Entering edit mode
I am doing DESeq with three continuous variables. The dataset containing the following information.
sample group Age BMI FBG samplea A 55 22 80 sampleb B 60 20 97 samplec C 52 25 102 sampled D 45 35 96
I want to see differential genes expression by group, Age, BMI, and FBG level.
Here is my design:
dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ group + age + BMI + FBG )
However, I am not sure how to extract the result data for age, BMI and FBG to see the up and down-regulated genes.
I would use contrast if they were categorical but they are continues. Please forward your valuable comments.
Thanks for your help!
Thanks for your answer. But still I have Problems after I did DESeq a kind of message was pop-up" ----- the design formula contains one or more numeric variables with integer values, specifying a model with increasing fold change for higher values…….." Then, i did scaling and centering as follow: dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ group + scale(age, center =T) + scale(BMI, center =T + scale(FBG, center=T ). However, the message still comes. So I may ask how to scale and center this continues variables in the design? How I can apply cut() in the design? Lastly, to see the genes explained by age, BMI, and FBG, do you think I must run DESeq separately? like: ddsBMI <- dds DESeq(ddsBMI)
ddsage <- dds DESeq(ddsage) and etc
Thank you so much!
I moved your post from an "Answer" to a "Comment" to make the thread easier to follow.
See perhaps my other recent reply on the forum to this question.