DESeq2 analysis of multifactorial RNAseq experiment
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Entering edit mode
@victor-chano-20932
Last seen 13 months ago
Madrid (UPM)

Hi,

I am trying to perform differential gene expression analysis with a multifactorial experiment of plant responses during fungi infection, and I have some concerns about how to address the analysis. This experiment includes a full design with 2 conditions (control and inoculated plants), time series (6, 24, 72 and 144 hours after infection), two responses (local and systemic, both from same plant), and three genotypes differentiated by their level of tolerance or susceptibility to the infection. Four biological replicates were collected for each sampling point (2x4x2x3x4 = 192 samples). Reading the vignettes, the ?results, and other manuals and forums like this one, I am not reaching a clear option for my design (of course, english+statistical language may difficult the understanding).

The full colData is (sorry, it is too long, but I prefer to show you the complete design):

> print(coldata)
            genotype plant condition    time  response  
A.1_C_L_6      "A"   "1"   "control"    "6"   "local"   
A.3_C_L_6      "A"   "3"   "control"    "6"   "local"   
A.36_C_L_6     "A"   "36"  "control"    "6"   "local"   
A.47_C_L_6     "A"   "47"  "control"    "6"   "local"   
A.4_C_L_24     "A"   "4"   "control"    "24"  "local"   
A.20_C_L_24    "A"   "20"  "control"    "24"  "local"   
A.22_C_L_24    "A"   "22"  "control"    "24"  "local"   
A.43_C_L_24    "A"   "43"  "control"    "24"  "local"   
A.2_C_L_72     "A"   "2"   "control"    "72"  "local"   
A.11_C_L_72    "A"   "11"  "control"    "72"  "local"   
A.34_C_L_72    "A"   "34"  "control"    "72"  "local"   
A.42_C_L_72    "A"   "42"  "control"    "72"  "local"   
A.8_C_L_144    "A"   "8"   "control"    "144" "local"   
A.21_C_L_144   "A"   "21"  "control"    "144" "local"   
A.37_C_L_144   "A"   "37"  "control"    "144" "local"   
A.39_C_L_144   "A"   "39"  "control"    "144" "local"   
A.13_I_L_6     "A"   "1"   "control"    "6"   "systemic"
A.15_I_L_6     "A"   "3"   "control"    "6"   "systemic"
A.23_I_L_6     "A"   "36"  "control"    "6"   "systemic"
A.50_I_L_6     "A"   "47"  "control"    "6"   "systemic"
A.16_I_L_24    "A"   "4"   "control"    "24"  "systemic"
A.33_I_L_24    "A"   "20"  "control"    "24"  "systemic"
A.41_I_L_24    "A"   "22"  "control"    "24"  "systemic"
A.44_I_L_24    "A"   "43"  "control"    "24"  "systemic"
A.18_I_L_72    "A"   "2"   "control"    "72"  "systemic"
A.31_I_L_72    "A"   "11"  "control"    "72"  "systemic"
A.46_I_L_72    "A"   "34"  "control"    "72"  "systemic"
A.49_I_L_72    "A"   "42"  "control"    "72"  "systemic"
A.9_I_L_144    "A"   "8"   "control"    "144" "systemic"
A.12_I_L_144   "A"   "21"  "control"    "144" "systemic"
A.24_I_L_144   "A"   "37"  "control"    "144" "systemic"
A.45_I_L_144   "A"   "39"  "control"    "144" "systemic"
A.1_C_S_6      "A"   "13"  "inoculated" "6"   "local"   
A.3_C_S_6      "A"   "15"  "inoculated" "6"   "local"   
A.36_C_S_6     "A"   "23"  "inoculated" "6"   "local"   
A.47_C_S_6     "A"   "50"  "inoculated" "6"   "local"   
A.4_C_S_24     "A"   "16"  "inoculated" "24"  "local"   
A.20_C_S_24    "A"   "33"  "inoculated" "24"  "local"   
A.22_C_S_24    "A"   "41"  "inoculated" "24"  "local"   
A.43_C_S_24    "A"   "44"  "inoculated" "24"  "local"   
A.2_C_S_72     "A"   "18"  "inoculated" "72"  "local"   
A.11_C_S_72    "A"   "31"  "inoculated" "72"  "local"   
A.34_C_S_72    "A"   "46"  "inoculated" "72"  "local"   
A.42_C_S_72    "A"   "49"  "inoculated" "72"  "local"   
A.8_C_S_144    "A"   "9"   "inoculated" "144" "local"   
A.21_C_S_144   "A"   "12"  "inoculated" "144" "local"   
A.37_C_S_144   "A"   "24"  "inoculated" "144" "local"   
A.39_C_S_144   "A"   "45"  "inoculated" "144" "local"   
A.13_I_S_6     "A"   "13"  "inoculated" "6"   "systemic"
