One-color spotted microarrays analysis
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@pier-luc-poulin-3461
Last seen 10.2 years ago
Hi everyone, I have a general question about microarray data analysis using bioconductor. We are using a 32k custom spotted oligo array and we are planning on doing one-color microarray experiments. We need advice on how to proceed with data normalization and analysis. We have searched in the literature and in the vignettes and user guides of BioConductor but it seems that almost every experiment with spotted arrays is done with two colors. No documentation exists for single channel spotted microarrays, except for the article by 't Hoen et al., 2004, Nucleic Acids Research. Does anyone have knowledge or suggestions on methods or Bioconductor packages that could be used for this kind of analysis? Thanks, P-L Poulin Research assistant Universit? Laval www.arborea.ca
Microarray Normalization oligo Microarray Normalization oligo • 2.1k views
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Massimo Pinto ▴ 390
@massimo-pinto-3396
Last seen 10.2 years ago
Dear Pier Luc,there is support for one color microarrays in BioConductor. As far as I know, affymetrix (package "affy") and agilent (package Agi4x44PreProcess) arrays are supported, and there may be way more than that. Massimo -- Massimo Pinto Post Doctoral Research Fellow Enrico Fermi Centre and Italian Public Health Research Institute (ISS), Rome http://claimid.com/massimopinto [[alternative HTML version deleted]]
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Dear Pier Luc, there is support for one color microarrays in BioConductor. As far as I know, affymetrix (package "affy") and agilent (package Agi4x44PreProcess)?arrays are supported, and there may be way more than that. Massimo -- Massimo Pinto Post Doctoral Research Fellow Enrico Fermi Centre and Italian Public Health Research Institute (ISS), Rome http://claimid.com/massimopinto
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@pier-luc-poulin-3461
Last seen 10.2 years ago
Hi Massimo and everyone, Thanks for the suggestion. I've read documentation about Agi4x44PreProcess and Affy packages but I still need advice. Agi4x44PreProcess contains no method for normalization between print tips within arrays. Our data consists of single color spotted chips. We need to find a way in bioconductor to do within array normalization. Limma's normalizeWithinArrays and marray's maNormMain only do that for two color arrays. I haven't find any function for normalizing single channel arrays, except for affymetrix chips. Thanks P-L Poulin Research assistant Universit? Laval www.arborea.ca
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Hi Pier-Luc, What sort of within array normalisation are you trying to perform? ie what issues have you spotted in your data that you think need removing? There are no print-tip's as such on an agilent array since they're printed by fancy ink jet printers. You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps by taking the average of all channels. cheers, Mark ----------------------------------------------------- Mark Cowley, PhD Peter Wills Bioinformatics Centre Garvan Institute of Medical Research, Sydney, Australia ----------------------------------------------------- On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote: > Hi Massimo and everyone, > > Thanks for the suggestion. I've read documentation about > Agi4x44PreProcess > and Affy packages but I still need advice. Agi4x44PreProcess > contains no > method for normalization between print tips within arrays. > > Our data consists of single color spotted chips. We need to find a way > in bioconductor to do within array normalization. Limma's > normalizeWithinArrays > and marray's maNormMain only do that for two color arrays. I haven't > find > any function for normalizing single channel arrays, except for > affymetrix chips. > > Thanks > > P-L Poulin > Research assistant > Universit? Laval > www.arborea.ca > > _______________________________________________ > 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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I am aware of 2 methods. You could do quantile normalization. This is very stringent as it forces the overall expression distribution to be the same on every array. You could pick one array (or the genewise mean or median of all arrays) to act as the "control" and lowess normalize everything relative to that array. --Naomi At 09:05 PM 5/21/2009, Mark Cowley wrote: >Hi Pier-Luc, >What sort of within array normalisation are you trying to perform? ie >what issues have you spotted in your data that you think need removing? > >There are no print-tip's as such on an agilent array since they're >printed by fancy ink jet printers. >You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps >by taking the average of all channels. > >cheers, >Mark >----------------------------------------------------- >Mark Cowley, PhD > >Peter Wills Bioinformatics Centre >Garvan Institute of Medical Research, Sydney, Australia >----------------------------------------------------- >On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote: > >>Hi Massimo and everyone, >> >>Thanks for the suggestion. I've read documentation about >>Agi4x44PreProcess >>and Affy packages but I still need advice. Agi4x44PreProcess >>contains no >>method for normalization between print tips within arrays. >> >>Our data consists of single color spotted chips. We need to find a way >>in bioconductor to do within array normalization. Limma's >>normalizeWithinArrays >>and marray's maNormMain only do that for two color arrays. I haven't >>find >>any function for normalizing single channel arrays, except for >>affymetrix chips. >> >>Thanks >> >>P-L Poulin >>Research assistant >>Universit? Laval >>www.arborea.ca >> >>_______________________________________________ >>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 > >_______________________________________________ >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 Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111
