I used to perform the normalization of microarray data from Affymatrix platform using RMA method. However the processed data tend to be smaller and the divergence between probes also become smaller. I know the reason is the logarithm. I wanna know the reduction of relative value of probes may affect the discovering the differentiated expressed genes. Or should I use the ratio between value before log?
•
written
by
Jonathan Hsu •
1 answer
When you take logs of expression values, you need to remember that the value obtained is now in "log base N". So for example if you used log base 2, a difference between values of 1 is actually a 2x difference, a difference between values of 2 = 4x difference and so on. So the smaller ratio between probes under different conditions when logged is not a "bad" thing; it's just a different way to express the numbers.
If there is differential expression, the test used to find it (e.g. p-values or something better, such as SAM) will take the magnitude of the expression values into account. So don't worry if it "looks small" to your eyes.
Log in to answer this question.
-
microarray analysis - gene upregulation/downregulation
written by bioinformatics •
-
Microarray DEG scatterplot
written by bioinformatics •
-
Microarray DEG analysis scatterplot
written by bioinformatics •
-
how to find consensus modules between 2 datasets by different platform through WGCNA
written by modarzi
-
Normalization based on housekeeping genes
written by elenichri •
-
How to deal with multiple probes for same gene while obtaining the co-expressed genes
written by ancient_learner
-
Difference Between Rma Analysis Of Cel Files And Data From Geoquery Of Array Data
written by J.F.Jiang
-
Tutorial: Analysing Microarray Data In Bioconductor
written by Obi Griffith
-
Problem Understanding Affymetrix Gene Expression Data
written by Pi •
-
Background Expression Level With Affymetrix St Arrays And Rma
written by David Quigley