A.15_I_S_6     "A"   "15"  "inoculated" "6"   "systemic"
A.23_I_S_6     "A"   "23"  "inoculated" "6"   "systemic"
A.50_I_S_6     "A"   "50"  "inoculated" "6"   "systemic"
A.16_I_S_24    "A"   "16"  "inoculated" "24"  "systemic"
A.33_I_S_24    "A"   "33"  "inoculated" "24"  "systemic"
A.41_I_S_24    "A"   "41"  "inoculated" "24"  "systemic"
A.44_I_S_24    "A"   "44"  "inoculated" "24"  "systemic"
A.18_I_S_72    "A"   "18"  "inoculated" "72"  "systemic"
A.31_I_S_72    "A"   "31"  "inoculated" "72"  "systemic"
A.46_I_S_72    "A"   "46"  "inoculated" "72"  "systemic"
A.49_I_S_72    "A"   "49"  "inoculated" "72"  "systemic"
A.9_I_S_144    "A"   "9"   "inoculated" "144" "systemic"
A.12_I_S_144   "A"   "12"  "inoculated" "144" "systemic"
A.24_I_S_144   "A"   "24"  "inoculated" "144" "systemic"
A.45_I_S_144   "A"   "45"  "inoculated" "144" "systemic"
B.8_C_L_6    "B" "8"   "control"    "6"   "local"   
B.24_C_L_6   "B" "24"  "control"    "6"   "local"   
B.29_C_L_6   "B" "29"  "control"    "6"   "local"   
B.38_C_L_6   "B" "38"  "control"    "6"   "local"   
B.5_C_L_24   "B" "5"   "control"    "24"  "local"   
B.6_C_L_24   "B" "6"   "control"    "24"  "local"   
B.7_C_L_24   "B" "7"   "control"    "24"  "local"   
B.43_C_L_24  "B" "43"  "control"    "24"  "local"   
B.3_C_L_72   "B" "3"   "control"    "72"  "local"   
B.11_C_L_72  "B" "11"  "control"    "72"  "local"   
B.41_C_L_72  "B" "41"  "control"    "72"  "local"   
B.47_C_L_72  "B" "47"  "control"    "72"  "local"   
B.10_C_L_144 "B" "10"  "control"    "144" "local"   
B.27_C_L_144 "B" "27"  "control"    "144" "local"   
B.40_C_L_144 "B" "40"  "control"    "144" "local"   
B.42_C_L_144 "B" "42"  "control"    "144" "local"   
B.18_I_L_6   "B" "8"   "control"    "6"   "systemic"
B.21_I_L_6   "B" "24"  "control"    "6"   "systemic"
B.33_I_L_6   "B" "29"  "control"    "6"   "systemic"
B.49_I_L_6   "B" "38"  "control"    "6"   "systemic"
B.13_I_L_24  "B" "5"   "control"    "24"  "systemic"
B.17_I_L_24  "B" "6"   "control"    "24"  "systemic"
B.30_I_L_24  "B" "7"   "control"    "24"  "systemic"
B.45_I_L_24  "B" "43"  "control"    "24"  "systemic"
B.15_I_L_72  "B" "3"   "control"    "72"  "systemic"
B.28_I_L_72  "B" "11"  "control"    "72"  "systemic"
B.32_I_L_72  "B" "41"  "control"    "72"  "systemic"
B.44_I_L_72  "B" "47"  "control"    "72"  "systemic"
B.19_I_L_144 "B" "10"  "control"    "144" "systemic"
B.26_I_L_144 "B" "27"  "control"    "144" "systemic"
B.46_I_L_144 "B" "40"  "control"    "144" "systemic"
B.50_I_L_144 "B" "42"  "control"    "144" "systemic"
B.8_C_S_6    "B" "18"  "inoculated" "6"   "local"   
B.24_C_S_6   "B" "21"  "inoculated" "6"   "local"   
B.29_C_S_6   "B" "33"  "inoculated" "6"   "local"   
B.38_C_S_6   "B" "49"  "inoculated" "6"   "local"   
B.5_C_S_24   "B" "13"  "inoculated" "24"  "local"   
B.6_C_S_24   "B" "17"  "inoculated" "24"  "local"   
B.7_C_S_24   "B" "30"  "inoculated" "24"  "local"   
B.43_C_S_24  "B" "45"  "inoculated" "24"  "local"   
B.3_C_S_72   "B" "15"  "inoculated" "72"  "local"   
B.11_C_S_72  "B" "28"  "inoculated" "72"  "local"   
B.41_C_S_72  "B" "32"  "inoculated" "72"  "local"   
B.47_C_S_72  "B" "44"  "inoculated" "72"  "local"   
B.10_C_S_144 "B" "19"  "inoculated" "144" "local"   
B.27_C_S_144 "B" "26"  "inoculated" "144" "local"   
B.40_C_S_144 "B" "46"  "inoculated" "144" "local"   
B.42_C_S_144 "B" "50"  "inoculated" "144" "local"   
B.18_I_S_6   "B" "18"  "inoculated" "6"   "systemic"
B.21_I_S_6   "B" "21"  "inoculated" "6"   "systemic"
B.33_I_S_6   "B" "33"  "inoculated" "6"   "systemic"
B.49_I_S_6   "B" "49"  "inoculated" "6"   "systemic"
B.13_I_S_24  "B" "13"  "inoculated" "24"  "systemic"
B.17_I_S_24  "B" "17"  "inoculated" "24"  "systemic"
B.30_I_S_24  "B" "30"  "inoculated" "24"  "systemic"
B.45_I_S_24  "B" "45"  "inoculated" "24"  "systemic"
B.15_I_S_72  "B" "15"  "inoculated" "72"  "systemic"
B.28_I_S_72  "B" "28"  "inoculated" "72"  "systemic"