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Thank Naomi and Mark for the suggestions. Quantile normalization will be used to normalize between arrays but we have a spatial problem within arrays. Our arrays are custom oligo arrays. We have 48 print-tips on the array and there is an intensity bias from top to bottom of the arrays. I would like to normalize the spatial distribution of intensities between sub-arrays. Can a 2d spatial normalization be done without creating a "virtual" channel and using only one channel? Which package and function of BioConductor should I use? Thanks P-L Poulin Research assistant Universit? Laval www.arborea.ca -----Message d'origine----- De?: Naomi Altman [mailto:naomi at stat.psu.edu] Envoy??: May 21, 2009 11:19 PM ??: Mark Cowley; Pier-Luc Poulin Cc?: bioconductor at stat.math.ethz.ch Objet?: Re: [BioC] One-color spotted microarrays analysis I am aware of 2 methods. You could do quantile normalization. This is very stringent as it forces the overall expression distribution to be the same on every array. You could pick one array (or the genewise mean or median of all arrays) to act as the "control" and lowess normalize everything relative to that array. --Naomi At 09:05 PM 5/21/2009, Mark Cowley wrote: >Hi Pier-Luc, >What sort of within array normalisation are you trying to perform? ie >what issues have you spotted in your data that you think need removing? > >There are no print-tip's as such on an agilent array since they're >printed by fancy ink jet printers. >You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps >by taking the average of all channels. > >cheers, >Mark >----------------------------------------------------- >Mark Cowley, PhD > >Peter Wills Bioinformatics Centre >Garvan Institute of Medical Research, Sydney, Australia >----------------------------------------------------- >On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote: > >>Hi Massimo and everyone, >> >>Thanks for the suggestion. I've read documentation about >>Agi4x44PreProcess >>and Affy packages but I still need advice. Agi4x44PreProcess >>contains no >>method for normalization between print tips within arrays. >> >>Our data consists of single color spotted chips. We need to find a way >>in bioconductor to do within array normalization. Limma's >>normalizeWithinArrays >>and marray's maNormMain only do that for two color arrays. I haven't >>find >>any function for normalizing single channel arrays, except for >>affymetrix chips. >> >>Thanks >> >>P-L Poulin >>Research assistant >>Universit? Laval >>www.arborea.ca >> >>_______________________________________________ >>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 > >_______________________________________________ >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 Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111
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Hi Pier-Luc here's one more option: the "strata" parameter of vsn2 (in the vsn package) allows fitting the normalisation model separately for (print-tip) groups of probes, for an arbitrary number of one-colour arrays. If non-linear regression is desired, the method described in [1] is less ad hoc and less clumsy than loess against a "virtual second channel". [1] Normalization and analysis of DNA microarray data by self-consistency and local regression, TB Kepler, L Crosby, KT Morgan - Genome Biol, 2002. Best wishes Wolfgang Naomi Altman ha scritto: > I am aware of 2 methods. > > You could do quantile normalization. This is very stringent as it > forces the overall expression distribution to be the same on every array. > > You could pick one array (or the genewise mean or median of all arrays) > to act as the "control" and lowess normalize everything relative to that > array. > > --Naomi > > At 09:05 PM 5/21/2009, Mark Cowley wrote: >> Hi Pier-Luc, >> What sort of within array normalisation are you trying to perform? ie >> what issues have you spotted in your data that you think need removing? >> >> There are no print-tip's as such on an agilent array since they're >> printed by fancy ink jet printers. >> You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps >> by taking the average of all channels. >> >> cheers, >> Mark >> ----------------------------------------------------- >> Mark Cowley, PhD >> >> Peter Wills Bioinformatics Centre >> Garvan Institute of Medical Research, Sydney, Australia >> ----------------------------------------------------- >> On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote: >> >>> Hi Massimo and everyone, >>> >>> Thanks for the suggestion. I've read documentation about >>> Agi4x44PreProcess >>> and Affy packages but I still need advice. Agi4x44PreProcess >>> contains no >>> method for normalization between print tips within arrays. >>> >>> Our data consists of single color spotted chips. We need to find a way >>> in bioconductor to do within array normalization. Limma's >>> normalizeWithinArrays >>> and marray's maNormMain only do that for two color arrays. I haven't >>> find >>> any function for normalizing single channel arrays, except for >>> affymetrix chips. >>> >>> Thanks >>> >>> P-L Poulin >>> Research assistant >>> Universit? Laval >>> www.arborea.ca >>> >>> _______________________________________________ >>> 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 >> >> _______________________________________________ >> 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 > > Naomi S. Altman 814-865-3791 (voice) > Associate Professor > Dept. of Statistics 814-863-7114 (fax) > Penn State University 814-865-1348 (Statistics) > University Park, PA 16802-2111 > > _______________________________________________ > 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 -- Best wishes Wolfgang ------------------------------------------------ Wolfgang Huber, EMBL, http://www.ebi.ac.uk/huber
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Suggestion: Your scanner probably shift your data by a small constant (~15-25 => significant impact) due to what I call "scanner offset" (Bengtsson et al. 2004). This offset tends to be stable across scans (arrays). Try to correct for this single(!) parameter before anything else. This will simplify your life and safe you many hours. You can either estimate it by assume it is there or estimate it using a multiscan protocol as suggested in the above reference. Methods are available in aroma.light. Then follow what has already been suggested by others - often things are rather linear afterward so simple rescaling (or linear regression) will take you quite far. H. Bengtsson, J. Vallon-Christersson and G. J?nsson, Calibration and assessment of channel-specific biases in microarray data with extended dynamical range, BMC Bioinformatics, 5:177, 2004. My $.02 /Henrik On Tue, May 26, 2009 at 3:22 PM, Wolfgang Huber <huber at="" ebi.ac.uk=""> wrote: > Hi Pier-Luc > > here's one more option: the "strata" parameter of vsn2 (in the vsn package) > allows fitting the normalisation model separately for (print-tip) groups of > probes, for an arbitrary number of one-colour arrays. > > If non-linear regression is desired, the method described in [1] is less ad > hoc and less clumsy than loess against a "virtual second channel". > > [1] Normalization and analysis of DNA microarray data by self- consistency > and local regression, TB Kepler, L Crosby, KT Morgan - Genome Biol, 2002. > > ?Best wishes > ? ? ? ?Wolfgang > > Naomi Altman ha scritto: >> >> I am aware of 2 methods. >> >> You could do quantile normalization. ?This is very stringent as it forces >> the overall expression distribution to be the same on every array. >> >> You could pick one array (or the genewise mean or median of all arrays) to >> act as the "control" and lowess normalize everything relative to that array. >> >> --Naomi >> >> At 09:05 PM 5/21/2009, Mark Cowley wrote: >>> >>> Hi Pier-Luc, >>> What sort of within array normalisation are you trying to perform? ie >>> what issues have you spotted in your data that you think need removing? >>> >>> There are no print-tip's as such on an agilent array since they're >>> printed by fancy ink jet printers. >>> You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps >>> by taking the average of all channels. >>> >>> cheers, >>> Mark >>> ----------------------------------------------------- >>> Mark Cowley, PhD >>> >>> Peter Wills Bioinformatics Centre >>> Garvan Institute of Medical Research, Sydney, Australia >>> ----------------------------------------------------- >>> On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote: >>> >>>> Hi Massimo and everyone, >>>> >>>> Thanks for the suggestion. I've read documentation about >>>> Agi4x44PreProcess >>>> and Affy packages but I still need advice. Agi4x44PreProcess >>>> contains no >>>> method for normalization between print tips within arrays. >>>> >>>> Our data consists of single color spotted chips. We need to find a way >>>> in bioconductor to do within array normalization. Limma's >>>> normalizeWithinArrays >>>> and marray's maNormMain only do that for two color arrays. I haven't >>>> find >>>> any function for normalizing single channel arrays, except for >>>> affymetrix chips. >>>> >>>> Thanks >>>> >>>> P-L Poulin >>>> Research assistant >>>> Universit? Laval >>>> www.arborea.ca >>>> >>>> _______________________________________________ >>>> 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 >>> >>> _______________________________________________ >>> 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 >> >> Naomi S. Altman ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?814-865-3791 (voice) >> Associate Professor >> Dept. of Statistics ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?814-863-7114 (fax) >> Penn State University ? ? ? ? ? ? ? ? ? ? ? ? 814-865-1348 (Statistics) >> University Park, PA 16802-2111 >> >> _______________________________________________ >> 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 > > > -- > > Best wishes > ? ? Wolfgang > > ------------------------------------------------ > Wolfgang Huber, EMBL, http://www.ebi.ac.uk/huber > > _______________________________________________ > 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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Naomi Altman ★ 6.0k
@naomi-altman-380
