Question

Differentially Paired RNA-Seq Analysis DESeq2

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Entering edit mode

Raúl • 0

@566964b1

Last seen 3.8 years ago

Spain

Hello,

I'm exhausted with this problem. I hope some of you can help me. I will explain my problem. I have 68 samples from 34 individuals (2 sample per individual, in different times). This 34 individuals belong to two different groups (F and C). I have to compare the different times from two groups. I mean F1 vs F2 and C1 vs C2.


data.frame(sample=c("C10_1", "C10_2", "C11_1", "C11_2", "C12_1", "C12_2", 
    "C13_1", "C13_2", "C14_1", "C14_2", "C17_1", "C17_2", "C2_1", 
    "C2_2", "C22_1", "C22_2", "C23_1", "C23_2", "C3_1", "C3_2", 
    "C30_1", "C30_2", "C32_1", "C32_2", "C4_1", "C4_2", "C6_1", 
    "C6_2", "C7_1", "C7_2", "C8_1", "C8_2", "F02_1", "F02_2", 
    "F03_1", "F03_2", "F04_1", "F04_2", "F06_1", "F06_2", "F07_1", 
    "F07_2", "F08_1", "F08_2", "F09_1", "F09_2", "F10_1", "F10_2", 
    "F12_1", "F12_2", "F14_1", "F14_2", "F16_1", "F16_2", "F17_1", 
    "F17_2", "F18_1", "F18_2", "F19_1", "F19_2", "F21_1", "F21_2", 
    "F22_1", "F22_2", "F23_1", "F23_2", "F26_1", "F26_2"), ind = c("C10", 
    "C10", "C11", "C11", "C12", "C12", "C13", "C13", "C14", "C14", 
    "C17", "C17", "C2", "C2", "C22", "C22", "C23", "C23", "C3", 
    "C3", "C30", "C30", "C32", "C32", "C4", "C4", "C6", "C6", 
    "C7", "C7", "C8", "C8", "F02", "F02", "F03", "F03", "F04", 
    "F04", "F06", "F06", "F07", "F07", "F08", "F08", "F09", "F09", 
    "F10", "F10", "F12", "F12", "F14", "F14", "F16", "F16", "F17", 
    "F17", "F18", "F18", "F19", "F19", "F21", "F21", "F22", "F22", 
    "F23", "F23", "F26", "F26"), group_time = c("C1", 
    "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", 
    "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", 
    "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", 
    "C2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", 
    "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", 
    "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", 
    "F2", "F1", "F2", "F1", "F2", "F1", "F2"))

When I want to perform the two comparisons with this code:


dds <- DESeqDataSetFromMatrix(expression_matrix, colData = new_pheno, design = ~ group_time + ind)

I received the next error:

Error in checkFullRank(modelMatrix) : the model matrix is not full rank, so the model cannot be fit as specified. One or more variables or interaction terms in the design formula are linear combinations of the others and must be removed.

Please read the vignette section 'Model matrix not full rank':

Am I wrong with the design?

Thanks for your help!

DESeq2 • 987 views

ADD COMMENT • link updated 3.8 years ago by Michael Love 43k • written 3.8 years ago by Raúl • 0

score 0 · Answer 1 · 2022-02-10

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Entering edit mode

Michael Love 43k

@mikelove

Last seen 18 hours ago

United States

Please do read the vignette, this design is covered.

ADD COMMENT • link 3.8 years ago Michael Love 43k

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Entering edit mode

Finally I think I understand the problem. However I'm still confused. I have changed the matrix in order to make it more similar to the example in vignettes.