B.32_I_S_72  "B" "32"  "inoculated" "72"  "systemic"
B.44_I_S_72  "B" "44"  "inoculated" "72"  "systemic"
B.19_I_S_144 "B" "19"  "inoculated" "144" "systemic"
B.26_I_S_144 "B" "26"  "inoculated" "144" "systemic"
B.46_I_S_144 "B" "46"  "inoculated" "144" "systemic"
B.50_I_S_144 "B" "50"  "inoculated" "144" "systemic"
C.4_C_L_6      "C"   "4"   "control"    "6"   "local"   
C.6_C_L_6      "C"   "6"   "control"    "6"   "local"   
C.7_C_L_6      "C"   "7"   "control"    "6"   "local"   
C.37_C_L_6     "C"   "37"  "control"    "6"   "local"   
C.1_C_L_24     "C"   "1"   "control"    "24"  "local"   
C.11_C_L_24    "C"   "11"  "control"    "24"  "local"   
C.19_C_L_24    "C"   "19"  "control"    "24"  "local"   
C.42_C_L_24    "C"   "42"  "control"    "24"  "local"   
C.2_C_L_72     "C"   "2"   "control"    "72"  "local"   
C.9_C_L_72     "C"   "9"   "control"    "72"  "local"   
C.27_C_L_72    "C"   "27"  "control"    "72"  "local"   
C.41_C_L_72    "C"   "41"  "control"    "72"  "local"   
C.8_C_L_144    "C"   "8"   "control"    "144" "local"   
C.36_C_L_144   "C"   "36"  "control"    "144" "local"   
C.40_C_L_144   "C"   "40"  "control"    "144" "local"   
C.43_C_L_144   "C"   "43"  "control"    "144" "local"   
C.14_I_L_6     "C"   "4"   "control"    "6"   "systemic"
C.15_I_L_6     "C"   "6"   "control"    "6"   "systemic"
C.29_I_L_6     "C"   "7"   "control"    "6"   "systemic"
C.44_I_L_6     "C"   "37"  "control"    "6"   "systemic"
C.25_I_L_24    "C"   "1"   "control"    "24"  "systemic"
C.26_I_L_24    "C"   "11"  "control"    "24"  "systemic"
C.28_I_L_24    "C"   "19"  "control"    "24"  "systemic"
C.45_I_L_24    "C"   "42"  "control"    "24"  "systemic"
C.17_I_L_72    "C"   "2"   "control"    "72"  "systemic"
C.22_I_L_72    "C"   "9"   "control"    "72"  "systemic"
C.33_I_L_72    "C"   "27"  "control"    "72"  "systemic"
C.48_I_L_72    "C"   "41"  "control"    "72"  "systemic"
C.18_I_L_144   "C"   "8"   "control"    "144" "systemic"
C.23_I_L_144   "C"   "36"  "control"    "144" "systemic"
C.35_I_L_144   "C"   "40"  "control"    "144" "systemic"
C.47_I_L_144   "C"   "43"  "control"    "144" "systemic"
C.4_C_S_6      "C"   "14"  "inoculated" "6"   "local"   
C.6_C_S_6      "C"   "15"  "inoculated" "6"   "local"   
C.7_C_S_6      "C"   "29"  "inoculated" "6"   "local"   
C.37_C_S_6     "C"   "44"  "inoculated" "6"   "local"   
C.1_C_S_24     "C"   "25"  "inoculated" "24"  "local"   
C.11_C_S_24    "C"   "26"  "inoculated" "24"  "local"   
C.19_C_S_24    "C"   "28"  "inoculated" "24"  "local"   
C.42_C_S_24    "C"   "45"  "inoculated" "24"  "local"   
C.2_C_S_72     "C"   "17"  "inoculated" "72"  "local"   
C.9_C_S_72     "C"   "22"  "inoculated" "72"  "local"   
C.27_C_S_72    "C"   "33"  "inoculated" "72"  "local"   
C.41_C_S_72    "C"   "48"  "inoculated" "72"  "local"   
C.8_C_S_144    "C"   "18"  "inoculated" "144" "local"   
C.36_C_S_144   "C"   "23"  "inoculated" "144" "local"   
C.40_C_S_144   "C"   "35"  "inoculated" "144" "local"   
C.43_C_S_144   "C"   "47"  "inoculated" "144" "local"   
C.14_I_S_6     "C"   "14"  "inoculated" "6"   "systemic"
C.15_I_S_6     "C"   "15"  "inoculated" "6"   "systemic"
C.29_I_S_6     "C"   "29"  "inoculated" "6"   "systemic"
C.44_I_S_6     "C"   "44"  "inoculated" "6"   "systemic"
C.25_I_S_24    "C"   "25"  "inoculated" "24"  "systemic"
C.26_I_S_24    "C"   "26"  "inoculated" "24"  "systemic"
C.28_I_S_24    "C"   "28"  "inoculated" "24"  "systemic"
C.45_I_S_24    "C"   "45"  "inoculated" "24"  "systemic"
C.17_I_S_72    "C"   "17"  "inoculated" "72"  "systemic"
C.22_I_S_72    "C"   "22"  "inoculated" "72"  "systemic"
C.33_I_S_72    "C"   "33"  "inoculated" "72"  "systemic"
C.48_I_S_72    "C"   "48"  "inoculated" "72"  "systemic"
C.18_I_S_144   "C"   "18"  "inoculated" "144" "systemic"
C.23_I_S_144   "C"   "23"  "inoculated" "144" "systemic"
C.35_I_S_144   "C"   "35"  "inoculated" "144" "systemic"
C.47_I_S_144   "C"   "47"  "inoculated" "144" "systemic"

