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@marcelo-luiz-de-laia-377
Last seen 10.2 years ago
Hi everyone. I have the following layout: SlideNamber FileNameCy3 FileNameCy5 Cy3 Cy5 1 lamina1_1_selected.txt lamina1_0_selected.txt BCYE XDM 2 lamina2_1_selected.txt lamina2_0_selected.txt XDM BCYE 3 lamina3_1_selected.txt lamina3_0_selected.txt XDM BCYE And I have these results (fictitious): .Field Meta.Row Meta.Column Row 4432 XDM/BCYE 3 2 25 2955 XDM/BCYE 2 2 28 5203 XDM/BCYE 4 1 25 4510 XDM/BCYE 3 2 28 1533 XDM/BCYE 1 2 32 4562 XDM/BCYE 3 2 31 5137 XDM/BCYE 4 1 23 Column Gene.ID M t P.Value B 16 SemP01 -3.00 -61.01 0.00 7.96 3 ty0012 -2.83 -51.54 0.00 7.78 19 SemP08 -2.73 -51.46 0.00 7.71 22 SemP12 -3.55 -51.35 0.00 7.62 21 ty2196 -3.97 -41.90 0.00 5.68 2 SemP38 -2.60 -41.70 0.00 5.48 1 ty0559 1.66 41.09 0.00 5.03 Which is the interpretation for the gene 4432? Inside of this layout it was up or down regulated? And the gene 5237? Was it up or down? Thanks very much Marcelo ---
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@james-wettenhall-153
Last seen 10.2 years ago
On Thu, 23 Oct 2003, Marcelo Luiz de Laia wrote: > Hi everyone. > > I have the following layout: > > SlideNamber FileNameCy3 FileNameCy5 Cy3 Cy5 > 1 lamina1_1_selected.txt lamina1_0_selected.txt BCYE XDM > 2 lamina2_1_selected.txt lamina2_0_selected.txt XDM BCYE > 3 lamina3_1_selected.txt lamina3_0_selected.txt XDM BCYE > > And I have these results (fictitious): > > .Field Meta.Row Meta.Column Row > 4432 XDM/BCYE 3 2 25 > 2955 XDM/BCYE 2 2 28 > 5203 XDM/BCYE 4 1 25 > 4510 XDM/BCYE 3 2 28 > 1533 XDM/BCYE 1 2 32 > 4562 XDM/BCYE 3 2 31 > 5137 XDM/BCYE 4 1 23 > > Column Gene.ID M t P.Value B > 16 SemP01 -3.00 -61.01 0.00 7.96 > 3 ty0012 -2.83 -51.54 0.00 7.78 > 19 SemP08 -2.73 -51.46 0.00 7.71 > 22 SemP12 -3.55 -51.35 0.00 7.62 > 21 ty2196 -3.97 -41.90 0.00 5.68 > 2 SemP38 -2.60 -41.70 0.00 5.48 > 1 ty0559 1.66 41.09 0.00 5.03 > > Which is the interpretation for the gene 4432? Inside of this layout it was > up or down regulated? > > And the gene 5237? Was it up or down? > > Thanks very much > > Marcelo Marcelo, Given that you have a toptable, I assume that at some stage you were successful in specifying a design matrix. A quick look at your data suggests design=c(1,-1,-1), meaning that you are estimating one parameter (for each gene) which is log2(XDM/BCYE). A gene such as 4432 which has a negative M value in the toptable and negative moderated t statistic is down-regulated in XDM compared with BCYE with a log2 fold change given by the M value. A (moderated) t statistic which is large in magnitude means a high confidence of differential expression because there is good consistency between replicates as well as a significant log2 fold change for that gene. 5137 is upregulated in XDB compared with BCYE with high confidence (for similar reasons). The B statistic estimates the log odds of differential expression of a gene given its M value. So if it is greater than zero, then you have more than a 50/50 chance that the gene is differentially expressed. Hope This Helps, James
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