I'm > happy to give you more details if you are interested. > > -Deepayan > _______________________________________________ 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
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Hmm interesting. I might try introducing the extra columns into the files and specifying all the values as 0. I can't see why that shouldn't work? -Paul On Wed, May 7, 2008 at 1:39 PM, Narendra Kaushik <kaushiknk at="" cardiff.ac.uk=""> wrote: > You can specify your red channel like this: > > RG <- read.maimages(files,source="genepix", columns=list(R="F635 Median",G="F532 > Median",Rb="B635",Gb="B532")) > > I will suggest you read limma guide. > > But I think your have data from Imagene package which gives one file for each channel, you can: > > files <- targets[,c("FileNameCy3","FileNameCy5")] > RG <- read.maimages(files, source="imagene") > > Hope, this helps > > Narendra > > >>> "Paul Geeleher" <paulgeeleher at="" gmail.com=""> 07/05/2008 13:24:01 >>> > > > Hi Deepayan, > > Thanks for your reply. I suppose my main concern is how I should read > in the data initially in order to be able to use the normal tools to > analyze the data. Reading the data normally like this: > > RG <- read.maimages( files, source="genepix") > > Gives the following error: > > Error in RG[[a]][, i] <- obj[, columns[[a]]] : > number of items to replace is not a multiple of replacement length > > > I'm assuming this is down to the fact that the files only contain > intensity data for one color rather than two? > > How should I go about reading the data? > > Thanks alot, > > -Paul. > > On Tue, May 6, 2008 at 10:15 PM, Deepayan Sarkar > <deepayan.sarkar at="" gmail.com=""> wrote: > > On 5/6/08, Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: > > > Dear Members, > > > > > > I've inherited a bunch of GenePix files from an miRNA experiment. They > > > are single color arrays, ( as opposed to 2 color as is the norm for > > > GenePix I think). There is a subset of 7 arrays and I wish to compare > > > a group of 4 of these to the other group of 3 and analyze differential > > > expression between the two groups. I was hoping somebody could point > > > me in the right direction of how I'd go about doing this with > > > Bioconductor? Is it possible using the Limma package? Is there any > > > code out there to assist me? > > > > > > I've experience in analyzing Affymetrix data using Limma and PUMA, but > > > not GenePix, and the Limma Users Guide seems to focus on analyzing two > > > dye experiments. > > > > Any analysis ultimately boils down to some sort of normalization, and > > the actual differential expression analysis. The second part in limma > > (lmFit, etc.) can work with any expression matrix, irrespective of > > whether it's 2-color or 1-color (or affy). > > > > We have been working with a miRNA array dataset recently, and we used > > limma to read in the GPR files and do the differential expression > > analysis (on one channel). For normalization, many of the standard > > microarray algorithms probably don't make much sense, but VSN seems to > > work fine. > > > > We don't really have code (beyond what's already in limma and vsn) > > that is generally useful; most of the work is in figuring out which > > rows are of interest (i.e., those representing human miRNAs), > > combining the replicates (you seem to have four of each), etc. I'm > > happy to give you more details if you are interested. > > > > -Deepayan > > > > _______________________________________________ > 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 >
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Dear Paul, > Hmm interesting. I might try introducing the extra columns into the > files and specifying all the values as 0. I can't see why that > shouldn't work? It might, but Narendra's suggestion of reading the limma users guide is a worthwhile option to consider. Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber > > -Paul > > On Wed, May 7, 2008 at 1:39 PM, Narendra Kaushik > <kaushiknk at="" cardiff.ac.uk=""> wrote: >> You can specify your red channel like this: >> >> RG <- read.maimages(files,source="genepix", columns=list(R="F635 Median",G="F532 >> Median",Rb="B635",Gb="B532")) >> >> I will suggest you read limma guide. >> >> But I think your have data from Imagene package which gives one file for each channel, you can: >> >> files <- targets[,c("FileNameCy3","FileNameCy5")] >> RG <- read.maimages(files, source="imagene") >> >> Hope, this helps >> >> Narendra >> >> >>> "Paul Geeleher" <paulgeeleher at="" gmail.com=""> 07/05/2008 13:24:01 >>> >> >> >> Hi Deepayan, >> >> Thanks for your reply. I suppose my main concern is how I should read >> in the data initially in order to be able to use the normal tools to >> analyze the data. Reading the data normally like this: >> >> RG <- read.maimages( files, source="genepix") >> >> Gives the following error: >> >> Error in RG[[a]][, i] <- obj[, columns[[a]]] : >> number of items to replace is not a multiple of replacement length >> >> >> I'm assuming this is down to the fact that the files only contain >> intensity data for one color rather than two? >> >> How should I go about reading the data? >> >> Thanks alot, >> >> -Paul. >> >> On Tue, May 6, 2008 at 10:15 PM, Deepayan Sarkar >> <deepayan.sarkar at="" gmail.com=""> wrote: >> > On 5/6/08, Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: >> > > Dear Members, >> > > >> > > I've inherited a bunch of GenePix files from an miRNA experiment. They >> > > are single color arrays, ( as opposed to 2 color as is the norm for >> > > GenePix I think). There is a subset of 7 arrays and I wish to compare >> > > a group of 4 of these to the other group of 3 and analyze differential >> > > expression between the two groups. I was hoping somebody could point >> > > me in the right direction of how I'd go about doing this with >> > > Bioconductor? Is it possible using the Limma package? Is there any >> > > code out there to assist me? >> > > >> > > I've experience in analyzing Affymetrix data using Limma and PUMA, but >> > > not GenePix, and the Limma Users Guide seems to focus on analyzing two >> > > dye experiments. >> > >> > Any analysis ultimately boils down to some sort of normalization, and >> > the actual differential expression analysis. The second part in limma >> > (lmFit, etc.) can work with any expression matrix, irrespective of >> > whether it's 2-color or 1-color (or affy). >> > >> > We have been working with a miRNA array dataset recently, and we used >> > limma to read in the GPR files and do the differential expression >> > analysis (on one channel). For normalization, many of the standard >> > microarray algorithms probably don't make much sense, but VSN seems to >> > work fine. >> > >> > We don't really have code (beyond what's already in limma and vsn) >> > that is generally useful; most of the work is in figuring out which >> > rows are of interest (i.e., those representing human miRNAs), >> > combining the replicates (you seem to have four of each), etc. I'm >> > happy to give you more details if you are interested. >> > >> > -Deepayan >> >
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Doesn't seem to be anything in the users guide specific to this kind of analysis unfortunately. -Paul On Thu, May 8, 2008 at 10:31 AM, Wolfgang Huber <huber at="" ebi.ac.uk=""> wrote: > Dear Paul, > >> Hmm interesting. I might try introducing the extra columns into the >> files and specifying all the values as 0. I can't see why that >> shouldn't work? > > It might, but Narendra's suggestion of reading the limma users guide is a > worthwhile option to consider. > > Best wishes > Wolfgang > > ------------------------------------------------------------------ > Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber > >> >> -Paul >> >> On Wed, May 7, 2008 at 1:39 PM, Narendra Kaushik >> <kaushiknk at="" cardiff.ac.uk=""> wrote: >>> >>> You can specify your red channel like this: >>> >>> RG <- read.maimages(files,source="genepix", columns=list(R="F635 >>> Median",G="F532 >>> Median",Rb="B635",Gb="B532")) >>> >>> I will suggest you read limma guide. >>> >>> But I think your have data from Imagene package which gives one file for >>> each channel, you can: >>> >>> files <- targets[,c("FileNameCy3","FileNameCy5")] >>> RG <- read.maimages(files, source="imagene") >>> >>> Hope, this helps >>> >>> Narendra >>> >>> >>> "Paul Geeleher" <paulgeeleher at="" gmail.com=""> 07/05/2008 13:24:01 >>> >>> >>> >>> Hi Deepayan, >>> >>> Thanks for your reply. I suppose my main concern is how I should read >>> in the data initially in order to be able to use the normal tools to >>> analyze the data. Reading the data normally like this: >>> >>> RG <- read.maimages( files, source="genepix") >>> >>> Gives the following error: >>> >>> Error in RG[[a]][, i] <- obj[, columns[[a]]] : >>> number of items to replace is not a multiple of replacement length >>> >>> >>> I'm assuming this is down to the fact that the files only contain >>> intensity data for one color rather than two? >>> >>> How should I go about reading the data? >>> >>> Thanks alot, >>> >>> -Paul. >>> >>> On Tue, May 6, 2008 at 10:15 PM, Deepayan Sarkar >>> <deepayan.sarkar at="" gmail.com=""> wrote: >>> > On 5/6/08, Paul Geeleher <paulgeeleher at="" gmail.com=""> wrote: >>> > > Dear Members, >>> > > >>> > > I've inherited a bunch of GenePix files from an miRNA experiment. >>> They >>> > > are single color arrays, ( as opposed to 2 color as is the norm >>> for >>> > > GenePix I think). There is a subset of 7 arrays and I wish to >>> compare >>> > > a group of 4 of these to the other group of 3 and analyze >>> differential >>> > > expression between the two groups. I was hoping somebody could >>> point >>> > > me in the right direction of how I'd go about doing this with >>> > > Bioconductor? Is it possible using the Limma package? Is there any >>> > > code out there to assist me? >>> > > >>> > > I've experience in analyzing Affymetrix data using Limma and PUMA, >>> but >>> > > not GenePix, and the Limma Users Guide seems to focus on analyzing >>> two >>> > > dye experiments. >>> > >>> > Any analysis ultimately boils down to some sort of normalization, and >>> > the actual differential expression analysis. The second part in limma >>> > (lmFit, etc.) can work with any expression matrix, irrespective of >>> > whether it's 2-color or 1-color (or affy). >>> > >>> > We have been working with a miRNA array dataset recently, and we used >>> > limma to read in the GPR files and do the differential expression >>> > analysis (on one channel). For normalization, many of the standard >>> > microarray algorithms probably don't make much sense, but VSN seems >>> to >>> > work fine. >>> > >>> > We don't really have code (beyond what's already in limma and vsn) >>> > that is generally useful; most of the work is in figuring out which >>> > rows are of interest (i.e., those representing human miRNAs), >>> > combining the replicates (you seem to have four of each), etc. I'm >>> > happy to give you more details if you are interested. >>> > >>> > -Deepayan >>> > >
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