I applied the R package DEXSeq to an RNAseq data set and wrote the results to a HTML file. Comparing the expression plot and log2 fold change in the corresponding result table, the log2foldchange values on the table seem conservative relative to those shown on the plot. Could anyone help me to understand this discrepancy?
For example, in an analysis of the pasilla sample data set, exon 10 in FBgn0010909 looks to be ~4 fold lower in the treated data:
but in the results table it has a log2foldchange value of 0.64:
The following commands were put in to do the analysis:
library("DEXSeq")
library("pasilla")
data("pasillaExons", package="pasilla")
pasillaExons <- estimateSizeFactors(pasillaExons)
pasillaExons <- estimateDispersions(pasillaExons)
pasillaExons <- fitDispersionFunction(pasillaExons)
pasillaExons <- testForDEU( pasillaExons,nCore=8)
pasillaExons <- estimatelog2FoldChanges( pasillaExons )
ecs1 <- pasillaExons
#
formuladispersion <- count ~ sample + ( condition + type ) * exon
pasillaExons <- estimateDispersions( pasillaExons, formula = formuladispersion )
pasillaExons <- fitDispersionFunction(pasillaExons)
formula0 <- count ~ sample + type * exon + condition
formula1 <- count ~ sample + type * exon + condition * I(exon == exonID)
pasillaExons <- testForDEU( pasillaExons, formula0=formula0, formula1=formula1,nCore=8)
pasillaExons <- estimatelog2FoldChanges( pasillaExons )
ecs2 <- pasillaExons
Then the results were written by:
DEXSeqHTML( ecs1, FDR=0.1, color=c("#FF000080", "#0000FF80"),path="/agf/illum/ID0095DEU_2f847c24e9311da6/model1/",file="pasilla_DEU_res.html")
#
DEXSeqHTML( ecs2, FDR=0.1, color=c("#FF000080", "#0000FF80"),path="/agf/illum/ID0095DEU_2f847c24e9311da6/model2",file="pasilla_DEU_res.html")
The results are available from:
Thanks in advance if anyone can give a reasonable explanation.
For example, in an analysis of the pasilla sample data set, exon 10 in FBgn0010909 looks to be ~4 fold lower in the treated data:
but in the results table it has a log2foldchange value of 0.64:
The following commands were put in to do the analysis:
library("DEXSeq")
library("pasilla")
data("pasillaExons", package="pasilla")
pasillaExons <- estimateSizeFactors(pasillaExons)
pasillaExons <- estimateDispersions(pasillaExons)
pasillaExons <- fitDispersionFunction(pasillaExons)
pasillaExons <- testForDEU( pasillaExons,nCore=8)
pasillaExons <- estimatelog2FoldChanges( pasillaExons )
ecs1 <- pasillaExons
#
formuladispersion <- count ~ sample + ( condition + type ) * exon
pasillaExons <- estimateDispersions( pasillaExons, formula = formuladispersion )
pasillaExons <- fitDispersionFunction(pasillaExons)
formula0 <- count ~ sample + type * exon + condition
formula1 <- count ~ sample + type * exon + condition * I(exon == exonID)
pasillaExons <- testForDEU( pasillaExons, formula0=formula0, formula1=formula1,nCore=8)
pasillaExons <- estimatelog2FoldChanges( pasillaExons )
ecs2 <- pasillaExons
Then the results were written by:
DEXSeqHTML( ecs1, FDR=0.1, color=c("#FF000080", "#0000FF80"),path="/agf/illum/ID0095DEU_2f847c24e9311da6/model1/",file="pasilla_DEU_res.html")
#
DEXSeqHTML( ecs2, FDR=0.1, color=c("#FF000080", "#0000FF80"),path="/agf/illum/ID0095DEU_2f847c24e9311da6/model2",file="pasilla_DEU_res.html")
The results are available from:
Thanks in advance if anyone can give a reasonable explanation.
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