I know that it will depend on the questions you want to answer. The first one, the easy one, is to compare just the two conditions, control vs inoculated, at every sampling point, which I have already done.

But now I would like to perform the analysis considering the other factors. I thought that I could simplify the formula by coding the local and systemic responses and the control and inoculation treatments in four conditions (control-local, control-systemic, inoculated-local, and inoculated-systemic), so the colData has now three variables: genotype, time, and condition.

Now, if I want to analyze the effect of time course, considering the four conditions but not the genotypes, the design should be ~ time + condition + time:condition?

The design is complicated, since many factors enable many combinations. I have few questions in my head: differences between genotypes within each time-course response, differences between local and systemic responses within genotypes, differences between sampling times within responses and genotypes... But, I would like to solve this using a complete formula that I could mine further. Any suggestions?

Thank you very much for your time.

deseq2 design time-course • 256 views
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Entering edit mode
@mikelove
Last seen 2 days ago
United States

hi,

For fairly complex designs, it's not a simple answer I can give about use of the DESeq2 software, but a long conversation about biological questions, assumptions about various effects being required, and details about terms in linear models, which is beyond the software support I can provide here (I just don't have any spare time to provide in depth statistical support on the software forum... as part of my service I often meet with local scientists at my university for an hour to go over a question like this). I'd recommend to discuss your analysis plan with a local statistician or bioinformatician with experience with linear models.

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