Limma: combining 2 microarray studies
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Ana Conesa ▴ 140
@ana-conesa-925
Last seen 10.2 years ago
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Ana Conesa ▴ 140
@ana-conesa-925
Last seen 10.2 years ago
Hi, I have been asked to analyze jointly two different microarray studies (2 color technology). They use the same microarray platform and represent the same biological process but each one follows a different experimental design and evaluate slightly different conditions One study has a reference design, while the other is a dye-swap of pairs treatment vs. control, schematically Study A: Cy3 Cy5 chipA1 trt1 reference chipA2 trt1 reference chipA3 trt2 reference chipA4 trt2 reference ..... Study B Cy3 Cy5 chipB1 trt3 control.trt3 chipB2 control.trt3 trt3 chipB3 trt4 control.trt4 chipB4 control.trt3 trt4 ..... We would like to make comparisons between treatments in Study A and treatments in Study B. (e.g., trt1 and trt3) I am not sure on how I should set design and contrasts in Limma to address such comparisons (if possible). Maybe someone in the List can give me some hints? Thank you Ana -- IVIA (http://www.ivia.es) Open WebMail Project (http://openwebmail.org) Debian Project (http://www.debian.org)
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Quoting Ana Conesa <aconesa at="" ivia.es="">: > > Hi, > I have been asked to analyze jointly two different microarray studies (2 > color technology). They use the same microarray platform and represent the > same biological process but each one follows a different experimental design > and evaluate slightly different conditions > One study has a reference design, while the other is a dye-swap of pairs > treatment vs. control, schematically > Study A: > Cy3 Cy5 > chipA1 trt1 reference > chipA2 trt1 reference > chipA3 trt2 reference > chipA4 trt2 reference > ..... > > Study B > Cy3 Cy5 > chipB1 trt3 control.trt3 > chipB2 control.trt3 trt3 > chipB3 trt4 control.trt4 > chipB4 control.trt3 trt4 > ..... > > > We would like to make comparisons between treatments in Study A and > treatments in Study B. (e.g., trt1 and trt3) > > I am not sure on how I should set design and contrasts in Limma to address > such comparisons (if possible). Maybe someone in the List can give me some > hints? > > Thank you > > Ana Hola Ana, I am not the most experienced here exactly, but what you are trying to do sounds a lot like an example in the Limma user's guide: Chapter 17, separate channel analysis of two-color data. Have you looked at that? Jose -- Dr. Jose I. de las Heras Email: J.delasHeras at ed.ac.uk The Wellcome Trust Centre for Cell Biology Phone: +44 (0)131 6513374 Institute for Cell & Molecular Biology Fax: +44 (0)131 6507360 Swann Building, Mayfield Road University of Edinburgh Edinburgh EH9 3JR UK
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Dera group, limma is an excellent module for gene expression data preprocessing and analysis. however, I looked into many places i did not find a good tutorial when the .gpr file is not what I it should look like. Also, when GAL file is not the same what it should be. I have a dataset downloaded from ArrayExpress and has the following column names: [B635+1SD B635+2SD Autoflag B Pixels B635 B635 CV B635 Mean B635 Median B635 SD Circularity Dia. F Pixels F635 % Sat. F635 CV F635 Mean F635 Mean - B635 F635 Median F635 Median - B635 F635 SD F635 Total Intensity Flags Normalize SNR 635] The chip definition file obtained from "Array design used" section of ArrayExpress has the following columns: [MetaColumn MetaRow Column Row Reporter Identifier Reporter Name Reporter Biosequence Type Reporter actual Sequence Reporter Comment Reporter Group Role Reporter Control Type CompositeSequence Identifier CompositeSequence Name Composite Sequence Comment] when i did: dat <- read.maimages('filename',source ='genepix.custom') I get "Error in readGPRHeader(fullname) : File is not in Axon Text File (ATF) format" my questions are: what should I tell read.maimages to accept my file and process further. what should I do when I do not have GAL file. how can the other file help me get genelist etc. Please help me. Thanks sri
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Quoting Srinivas Iyyer <srini_iyyer_bio at="" yahoo.com="">: > Dera group, > limma is an excellent module for gene expression data > preprocessing and analysis. > however, I looked into many places i did not find a > good tutorial when the .gpr file is not what I it > should look like. Also, when GAL file is not the same > what it should be. > > I have a dataset downloaded from ArrayExpress and has > the following column names: > > [B635+1SD B635+2SD Autoflag B Pixels B635 B635 CV B635 > Mean B635 Median B635 SD Circularity Dia. F Pixels > F635 % Sat. F635 CV F635 Mean F635 Mean - B635 F635 > Median F635 Median - B635 F635 SD F635 Total Intensity > Flags Normalize SNR 635] > > > The chip definition file obtained from "Array design > used" section of ArrayExpress has the following > columns: > > [MetaColumn MetaRow Column Row Reporter Identifier > Reporter Name Reporter Biosequence Type Reporter > actual Sequence Reporter Comment Reporter Group Role > Reporter Control Type CompositeSequence Identifier > CompositeSequence Name Composite Sequence Comment] > > when i did: > dat <- read.maimages('filename',source > ='genepix.custom') > > I get "Error in readGPRHeader(fullname) : File is not > in Axon Text File (ATF) format" > > > my questions are: > > what should I tell read.maimages to accept my file and > process further. > > what should I do when I do not have GAL file. how can > the other file help me get genelist etc. > > Please help me. > > Thanks > sri I am not sure what's the simplest way to go about it, but when in doubt, I'd just define everything myself. I'd probably make my own GAL file first. You need to convert the MR MC R C coordinates you have into Block, Row and Column. I had the same issue when using TIGR