shorth function and Affymetrix Hugene
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@juan-fernandez-tajes-5273
Last seen 9.7 years ago
Dear List I´m trying to reproduce an analysis (a transcriptomic analysis) that I found in a research paper. The methods section says: "After normalization an expression threshold for each cell line was calculated to get rid of low intensity probes that can be considered technical noise. First, probe sets were sorted by increasing expression value. For each probe set a t-test was performed to evaluate the differential expression between this probe set and the median value of the probe sets with less expression values" I´ve used the shorth function in R in order to reproduce this analysis, I would like to know if you consider that is a appropriate method. My data (dat) is called data.exprs from Affymetrix Hugene 1.1 st array. After normalization using RMA I executed the following code to obtain the less expressed probe sets: med.exp <- rowMedians(exprs(dat)) med <- shorth(med.exprs) And then, I calculated a t.test for comparing each probe sets with the *med* value tt <- rep(0.8256, 23) ## 0.8256 is the value of shorth(med.exprs) and I have 23 samples result.pvalue <- sapply(1:nrow(myAB1_rma.exprs), function(i) t.test(i, tt)) Could be this approach valid? Many thanks in advance, Juan --------------------------------------------------------------- Juan Fernandez Tajes, ph. D Grupo XENOMAR Departamento de Biología Celular y Molecular Facultad de Ciencias-Universidade da Coruña Tlf. +34 981 167000 ext 2030 e-mail: jfernandezt@udc.es ---------------------------------------------------------------- [[alternative HTML version deleted]]
Normalization probe Normalization probe • 684 views
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