Differential Expression using simpleaffy R package
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@agaz-hussain-wani-7620
Last seen 6.0 years ago
India

I am interested to perform differential expression on affymetrix gene expression data by using simpleaffy package. I use 

significant <- pairwise.filter(results,min.exp=log2(10),min.exp.no=2, fc=log2(1.5),
                                     tt= 0.05)

to select the gene  showing fold change of greater than 1.5 and having t.test of 0.05 or better. However i get the results with fold change less than 1.5 also. The results are shown below. Please let me know if i am going wrong . Help appreciated, thanks

rowname            fc.significant.
1 1552264_a_at      -1.0039565
2 1552283_s_at       2.5965465
3   1552291_at      -2.1498897
4 1552316_a_at       2.0454884
5   1552365_at       3.0642035
6 1552378_s_at      -0.7997985
r differential gene expression • 1.2k views
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@james-w-macdonald-5106
Last seen 48 minutes ago
United States

Please note that log2(1.5) = 0.585
 

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Oh, a real mistake. Thanks for making out. But in simpleaffy they claim log2(1.5) as fold change greater than 1.5, how it is??.

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The idea is that you want to filter to only keep genes that show support for a 1.5x change between conditions. The numbers that are consumed by fc are in log2 space, and so are the fold change values that are reported, so you convert a 1.5x change on the "natural scale" to log2 scale.

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