I have this data set:

> colData(dds_WT) |> as.data.frame()
             id       sample cell_line time_point treatment   Condition replicate
WT0h_1        1       WT0h_1        WT          0      none  WT_0h_none         1
WT0h_2        2       WT0h_2        WT          0      none  WT_0h_none         2
WT0h_3        3       WT0h_3        WT          0      none  WT_0h_none         3
WT24h_CpG_13 13 WT24h_CpG_13        WT         24       CpG  WT_24h_CpG         1
WT24h_CpG_14 14 WT24h_CpG_14        WT         24       CpG  WT_24h_CpG         2
WT24h_CpG_15 15 WT24h_CpG_15        WT         24       CpG  WT_24h_CpG         3
WT24hns_7     7    WT24hns_7        WT         24      none WT_24h_none         1
WT24hns_8     8    WT24hns_8        WT         24      none WT_24h_none         2
WT24hns_9     9    WT24hns_9        WT         24      none WT_24h_none         3
WT6h_CpG_10  10  WT6h_CpG_10        WT          6       CpG   WT_6h_CpG         1
WT6h_CpG_11  11  WT6h_CpG_11        WT          6       CpG   WT_6h_CpG         2
WT6h_CpG_12  12  WT6h_CpG_12        WT          6       CpG   WT_6h_CpG         3
WT6hns_4      4     WT6hns_4        WT          6      none  WT_6h_none         1
WT6hns_5      5     WT6hns_5        WT          6      none  WT_6h_none         2
WT6hns_6      6     WT6hns_6        WT          6      none  WT_6h_none         3
                genotype
WT0h_1        WT_0h_none
WT0h_2        WT_0h_none
WT0h_3        WT_0h_none
WT24h_CpG_13  WT_24h_CpG
WT24h_CpG_14  WT_24h_CpG
WT24h_CpG_15  WT_24h_CpG
WT24hns_7    WT_24h_none
WT24hns_8    WT_24h_none
WT24hns_9    WT_24h_none
WT6h_CpG_10    WT_6h_CpG
WT6h_CpG_11    WT_6h_CpG
WT6h_CpG_12    WT_6h_CpG
WT6hns_4      WT_6h_none
WT6hns_5      WT_6h_none
WT6hns_6      WT_6h_none

(and the same number of of samples for a KO (defined in the cell_line column - see below for full colData() )

I would like to do a time-series analysis, but for time-point 0 I have only non-treated samples. When I build the two models e.g.

design(dds_WT) <- ~ 0 + time_point + time_point:treatment
reduced_design <- ~ 0 + time_point # The coefficients for treatment and time_point:treatment are all zero.

If i understand it correctly, I added the ~0 to compensate for that fact. But when I run the DESEq() command I get the error

Error in designAndArgChecker(object, betaPrior) :

full model matrix is less than full rank

Am I building the correct models? or where Do I make an error?

