Hi,
I am working with the transcriptomics expression data and trying to identify differentially expressed genes between "Molecules" groups thorugh a limma R package.
Currently, I have tried to perform simple comparison within the "Molecules" groups specific to "Condition" and "Stage" columns. For instance, I have extracted the samples of "Healthy" from "Condition" and "Stage" columns and compared between LPS vs. 6h (Baseline), and LTA_vs_6h (Baseline). Likewise for the "Group_A" and "Rem" sample-set. Both these designs are intra group comparisons. The sample metadata and example R code is as follows:
I am interested in inter-group comparisons; My question is, how can I make the contrasts or compare contrasts by mixing both the "Healthy" and "Group_A" sample-set simultaneously by considering both "6h samples" and "Healthy samples" as the Baseline.
Thank you, Toufiq
library(limma)
dput(Sample_metadata)
structure(list(Subject = c("HC1", "HC1", "HC1", "HC2", "HC2",
"HC2", "P1", "P1", "P1", "P2", "P2", "P2", "P3", "P3", "P3"),
Molecules = c("6h", "LTA", "LPS", "6h", "LTA", "LPS", "6h",
"LTA", "LPS", "6h", "LTA", "LPS", "6h", "LTA", "LPS"), Condition = c("Healthy",
"Healthy", "Healthy", "Healthy", "Healthy", "Healthy", "Group_A",
"Group_A", "Group_A", "Group_A", "Group_A", "Group_A", "Group_A",
"Group_A", "Group_A"), Stage = c("Healthy", "Healthy", "Healthy",
"Healthy", "Healthy", "Healthy", "Rem", "Rem", "Rem", "Rem",
"Rem", "Rem", "Rem", "Rem", "Rem")), class = "data.frame", row.names = c("S1",
"S2", "S3", "S4", "S5", "S6", "S7", "S8", "S9", "S10", "S11",
"S12", "S13", "S14", "S15"))
#> Subject Molecules Condition Stage
#> S1 HC1 6h Healthy Healthy
#> S2 HC1 LTA Healthy Healthy
#> S3 HC1 LPS Healthy Healthy
#> S4 HC2 6h Healthy Healthy
#> S5 HC2 LTA Healthy Healthy
#> S6 HC2 LPS Healthy Healthy
#> S7 P1 6h Group_A Rem
#> S8 P1 LTA Group_A Rem
#> S9 P1 LPS Group_A Rem
#> S10 P2 6h Group_A Rem
#> S11 P2 LTA Group_A Rem
#> S12 P2 LPS Group_A Rem
#> S13 P3 6h Group_A Rem
#> S14 P3 LTA Group_A Rem
#> S15 P3 LPS Group_A Rem
Created on 2022-04-10 by the [reprex package](https://reprex.tidyverse.org) (v2.0.1)
Molecules <- factor(Sample_metadata$Molecules)
# simple design; considering samples from the "Healthy" condition only
design_Molecules_Healthy <- model.matrix(~ 0 + Molecules)
dput(design_Molecules_Healthy)
structure(c(1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0), .Dim = c(12L,
3L), .Dimnames = list(c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12"), c("Molecules6h", "MoleculesLPS", "MoleculesLTA"
)), assign = c(1L, 1L, 1L), contrasts = list(Molecules = "contr.treatment"))
#> Molecules6h MoleculesLPS MoleculesLTA
#> 1 1 0 0
#> 2 0 0 1
#> 3 0 1 0
#> 4 1 0 0
#> 5 0 0 1
#> 6 0 1 0
#> 7 1 0 0
#> 8 0 0 1
#> 9 0 1 0
#> 10 1 0 0
#> 11 0 0 1
#> 12 0 1 0
#> attr(,"assign")
#> [1] 1 1 1
#> attr(,"contrasts")
#> attr(,"contrasts")$Molecules
#> [1] "contr.treatment"
## Make contrast
Cont.matrix_Molecules_Healthy <- makeContrasts("LPS_vs_0h" = MoleculesLPS-Molecules6h,
"LTA_vs_6h" = MoleculesLTA-Molecules6h,levels=design_Molecules_Healthy)
dput(Cont.matrix_Molecules_Healthy)
structure(c(-1, 1, 0, -1, 0, 1), .Dim = 3:2, .Dimnames = list(
Levels = c("Molecules6h", "MoleculesLPS", "MoleculesLTA"),
Contrasts = c("LPS_vs_0h", "LTA_vs_6h")))
#> Contrasts
#> Levels LPS_vs_0h LTA_vs_6h
#> Molecules6h -1 -1
#> MoleculesLPS 1 0
#> MoleculesLTA 0 1
# simple design; considering samples from the "Group A" condition + "Rem" stage only
design_Molecules_Group_A <- model.matrix(~ 0 + Molecules)
dput(design_Molecules_Group_A)
structure(c(1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0), .Dim = c(12L,
3L), .Dimnames = list(c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12"), c("Molecules6h", "MoleculesLPS", "MoleculesLTA"
)), assign = c(1L, 1L, 1L), contrasts = list(Molecules = "contr.treatment"))
#> Molecules6h MoleculesLPS MoleculesLTA
#> 1 1 0 0
#> 2 0 0 1
#> 3 0 1 0
#> 4 1 0 0
#> 5 0 0 1
#> 6 0 1 0
#> 7 1 0 0
#> 8 0 0 1
#> 9 0 1 0
#> 10 1 0 0
#> 11 0 0 1
#> 12 0 1 0
#> attr(,"assign")
#> [1] 1 1 1
#> attr(,"contrasts")
#> attr(,"contrasts")$Molecules
#> [1] "contr.treatment"
## Make contrast
Cont.matrix_Molecules_Group_A <- makeContrasts("LPS_vs_0h" = MoleculesLPS-Molecules6h,
"LTA_vs_6h" = MoleculesLTA-Molecules6h,levels=design_Molecules_Group_A)
dput(Cont.matrix_Molecules_Group_A)
structure(c(-1, 1, 0, -1, 0, 1), .Dim = 3:2, .Dimnames = list(
Levels = c("Molecules6h", "MoleculesLPS", "MoleculesLTA"),
Contrasts = c("LPS_vs_0h", "LTA_vs_6h")))
#> Contrasts
#> Levels LPS_vs_0h LTA_vs_6h
#> Molecules6h -1 -1
#> MoleculesLPS 1 0
#> MoleculesLTA 0 1
Created on 2022-04-10 by the [reprex package](https://reprex.tidyverse.org) (v2.0.1)
Do you have multiple samples from the same subjects or is every sample from a different subject? How many independent subjects are involved in your study?
Hi Gordon Smyth Thank you for the prompt response. I have 10 independent Healthy Controls and 25 independent Subjects. I have multiple samples (molecules) from the different subjects. I have revised the sample metadata above (please refer).
Thank you, Toufiq