coldata = data.frame(samples = c("C10_1", "C10_2", "C11_1", "C11_2", "C12_1", "C12_2", 
    "C13_1", "C13_2", "C14_1", "C14_2", "C17_1", "C17_2", "C2_1", 
    "C2_2", "C22_1", "C22_2", "C23_1", "C23_2", "C3_1", "C3_2", 
    "C30_1", "C30_2", "C32_1", "C32_2", "C4_1", "C4_2", "C6_1", 
    "C6_2", "C7_1", "C7_2", "C8_1", "C8_2", "F02_1", "F02_2", 
    "F03_1", "F03_2", "F04_1", "F04_2", "F06_1", "F06_2", "F07_1", 
    "F07_2", "F08_1", "F08_2", "F09_1", "F09_2", "F10_1", "F10_2", 
    "F12_1", "F12_2", "F14_1", "F14_2", "F16_1", "F16_2", "F17_1", 
    "F17_2", "F18_1", "F18_2", "F19_1", "F19_2", "F21_1", "F21_2", 
    "F22_1", "F22_2", "F23_1", "F23_2", "F26_1", "F26_2"), ind = c("C10", 
    "C10", "C11", "C11", "C12", "C12", "C13", "C13", "C14", "C14", 
    "C17", "C17", "C2", "C2", "C22", "C22", "C23", "C23", "C3", 
    "C3", "C30", "C30", "C32", "C32", "C4", "C4", "C6", "C6", 
    "C7", "C7", "C8", "C8", "F02", "F02", "F03", "F03", "F04", 
    "F04", "F06", "F06", "F07", "F07", "F08", "F08", "F09", "F09", 
    "F10", "F10", "F12", "F12", "F14", "F14", "F16", "F16", "F17", 
    "F17", "F18", "F18", "F19", "F19", "F21", "F21", "F22", "F22", 
    "F23", "F23", "F26", "F26"), time = c("1", "2", "1", "2", "1", "2", 
    "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", 
    "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", 
    "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", 
    "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", 
    "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", "1", "2", 
    "1", "2"), group = c("C", "C", "C", "C", "C", "C", "C", "C", "C", 
    "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", 
    "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "F", 
    "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", 
    "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", 
    "F", "F", "F", "F", "F", "F", "F", "F", "F", "F", "F"), c("C1", 
    "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", 
    "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", 
    "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", "C2", "C1", 
    "C2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", 
    "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", 
    "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", "F2", "F1", 
    "F2", "F1", "F2", "F1", "F2", "F1", "F2"), ind.c = c("1", "1", "2", 
    "2", "3", "3", "4", "4", "5", "5", "6", "6", "7", "7", "8", 
    "8", "9", "9", "10", "10", "11", "11", "12", "12", "13", 
    "13", "14", "14", "15", "15", "16", "16", "1", "1", "2", 
    "2", "3", "3", "4", "4", "5", "5", "6", "6", "7", "7", "8", 
    "8", "9", "9", "10", "10", "11", "11", "12", "12", "13", 
    "13", "14", "14", "15", "15", "16", "16", "17", "17", "18", 
    "18"))

dds <- DESeqDataSetFromMatrix(expression_matrix, colData = coldata, design = ~ time + time:group + time:ind.n)

After performing DESeq function my resultsNames are


resultsNames(dds)
 [1] "Intercept"     "time_2_vs_1"   "time1.groupF"  "time2.groupF"  "time1.ind.n2"  "time2.ind.n2"  "time1.ind.n3" 
 [8] "time2.ind.n3"  "time1.ind.n4"  "time2.ind.n4"  "time1.ind.n5"  "time2.ind.n5"  "time1.ind.n6"  "time2.ind.n6" 
[15] "time1.ind.n7"  "time2.ind.n7"  "time1.ind.n8"  "time2.ind.n8"  "time1.ind.n9"  "time2.ind.n9"  "time1.ind.n10"
[22] "time2.ind.n10" "time1.ind.n11" "time2.ind.n11" "time1.ind.n12" "time2.ind.n12" "time1.ind.n13" "time2.ind.n13"
[29] "time1.ind.n14" "time2.ind.n14" "time1.ind.n15" "time2.ind.n15" "time1.ind.n16" "time2.ind.n16" "time1.ind.n17"
[36] "time2.ind.n17" "time1.ind.n18" "time2.ind.n18"

So I can compare F1 vs F2 with time1.groupF and time2.groupF labels. But how can I compare C1 vs C2 or time1.groupC vs time2.groupC?

ADD REPLY • link 3.8 years ago Raúl • 0

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Entering edit mode

I don't have time to help with statistical analysis and interpretation of results here, I have to limit myself to software related questions. I recommend users collaborate with a local statistician or someone familiar with linear models in R.

ADD REPLY • link 3.8 years ago Michael Love 43k