thanks in advance for helping

new("DFrame", rownames = c("Il4i1ko0h_16", "Il4i1ko0h_17", "Il4i1ko0h_18", 
"Il4i1ko24h_CpG_28", "Il4i1ko24h_CpG_29", "Il4i1ko24h_CpG_30", 
"Il4i1ko24hns_22", "Il4i1ko24hns_23", "Il4i1ko24hns_24", "Il4i1ko6h_CpG_25", 
"Il4i1ko6h_CpG_26", "Il4i1ko6h_CpG_27", "Il4i1ko6hns_19", "Il4i1ko6hns_20", 
"Il4i1ko6hns_21", "WT0h_1", "WT0h_2", "WT0h_3", "WT24h_CpG_13", 
"WT24h_CpG_14", "WT24h_CpG_15", "WT24hns_7", "WT24hns_8", "WT24hns_9", 
"WT6h_CpG_10", "WT6h_CpG_11", "WT6h_CpG_12", "WT6hns_4", "WT6hns_5", 
"WT6hns_6"), nrows = 30L, elementType = "ANY", elementMetadata = new("DFrame", 
    rownames = NULL, nrows = 8L, elementType = "ANY", elementMetadata = NULL, 
    metadata = list(), listData = list(type = c("input", "input", 
    "input", "input", "input", "input", "input", "input"), description = c("", 
    "", "", "", "", "", "", ""))), metadata = list(), listData = list(
    id = c(16L, 17L, 18L, 28L, 29L, 30L, 22L, 23L, 24L, 25L, 
    26L, 27L, 19L, 20L, 21L, 1L, 2L, 3L, 13L, 14L, 15L, 7L, 8L, 
    9L, 10L, 11L, 12L, 4L, 5L, 6L), sample = c("Il4i1ko0h_16", 
    "Il4i1ko0h_17", "Il4i1ko0h_18", "Il4i1ko24h_CpG_28", "Il4i1ko24h_CpG_29", 
    "Il4i1ko24h_CpG_30", "Il4i1ko24hns_22", "Il4i1ko24hns_23", 
    "Il4i1ko24hns_24", "Il4i1ko6h_CpG_25", "Il4i1ko6h_CpG_26", 
    "Il4i1ko6h_CpG_27", "Il4i1ko6hns_19", "Il4i1ko6hns_20", "Il4i1ko6hns_21", 
    "WT0h_1", "WT0h_2", "WT0h_3", "WT24h_CpG_13", "WT24h_CpG_14", 
    "WT24h_CpG_15", "WT24hns_7", "WT24hns_8", "WT24hns_9", "WT6h_CpG_10", 
    "WT6h_CpG_11", "WT6h_CpG_12", "WT6hns_4", "WT6hns_5", "WT6hns_6"
    ), cell_line = c("Il4i1ko", "Il4i1ko", "Il4i1ko", "Il4i1ko", 
    "Il4i1ko", "Il4i1ko", "Il4i1ko", "Il4i1ko", "Il4i1ko", "Il4i1ko", 
    "Il4i1ko", "Il4i1ko", "Il4i1ko", "Il4i1ko", "Il4i1ko", "WT", 
    "WT", "WT", "WT", "WT", "WT", "WT", "WT", "WT", "WT", "WT", 
    "WT", "WT", "WT", "WT"), time_point = c(0L, 0L, 0L, 24L, 
    24L, 24L, 24L, 24L, 24L, 6L, 6L, 6L, 6L, 6L, 6L, 0L, 0L, 
    0L, 24L, 24L, 24L, 24L, 24L, 24L, 6L, 6L, 6L, 6L, 6L, 6L), 
    treatment = c("none", "none", "none", "CpG", "CpG", "CpG", 
    "none", "none", "none", "CpG", "CpG", "CpG", "none", "none", 
    "none", "none", "none", "none", "CpG", "CpG", "CpG", "none", 
    "none", "none", "CpG", "CpG", "CpG", "none", "none", "none"
    ), Condition = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 
    3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 
    8L, 9L, 9L, 9L, 10L, 10L, 10L), levels = c("Il4i1ko_0h_none", 
    "Il4i1ko_24h_CpG", "Il4i1ko_24h_none", "Il4i1ko_6h_CpG", 
    "Il4i1ko_6h_none", "WT_0h_none", "WT_24h_CpG", "WT_24h_none", 
    "WT_6h_CpG", "WT_6h_none"), class = "factor"), replicate = c(1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), 
    genotype = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 
    4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 
    9L, 9L, 9L, 10L, 10L, 10L), levels = c("Il4i1ko_0h_none", 
    "Il4i1ko_24h_CpG", "Il4i1ko_24h_none", "Il4i1ko_6h_CpG", 
    "Il4i1ko_6h_none", "WT_0h_none", "WT_24h_CpG", "WT_24h_none", 
    "WT_6h_CpG", "WT_6h_none"), class = "factor")))