Multi-factor Analysis in DeSEQ2
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pthom010 • 0
@pthom010-23694
Last seen 4 months ago
United States

I have a 22-day time course experiment I conducted with two plant genotypes and five time points (0, 1, 7, 14, 22 dpi). I have manged to successfully complete some basic analysis of my RNAseq data. I now wanted to do some multi factor analysis but wasn't sure where to stat. Here is the layout of my samples:

RA - resistant, 0 dpi RB - resistant, 1dpi RC - resistant, 7dpi RD - resistant, 14 dpi RE - resistant, 22 dpi

SA - susceptible, 0 dpi SB - susceptible, 1 dpi SC - susceptible, 7 dpi SD - susceptible, 14 dpi SE - susceptible, 22 dpi

Here are the analyses I have done so far:

RA-SA RB-SB RC-RC RD-SD RE-SE

RA-RB RA-RC RA-RD RA-RE

SA-SB SA-SC SA-SD SA-SE

I am uploading my data using the tximport function. I have designed my sample file like so:

sample

         timepoint treatment genotype
S1A_rep1         0        SA        S
S1A_rep2         0        SA        S
S1A_rep3         0        SA        S
S1B_rep1         1        SB        S
S1B_rep2         1        SB        S
S1B_rep3         1        SB        S
S1C_rep1         7        SC        S
S1C_rep2         7        SC        S
S1C_rep3         7        SC        S
S1D_rep1        14        SD        S
S1D_rep2        14        SD        S
S1D_rep3        14        SD        S
S1E_rep1        22        SE        S
S1E_rep2        22        SE        S
S1E_rep3        22        SE        S
R1A_rep1         0        RA        R
R1A_rep2         0        RA        R
R1A_rep3         0        RA        R
R1B_rep1         1        RB        R
R1B_rep2         1        RB        R
R1B_rep3         1        RB        R
R1C_rep1         7        RC        R
R1C_rep2         7        RC        R
R1C_rep3         7        RC        R
R1D_rep1        14        RD        R
R1D_rep2        14        RD        R
R1D_rep3        14        RD        R
R1E_rep1        22        RE        R
R1E_rep2        22        RE        R
R1E_rep3        22        RE        R

The specific four comparisons I want to make are the following:

  1. (RB - SB) - (RA - SA) (compare RB and SB, then compare that to RA and SA, compared)
  2. (RE + SE) - (RA + SA)
  3. (RE + RD) - (RC + RB)
  4. [(RE + RD) - (RC + RB)] - [(SE + SD) - (SC - SB)] (compare the early vs late response of the R plants to that of the susceptible)

Do I need to change my sample object to facilitate these comparisons or is there another piece of code I should be using?

tximport R tximportData RNASeq DESeq2 • 178 views
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Entering edit mode
@mikelove
Last seen 6 hours ago
United States

You can use a single design and then results() with the contrast argument to perform the comparisons.

I cannot offer statistical design support here. Due to time restrictions, I have to limit myself to software-related questions only, whereas choice of statistical design and interpretations of contrasts is really statistical consultation. I recommend to partner with a statistician or someone familiar with linear models for the latter.

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