To assess the effects of independent variables: tissue type, fed/fasted state, and larval cortisol treatment on dependent variable cortisol level:
#import cortisol ELISA data
zf_cortisol <- read.table("zebrafish_cortisol/fedstate_cortisol_data.txt", header = TRUE)
zf_cortisol_techreps <- read.table("zebrafish_cortisol/fedstate_cortisol_data_technicalreplicates.txt", header = TRUE)
#change larval_cort from numeric to factor
zf_cortisol$larval_cort <- factor(zf_cortisol$larval_cort,
levels = c(0,1))
zf_cortisol_techreps$larval_cort <- factor(zf_cortisol$larval_cort,
levels = c(0,1))
#Run 3-way Anova to assess variance of dependent variable (cort_level) across independent variables tissue, fed/fasted state, and larval cortisol exposure
res.aov3 <- aov(cort_level ~ tissue * fed_state + larval_cort, data = zf_cortisol)
summary(res.aov3)
## Df Sum Sq Mean Sq F value Pr(>F)
## tissue 5 3867 773.5 6.347 0.00523 **
## fed_state 1 38 37.7 0.310 0.58912
## larval_cort 1 267 266.7 2.189 0.16709
## tissue:fed_state 5 2205 440.9 3.618 0.03517 *
## Residuals 11 1340 121.9
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Cortisol level is significantly different across tissues with a p-value of 0.00523.
There is also a significant interaction affect of tissue/fed state, with a p-value of 0.03517.
However, there is not a significant, concerted effect of larval cortisol exposure across tissues and fed states.
Verify the distribution of residuals is normal:
res <- res.aov3$residuals
hist(res, main = "3-Way Anova Residuals")
Unfortunately, because there is only 1 biological replicate (pooled), I will have to use the technical replicates for the individual tissue ANOVA tests.
kidney_cortisol <- filter(zf_cortisol_techreps, tissue == "KIDNEY")
res.aov2.kidney <- aov(cort_level ~ larval_cort * fed_state, data = kidney_cortisol)
summary(res.aov2.kidney)
## Df Sum Sq Mean Sq F value Pr(>F)
## larval_cort 1 43 43.2 0.087 0.7752
## fed_state 1 2681 2681.4 5.416 0.0484 *
## larval_cort:fed_state 1 426 426.3 0.861 0.3806
## Residuals 8 3961 495.1
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
blood_cortisol <- filter(zf_cortisol_techreps, tissue == "BLOOD")
res.aov2.blood <- aov(cort_level ~ larval_cort * fed_state, data = blood_cortisol)
summary(res.aov2.blood)
## Df Sum Sq Mean Sq F value Pr(>F)
## larval_cort 1 21 21 0.488 0.505
## fed_state 1 3987 3987 92.204 1.15e-05 ***
## larval_cort:fed_state 1 55 55 1.272 0.292
## Residuals 8 346 43
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
brain_cortisol <- filter(zf_cortisol_techreps, tissue == "BRAIN")
res.aov2.blood <- aov(cort_level ~ larval_cort * fed_state, data = blood_cortisol)
summary(res.aov2.blood)
## Df Sum Sq Mean Sq F value Pr(>F)
## larval_cort 1 21 21 0.488 0.505
## fed_state 1 3987 3987 92.204 1.15e-05 ***
## larval_cort:fed_state 1 55 55 1.272 0.292
## Residuals 8 346 43
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
gut_cortisol <- filter(zf_cortisol_techreps, tissue == "GUT")
res.aov2.gut <- aov(cort_level ~ larval_cort * fed_state, data = gut_cortisol)
summary(res.aov2.gut)
## Df Sum Sq Mean Sq F value Pr(>F)
## larval_cort 1 0.914 0.914 0.397 0.546
## fed_state 1 6.062 6.062 2.628 0.144
## larval_cort:fed_state 1 0.150 0.150 0.065 0.805
## Residuals 8 18.451 2.306
skin_cortisol <- filter(zf_cortisol_techreps, tissue == "SKIN")
res.aov2.skin <- aov(cort_level ~ larval_cort * fed_state, data = skin_cortisol)
summary(res.aov2.skin)
## Df Sum Sq Mean Sq F value Pr(>F)
## larval_cort 1 5.44 5.436 0.924 0.3645
## fed_state 1 26.30 26.303 4.473 0.0674 .
## larval_cort:fed_state 1 2.98 2.984 0.507 0.4965
## Residuals 8 47.05 5.881
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
muscle_cortisol <- filter(zf_cortisol_techreps, tissue == "MUSCLE")
res.aov2.muscle <- aov(cort_level ~ larval_cort * fed_state, data = muscle_cortisol)
summary(res.aov2.muscle)
## Df Sum Sq Mean Sq F value Pr(>F)
## larval_cort 1 0.648 0.648 4.169 0.0755 .
## fed_state 1 8.942 8.942 57.506 6.4e-05 ***
## larval_cort:fed_state 1 0.224 0.224 1.439 0.2647
## Residuals 8 1.244 0.155
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Kidney, blood, brain, and muscle are all significantly effected by fed state with p < 0.05, but there is no significant, concerted effect of larval cortisol across fed state.
Overall, this supports our observation that the long-term effects of early-life cortisol treatment differ by tissue and are dynamic based on fed/fasted state.