Nimblegen arrays; random probes
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@maria-jose-rivas-5696
Last seen 10.2 years ago
Hi all, I have an experiment with 72 cDNA Nimblegen arrays. I notice that the arrays have some probes type RANDOM (I guess that there are control probes). I have performed the normalization doing: 1. Background correction RG50_bg <- backgroundCorrect (RGback, method="normexp", offset=50) RGback$printer <- list(ngrid.r=1, ngrid.c=1, nspot.r=nrow(RGback), nspot.c=ncol(RGback)) 2. Between-array normalization MA.q_50_bg <- normalizeBetweenArrays(RG50_bg, method="quantile") In the object MA.q_50_bg there are still random probes. Should the normalization removes them??? Or is normal doing the analysis with random probes??? Thanks in advance, -- María José Rivas Quelle (PhD. Student) Área de Genética (Grupo Xb2) Dpto. Bioquímica, Genética e Inmunología Facultad de Biología 36310 Universidad de Vigo (SPAIN) [[alternative HTML version deleted]]
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@todd-richmond-3065
Last seen 10.2 years ago
Hi Maria, The RANDOM probes on the NimbleGen arrays are randomly generated probes with the same length and GC content characteristics as the experimental probes on the array. They are meant to give researchers an estimate of the signal from non-specific binding on the array. There should be no harm in carrying them through the analysis, and the final expression value generated for those probes can be a useful threshold for estimating which transcripts are expressed above the background level. Todd On Thu, Jan 10, 2013 at 6:24 AM, María José Rivas <marivas@uvigo.es> wrote: > Hi all, > > I have an experiment with 72 cDNA Nimblegen arrays. I notice that the > arrays have some probes type RANDOM (I guess that there are control > probes). I have performed the normalization doing: > > 1. Background correction > > RG50_bg <- backgroundCorrect (RGback, method="normexp", offset=50) > > RGback$printer <- list(ngrid.r=1, ngrid.c=1, nspot.r=nrow(RGback), > nspot.c=ncol(RGback)) > > > 2. Between-array normalization > > MA.q_50_bg <- normalizeBetweenArrays(RG50_bg, method="quantile") > > In the object MA.q_50_bg there are still random probes. Should the > normalization removes them??? Or is normal doing the analysis with random > probes??? > > Thanks in advance, > > > -- > > María José Rivas Quelle (PhD. Student) > Área de Genética (Grupo Xb2) > Dpto. Bioquímica, Genética e Inmunología > Facultad de Biología 36310 > Universidad de Vigo (SPAIN) > > [[alternative HTML version deleted]] > > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Dr Todd Richmond, PhD richmond.todd@gmail.com [[alternative HTML version deleted]]
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Firstly, thanks you a lot for reply me. The strange thing is that, after doing eBayes(), in my significant probes appears some RANDOM probes. 2013/1/10 Todd Richmond <richmond.todd@gmail.com> > Hi Maria, > > The RANDOM probes on the NimbleGen arrays are randomly generated probes > with the same length and GC content characteristics as the experimental > probes on the array. They are meant to give researchers an estimate of the > signal from non-specific binding on the array. There should be no harm in > carrying them through the analysis, and the final expression value > generated for those probes can be a useful threshold for estimating which > transcripts are expressed above the background level. > > Todd > > > On Thu, Jan 10, 2013 at 6:24 AM, María José Rivas <marivas@uvigo.es>wrote: > >> Hi all, >> >> I have an experiment with 72 cDNA Nimblegen arrays. I notice that the >> arrays have some probes type RANDOM (I guess that there are control >> probes). I have performed the normalization doing: >> >> 1. Background correction >> >> RG50_bg <- backgroundCorrect (RGback, method="normexp", offset=50) >> >> RGback$printer <- list(ngrid.r=1, ngrid.c=1, nspot.r=nrow(RGback), >> nspot.c=ncol(RGback)) >> >> >> 2. Between-array normalization >> >> MA.q_50_bg <- normalizeBetweenArrays(RG50_bg, method="quantile") >> >> In the object MA.q_50_bg there are still random probes. Should the >> normalization removes them??? Or is normal doing the analysis with random >> probes??? >> >> Thanks in advance, >> >> >> -- >> >> María José Rivas Quelle (PhD. Student) >> Área de Genética (Grupo Xb2) >> Dpto. Bioquímica, Genética e Inmunología >> Facultad de Biología 36310 >> Universidad de Vigo (SPAIN) >> >> [[alternative HTML version deleted]] >> >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > > > -- > Dr Todd Richmond, PhD > richmond.todd@gmail.com > -- María José Rivas Quelle (PhD. Student) Área de Genética (Grupo Xb2) Dpto. Bioquímica, Genética e Inmunología Facultad de Biología 36310 Universidad de Vigo (SPAIN) [[alternative HTML version deleted]]
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@james-w-macdonald-5106
Last seen 9 hours ago
United States
Hi Maria, On 1/10/2013 9:24 AM, Mar?a Jos? Rivas wrote: > Hi all, > > I have an experiment with 72 cDNA Nimblegen arrays. I notice that the > arrays have some probes type RANDOM (I guess that there are control > probes). I have performed the normalization doing: > > 1. Background correction > > RG50_bg<- backgroundCorrect (RGback, method="normexp", offset=50) > > RGback$printer<- list(ngrid.r=1, ngrid.c=1, nspot.r=nrow(RGback), > nspot.c=ncol(RGback)) > > > 2. Between-array normalization > > MA.q_50_bg<- normalizeBetweenArrays(RG50_bg, method="quantile") > > In the object MA.q_50_bg there are still random probes. Should the > normalization removes them??? Or is normal doing the analysis with random > probes??? The normalization simply attempts to adjust the array distributions in order to account for technical variability. There is no removal of probes (and how would a function designed to work on arbitrary arrays know which probes to remove?). If these probes are in fact controls (which you don't seem to know, and as the analyst it is your job to know these things), then you can argue that they should be removed at some point. The usual prescription is to remove after the eBayes() step. Best, Jim > > Thanks in advance, > > > > > _______________________________________________ > 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 -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099
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