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Question: DESeq2 rna seq analysis
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3.0 years ago by
gv30
United States
gv30 wrote:

Hi,

I am trying to use DESeq2 package. I have some question's related to that.

1. DESeq2 manual say's in MAplot function  Points will be colored red if the adjusted p value is less than 0.1. Can i change the value to 0.05. If yes how??

2. Also point which falls out of the window are plotted as open triangles. In the file what should I see in the column of adjusted p value. Will it be NA??

Thanks

Varun

modified 3.0 years ago by Steve Lianoglou12k • written 3.0 years ago by gv30
1
3.0 years ago by
Denali
Steve Lianoglou12k wrote:

1. DESeq2 manual say's in MAplot function  Points will be colored red if the adjusted p value is less than 0.1. Can i change the value to 0.05. If yes how??

In the help page you get from ?plotMA function for a DESeqDataSet, you'll see that there is an alpha parameter you can tweak which sets the significance threshold to plot.

2. Also point which falls out of the window are plotted as open triangles. In the file what should I see in the column of adjusted p value. Will it be NA??

The position on the y-axis is defined by the log fold change of the gene expression, what you'll see in the related adjusted p value column is not a function of the fold change, but rather its p-value, so there isn't a real "direct" answer to your question (although on average you'd expect high logFC's with low p-values, but it's not always the case), if you know what I mean?

You should note that NA pvalues come from two sources (if you've run DESeq2 w/o any tweaks):

1. From genes that have outlier expression in >= 1 sample; or
2. From genes that have been filtered out by the "independent filtering" mojo DESeq does by default to reduce the multipe-testing burden via removing genes that have a small chance of being differentially expressed
ADD COMMENTlink modified 3.0 years ago • written 3.0 years ago by Steve Lianoglou12k

So in the file, how can i distinguish red points with red triangles which are outliers?? THis is because I need to know which genes are really differentially expressed and is not an outlier

ADD REPLYlink modified 3.0 years ago • written 3.0 years ago by gv30

Which file?

The object you get from calling results has columns for the log2 fold change as well as the adjusted pvalue -- those two columns together will etll you which ones are "really" differentially expressed, no? If there are NA's in the adjusted p values, these may or may not be outliers -- you will have to go back to your data an inspect it, the plotCounts function will be helpful here.

Ok I will look at the plotCounts function, it's usage and get back to you. Yes I was referring to the object generated after applying results function

res<-results(dds)
res<-res[order(res\$padj),]

@Steve: So I looked at plotCounts function and plotted it for some genes. What should I look for in them so as to distinguish outliers from other differentially expressed gene.