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I have never done spatial normalization. However, my expertise is nonparametric smoothing. You should not need a virtual channel to remove the spatial effect, because you are regressing on the x,y co-ordinates, not the spot means. I think this is available in either marray or limma. However, if it is not, you can use the loess function to do 2-d regression and then use the residuals as the expression values. (Usually you would do this after taking log2(expression)). Usually some constant is added back so that the array mean is not zero but some positive number. --Naomi At 07:50 AM 5/22/2009, Pier-Luc Poulin wrote: >Thank Naomi and Mark for the suggestions. Quantile normalization >will be used to normalize between arrays but we have a spatial >problem within arrays. > >Our arrays are custom oligo arrays. We have 48 print-tips on >the array and there is an intensity bias from top to bottom >of the arrays. I would like to normalize the spatial distribution >of intensities between sub-arrays. Can a 2d spatial normalization >be done without creating a "virtual" channel and using only >one channel? > >Which package and function of BioConductor should I use? > >Thanks > >P-L Poulin >Research assistant >Universit? Laval >www.arborea.ca > >-----Message d'origine----- >De : Naomi Altman [mailto:naomi at stat.psu.edu] >Envoy? : May 21, 2009 11:19 PM >? : Mark Cowley; Pier-Luc Poulin >Cc : bioconductor at stat.math.ethz.ch >Objet : Re: [BioC] One-color spotted microarrays analysis > >I am aware of 2 methods. > >You could do quantile normalization. This is >very stringent as it forces the overall >expression distribution to be the same on every array. > >You could pick one array (or the genewise mean or >median of all arrays) to act as the "control" and >lowess normalize everything relative to that array. > >--Naomi > >At 09:05 PM 5/21/2009, Mark Cowley wrote: > >Hi Pier-Luc, > >What sort of within array normalisation are you trying to perform? ie > >what issues have you spotted in your data that you think need removing? > > > >There are no print-tip's as such on an agilent array since they're > >printed by fancy ink jet printers. > >You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps > >by taking the average of all channels. > > > >cheers, > >Mark > >----------------------------------------------------- > >Mark Cowley, PhD > > > >Peter Wills Bioinformatics Centre > >Garvan Institute of Medical Research, Sydney, Australia > >----------------------------------------------------- > >On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote: > > > >>Hi Massimo and everyone, > >> > >>Thanks for the suggestion. I've read documentation about > >>Agi4x44PreProcess > >>and Affy packages but I still need advice. Agi4x44PreProcess > >>contains no > >>method for normalization between print tips within arrays. > >> > >>Our data consists of single color spotted chips. We need to find a way > >>in bioconductor to do within array normalization. Limma's > >>normalizeWithinArrays > >>and marray's maNormMain only do that for two color arrays. I haven't > >>find > >>any function for normalizing single channel arrays, except for > >>affymetrix chips. > >> > >>Thanks > >> > >>P-L Poulin > >>Research assistant > >>Universit? Laval > >>www.arborea.ca > >> > >>_______________________________________________ > >>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 > > > >_______________________________________________ > >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 > >Naomi S. Altman 814-865-3791 (voice) >Associate Professor >Dept. of Statistics 814-863-7114 (fax) >Penn State University 814-865-1348 (Statistics) >University Park, PA 16802-2111 > >_______________________________________________ >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 Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111
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@wolfgang-huber-3550
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Pier-Luc Poulin ha scritto: > Hi everyone, > > I have a general question about microarray data analysis using bioconductor. > > We are using a 32k custom spotted oligo array and we are planning on doing one-color microarray experiments. We need advice on how to proceed with data normalization and analysis. We have searched in the literature and in the vignettes and user guides of BioConductor but it seems that almost every experiment with spotted arrays is done with two colors. No documentation exists for single channel spotted microarrays, except for the article by 't Hoen et al., 2004, Nucleic Acids Research. > > Does anyone have knowledge or suggestions on methods or Bioconductor packages that could be used for this kind of analysis? > > Thanks, > > P-L Poulin > Research assistant > Universit? Laval > www.arborea.ca > > _______________________________________________ > 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 Dear Pier-Luc from the data analysis point of view, it does not make a substantial difference whether the DNA on the array probes was brought there by a spotter or synthesized in situ. There is an enormous amount of documentation on the analysis of one-colour arrays, and chapter 7.2 of the limma vignette might be a good start. More specifically, you could consider the justvsn function from the vsn package or the normalizeQuantiles function from the limma package for normalisation; and the arrayQualityMetrics package for quality-related diagnostics. Best wishes Wolfgang ------------------------------------------------ Wolfgang Huber, EMBL, http://www.ebi.ac.uk/huber
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