Spotfinder to quantitate my images. If you sort your info by MR, then MC, and then R, that's the same order as the GAL should be (B,R,C). R and C are your Row and Column columns. MR/MC defines each block (blocks are counted from the top left towards the right, across "metarows"... so MR,MC (1,1) is Block 1, MR,MC (1,2) is Block 2, etc... If you write your GAL file starting with the columns: Block Column Row Name ID... as in an original GAL file, then that's it. Your data has to be sorted the same way, of course. The GAL file only has to be created once. And for the data resorting (if necessary) you could just make a little script to re-format the input everytime automatically, before you feed it to read.maimages. Then just read the data specifying the actual column names: RG<-read.maimages(targets$FileName, columns=list(Gf="F532 Median", Gb="B532", Rf="F635 Median", Rb="B635")) This works for me... I use Genepix and/or SpotFinder data. Jose -- Dr. Jose I. de las Heras Email: J.delasHeras at ed.ac.uk The Wellcome Trust Centre for Cell Biology Phone: +44 (0)131 6513374 Institute for Cell & Molecular Biology Fax: +44 (0)131 6507360 Swann Building, Mayfield Road University of Edinburgh Edinburgh EH9 3JR UK
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Dear Jose, thank you very much. I could create GAL file. however there is a problem now. The data i obtained is from ArrayExpression. Experiment - E-TABM-68, when I click to obtain raw data, there are only 23 quantitation types provided. Of which there is only ONE channel data provided. which is F and B of 635. No F and B of 532 provided. In this case, what does that mean. Did the submitter already analyzed the data? Or was there some kind of problem in uploading data? Or is there a way from which expression values(M and A) from only 635 (Cy5) can be calculated effectively. URL: http://www.ebi.ac.uk/arrayexpress/query/dataselection;jsessionid=AD367 CE324DD14165D2F475107E4A3DC?expid=826113654 Could any one please comment on this. Thanks again. Sri --- J.delasHeras at ed.ac.uk wrote: > Quoting Srinivas Iyyer <srini_iyyer_bio at="" yahoo.com="">: > > > Dera group, > > limma is an excellent module for gene expression > data > > preprocessing and analysis. > > however, I looked into many places i did not find > a > > good tutorial when the .gpr file is not what I it > > should look like. Also, when GAL file is not the > same > > what it should be. > > > > I have a dataset downloaded from ArrayExpress and > has > > the following column names: > > > > [B635+1SD B635+2SD Autoflag B Pixels B635 B635 CV > B635 > > Mean B635 Median B635 SD Circularity Dia. F Pixels > > F635 % Sat. F635 CV F635 Mean F635 Mean - B635 > F635 > > Median F635 Median - B635 F635 SD F635 Total > Intensity > > Flags Normalize SNR 635] > > > > > > The chip definition file obtained from "Array > design > > used" section of ArrayExpress has the following > > columns: > > > > [MetaColumn MetaRow Column Row Reporter Identifier > > Reporter Name Reporter Biosequence Type Reporter > > actual Sequence Reporter Comment Reporter Group > Role > > Reporter Control Type CompositeSequence Identifier > > CompositeSequence Name Composite Sequence Comment] > > > > when i did: > > dat <- read.maimages('filename',source > > ='genepix.custom') > > > > I get "Error in readGPRHeader(fullname) : File is > not > > in Axon Text File (ATF) format" > > > > > > my questions are: > > > > what should I tell read.maimages to accept my file > and > > process further. > > > > what should I do when I do not have GAL file. how > can > > the other file help me get genelist etc. > > > > Please help me. > > > > Thanks > > sri > > I am not sure what's the simplest way to go about > it, but when in > doubt, I'd just define everything myself. > > I'd probably make my own GAL file first. You need to > convert the MR MC > R C coordinates you have into Block, Row and Column. > I had the same > issue when using TIGR Spotfinder to quantitate my > images. If you sort > your info by MR, then MC, and then R, that's the > same order as the GAL > should be (B,R,C). R and C are your Row and Column > columns. MR/MC > defines each block (blocks are counted from the top > left towards the > right, across "metarows"... so MR,MC (1,1) is Block > 1, MR,MC (1,2) is > Block 2, etc... If you write your GAL file starting > with the columns: > Block Column Row Name ID... as in an original GAL > file, then that's it. > Your data has to be sorted the same way, of course. > > The GAL file only has to be created once. And for > the data resorting > (if necessary) you could just make a little script > to re-format the > input everytime automatically, before you feed it to > read.maimages. > > Then just read the data specifying the actual column > names: > > RG<-read.maimages(targets$FileName, > columns=list(Gf="F532 Median", > Gb="B532", Rf="F635 Median", Rb="B635")) > > This works for me... I use Genepix and/or SpotFinder > data. > > Jose > > -- > Dr. Jose I. de las Heras Email: > J.delasHeras at ed.ac.uk > The Wellcome Trust Centre for Cell Biology Phone: > +44 (0)131 6513374 > Institute for Cell & Molecular Biology Fax: > +44 (0)131 6507360 > Swann Building, Mayfield Road > University of Edinburgh > Edinburgh EH9 3JR > UK > >
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Quoting J.delasHeras at ed.ac.uk: > I am not the most experienced here exactly, but what you are trying to > do sounds a lot like an example in the Limma user's guide: Chapter 17, > separate channel analysis of two-color data. Have you looked at that? whops, that should have said Chapter 9! (limma 2.2.0, users guide Oct'05). I was looking at an older version... Jose -- Dr. Jose I. de las Heras Email: J.delasHeras at ed.ac.uk The Wellcome Trust Centre for Cell Biology Phone: +44 (0)131 6513374 Institute for Cell & Molecular Biology Fax: +44 (0)131 6507360 Swann Building, Mayfield Road University of Edinburgh Edinburgh EH9 3JR UK
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