Question: Most diff exp genes are up-regulated... can this be true?
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gravatar for Peter Davidsen
6.4 years ago by
Peter Davidsen210 wrote:
Dear List, I'm analysing some one-color microarray data generated using a custom designed Agilent array (their 8 x 60K platform). When I compare control samples to treated ones most (i.e. >80%) of the differentially expressed transcripts are up-regulated. This pronounced up-regulation is independent of type of treatment. I have never before experienced such a quantitative difference in the number of up- and down-regulated transcripts. Furthermore, I have tried to analyse relevant datasets in the GEO that mimics my study design in terms of treatment regime, duration of treatment ect. These analyses--all in closely related species--suggest that the fraction of up and down-regulated transcripts should be roughly the same. The QC reports generated by the Agilent Feature Extraction Software indicate that the data quality should be fine. Also a few basic boxplot before and after normalization haven't raised my suspicion. I do, however, find that the median signal intensity for each sample is significantly lower than what I've seen in the past with the same platform (although targeted against another related species). I have tried to normalize my data using both quantile and vsn, respectively, with similar result. I have also tried to filter my dataset using different intensity filters - again with similar result. And finally, I also tried using both limma and SAMR for the statistics. Have anyone by any chance experienced something similar, and how did you deal with this issue of many siggenes going in one direction? Many thanks, Peter
ADD COMMENTlink written 6.4 years ago by Peter Davidsen210
Answer: Most diff exp genes are up-regulated... can this be true?
0
gravatar for Peter Davidsen
6.4 years ago by
Peter Davidsen210 wrote:
Dear List, I'm analysing some one-color microarray data generated using a custom designed Agilent array (their 8 x 60K platform). When I compare control samples to treated ones most (i.e. >80%) of the differentially expressed transcripts are up-regulated. This pronounced up-regulation is independent of type of treatment. I have never before experienced such a quantitative difference in the number of up- and down-regulated transcripts. Furthermore, I have tried to analyse relevant datasets in the GEO that mimics my study design in terms of treatment regime, duration of treatment ect. These analyses--all in closely related species--suggest that the fraction of up and down-regulated transcripts should be roughly the same. The QC reports generated by the Agilent Feature Extraction Software indicate that the data quality should be fine. Also a few basic boxplot before and after normalization haven't raised my suspicion. I do, however, find that the median signal intensity for each sample is significantly lower than what I've seen in the past with the same platform (although targeted against another related species). I have tried to normalize my data using both quantile and vsn, respectively, with similar result. I have also tried to filter my dataset using different intensity filters - again with similar result. And finally, I also tried using both limma and SAMR for the statistics. Have anyone by any chance experienced something similar, and how did you deal with this issue of many siggenes going in one direction? Many thanks, Peter
ADD COMMENTlink written 6.4 years ago by Peter Davidsen210
Dear Peter did you already generate a quality report with 'arrayQualityMetrics'? Also, I assume you (or the biologist who designed the experiment) knows about some controls, for which it is already known what they should be doing; or is able to test some of the results using an independent assay. The dimness of your arrays however suggests that there could be a problem with data quality that is not easy to fix by data analysis. Best wishes Wolfgang Il giorno Dec 7, 2012, alle ore 10:44 AM, Peter Davidsen <pkdavidsen at="" gmail.com=""> ha scritto: > Dear List, > > I'm analysing some one-color microarray data generated using a custom > designed Agilent array (their 8 x 60K platform). > When I compare control samples to treated ones most (i.e. >80%) of the > differentially expressed transcripts are up-regulated. This pronounced > up-regulation is independent of type of treatment. > I have never before experienced such a quantitative difference in the > number of up- and down-regulated transcripts. Furthermore, I have > tried to analyse relevant datasets in the GEO that mimics my study > design in terms of treatment regime, duration of treatment ect. These > analyses--all in closely related species--suggest that the fraction of > up and down-regulated transcripts should be roughly the same. > The QC reports generated by the Agilent Feature Extraction Software > indicate that the data quality should be fine. Also a few basic > boxplot before and after normalization haven't raised my suspicion. I > do, however, find that the median signal intensity for each sample is > significantly lower than what I've seen in the past with the same > platform (although targeted against another related species). > I have tried to normalize my data using both quantile and vsn, > respectively, with similar result. I have also tried to filter my > dataset using different intensity filters - again with similar result. > And finally, I also tried using both limma and SAMR for the > statistics. > > Have anyone by any chance experienced something similar, and how did > you deal with this issue of many siggenes going in one direction? > > Many thanks, > Peter > > _______________________________________________ > 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
ADD REPLYlink written 6.4 years ago by Wolfgang Huber13k
Dear Peter did you already generate a quality report with 'arrayQualityMetrics'? Also, I assume you (or the biologist who designed the experiment) knows about some controls, for which it is already known what they should be doing; or is able to test some of the results using an independent assay. The dimness of your arrays however suggests that there could be a problem with data quality that is not easy to fix by data analysis. Best wishes Wolfgang Il giorno Dec 7, 2012, alle ore 10:44 AM, Peter Davidsen <pkdavidsen at="" gmail.com=""> ha scritto: > Dear List, > > I'm analysing some one-color microarray data generated using a custom > designed Agilent array (their 8 x 60K platform). > When I compare control samples to treated ones most (i.e. >80%) of the > differentially expressed transcripts are up-regulated. This pronounced > up-regulation is independent of type of treatment. > I have never before experienced such a quantitative difference in the > number of up- and down-regulated transcripts. Furthermore, I have > tried to analyse relevant datasets in the GEO that mimics my study > design in terms of treatment regime, duration of treatment ect. These > analyses--all in closely related species--suggest that the fraction of > up and down-regulated transcripts should be roughly the same. > The QC reports generated by the Agilent Feature Extraction Software > indicate that the data quality should be fine. Also a few basic > boxplot before and after normalization haven't raised my suspicion. I > do, however, find that the median signal intensity for each sample is > significantly lower than what I've seen in the past with the same > platform (although targeted against another related species). > I have tried to normalize my data using both quantile and vsn, > respectively, with similar result. I have also tried to filter my > dataset using different intensity filters - again with similar result. > And finally, I also tried using both limma and SAMR for the > statistics. > > Have anyone by any chance experienced something similar, and how did > you deal with this issue of many siggenes going in one direction? > > Many thanks, > Peter > > _______________________________________________ > 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
ADD REPLYlink written 6.4 years ago by Wolfgang Huber13k
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