Erika Melissari wrote: > Dear Jim, > > thank you for your always usefull explanations. > If we observe a gene up-regulated in mutant "class" and also in the wt > "class" but the extent of this up-regulation is different and > statistically significant, we then should detect this gene as > differentially expressed in this contrast...is correct? If I understand your question correctly, then yes. You can have genes up-regulated in both wt and mutant, but less so in one than the other. If the difference in up-regulation is large enough and the variability within groups is small enough then you should get a significant interaction. Best, Jim > > >> Not four arrays, but four treatment/sample combinations. You will need >> replication to compute this contrast. >> > > Yes, I know that if I increase the number of contrasts I need more degrees > of freedom to compute the statistics. I referred only to direct > comparison. If I have more samples and perform a large reference design > can I compute this interaction term the same? > thank you > > Erika > >> Hi Erika, >> >> Erika Melissari wrote: >>> Dear bioconductor list, >>> >>> I am studing the Weaver experiment example of LIMMA manual and I am in a >>> maze about the biological meaning of interaction term present among the >>> contrasts. >>> I did not manage to understend what kind of differentially expressed >>> gene >>> this contrast takes-out. >> In this experiment we can look at genes that change between the two time >> points in the mutant samples, or that change between the two time points >> in the wild type samples. In addition, we might be interested in those >> genes that react differently in the two sample types. In other words, a >> particular gene might increase expression in the wild type samples, but >> actually decrease expression in the mutant samples. >> >> This third comparison is known as an interaction. >> >>> The interaction contrast is: >>> >>> (P21mt-P11mt)-(P21wt-P11wt) >> Correct. So using our example from above, the first term will be >> negative (since the expression level went down in mutant samples). The >> second term will be positive, since the expression went up over time in >> the wild type samples, but since we subtract, we end up with a >> (possibly) large negative number. >> >> The same will be true of any scenario you can envision where the mutant >> and wild type samples react differently to the incubation time. Another >> example would be the situation where the mutant samples were >> up-regulated at 21 hours, but the wild type samples were unaffected. In >> this case you can see that we might have a large value for this contrast. >> >> However, if both wild type and mutant samples were up-regulated >> approximately the same amount, the resulting value would be very close >> to zero. >> >>> The first bracket takes-out the differentially expressed genes between >>> the >>> mutant subjects at two different time points(21 and 11 minutes) and the >>> second bracket those between the wild-type subject at the same different >>> time points. >>> ..but what differentially expressed genes takes-out the global >>> interaction >>> contrast? >>> >>> In order to evaluate an interaction do I need absolutely the four arrays >>> in direct comparison done in this example? >> Not four arrays, but four treatment/sample combinations. You will need >> replication to compute this contrast. >> >> Best, >> >> Jim >> >> >>> Thank you very much for any explaination >>> >>> Erika >>> >>> _______________________________________________ >>> 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 >> -- >> James W. MacDonald, M.S. >> Biostatistician >> Douglas Lab >> University of Michigan >> Department of Human Genetics >> 5912 Buhl >> 1241 E. Catherine St. >> Ann Arbor MI 48109-5618 >> 734-615-7826 >> > > > > > Erika Melissari > > _______________________________________________ > 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 -- James W. MacDonald, M.S. Biostatistician Douglas Lab University of Michigan Department of Human Genetics 5912 Buhl 1241 E. Catherine St. Ann Arbor MI 48109-5618 734-615-7826