Contrasts in Deseq2
1
0
Entering edit mode
Pablo • 0
@97d1a63c
Last seen 4 days ago
Brazil

I have a question regarding contrasts in a multi-factorial design in Deseq2. I have a design that have 1 factor (Inoculation) with two levels (Inoc or No.Inoc) and another factor (Crop) with 4 levels (fallow - Fa, corn - Co, Mix 1 - M1, and mix 5 - M5). I set No.Inoc and Fa as the reference levels for their respective factors.

The design was the following:

design(degtreatMF) <- formula(~ Crop + Inoculation + Crop:Inoculation)
degtreatMF <- DESeq(degtreatMF, fitType="local")

And I got the following coeficients:


resultsNames(degtreatMF)

[1] "Intercept"                   "Crop_Co_vs_Fa"              
[3] "Crop_M1_vs_Fa"               "Crop_M5_vs_Fa"              
[5] "Inoculation_Inoc_vs_No.Inoc" "CropCo.InoculationInoc"     
[7] "CropM1.InoculationInoc"      "CropM5.InoculationInoc"

I need to find the following contrasts:

Co and Inoc vs Co and No.Inoc

M1 and Inoc vs M1 and No.Inoc

M5 and Inoc vs M5 and No.Inoc

Fa and Inoc vs Fa and No.Inoc

Now if I understood correctly, my intercept is Fa and No.Inoc and can be represented as c(1,0,0,0,0,0,0,0) while the others would be:

Fa and Inoc: (1,0,0,0,1,0,0,0)

Co and No.Inoc: (1,1,0,0,0,0,0,0)

Co and Inoc: (1,1,0,0,1,1,0,0)

M1 and No.Inoc: (1,0,1,0,0,0,0,0)

M1 and Inoc: (1,0,1,0,1,0,1,0)

M5 and No.Inoc: (1,0,0,1,0,0,0,0)

M5 and Inoc: (1,0,0,1,1,0,0,1)

Which means that I need to specifiy the following contrasts to get my expected results:

Co and Inoc vs Co and No.Inoc: c(0,0,0,0,1,1,0,0)

M1 and Inoc vs M1 and No.Inoc: c(0,0,0,0,1,0,1,0)

M5 and Inoc vs M5 and No.Inoc: c(0,0,0,0,1,0,0,1)

Fa and Inoc vs Fa and No.Inoc c(0,0,0,0,1,0,0,0)

Is that accurate?

DESeq2 • 115 views
ADD COMMENT
1
Entering edit mode
@mikelove
Last seen 4 days ago
United States

I have to limit my time on the support site to issues relating to the software. For questions about experimental design, statistical analysis and interpretation, I recommend to work with a local statistician or someone familiar with linear models in R.

ADD COMMENT

Login before adding your answer.

Traffic: 344 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6