aov() function is for analysis of variance (ANOVA).

aov(formula, data=NULL, ...)

formula: a formula specifying the model
data: the data frame containing the variables specified in the formula

Following is a csv file example, we will do ANOVA analysis:

Subtype,Gender,Expression A,m,-0.54 A,m,-0.8 A,m,-1.03 A,m,-0.41 A,m,-1.31 A,f,-0.66 A,m,-0.43 A,m,1.01 A,f,-1.15 A,m,0.14 A,m,1.42 A,f,-0.3 A,m,-0.16 A,m,0.15 A,m,-0.62 A,m,-0.42 A,f,-0.4 A,m,-0.35 A,m,-0.42 A,m,0.32 A,m,-0.57 A,m,-0.07 A,m,-0.06 A,f,-0.24 A,m,0.02 A,m,-0.39 A,m,-0.74 A,f,-0.92 A,m,-0.09 A,m,-0.03 A,m,0.18 A,m,0.25 A,f,0.48 A,m,-0.39 A,m,-0.24 A,m,-0.3 A,m,0.25 A,m,-0.42 A,m,0.54 A,m,0.03 A,m,-0.66 A,m,0.3 A,m,-0.38 A,m,-0.03 A,m,-0.62 A,m,0.14 A,f,-1.68 A,m,-0.77 A,f,-0.8 A,m,-0.09 A,m,-0.8 A,m,-0.41 A,m,-0.88 A,m,-0.27 A,f,-0.55 A,m,-0.07 A,m,-1.6 A,f,-0.11 A,m,-0.79 A,m,-0.33 A,f,-1.26 A,m,1.31 A,m,-0.33 A,m,-0.43 A,m,-0.92 A,f,-0.11 A,m,-0.29 A,m,-1.02 A,m,0.41 A,m,-0.81 A,m,0.61 A,m,-0.63 A,m,-0.49 A,m,0.18 A,m,0.17 A,m,0.24 A,f,0.13 A,m,-0.12 A,m,-0.24 A,m,-0.26 A,m,1.48 A,m,0.04 A,f,0.81 A,m,-0.56 A,m,-1.12 A,m,-0.19 A,m,0.27 A,m,-1.28 A,m,-0.38 A,m,-0.83 A,m,0.25 A,m,-0.14 A,f,0.45 A,m,0.29 A,m,0.18 A,f,0.74 A,m,0.44 A,m,-0.28 A,f,-0.31 A,m,0.08 A,f,-0.18 A,m,-0.29 A,m,-0.62 A,f,-0.08 A,m,-0.87 A,m,0.19 A,f,0.54 A,m,0.34 A,m,0.54 A,f,-0.35 A,m,0.02 A,m,-0.39 A,f,0.38 A,m,1.25 A,m,-0.51 A,f,-0.39 A,m,0.05 A,m,-0.36 A,m,-0.19 A,f,-1.49 A,m,-0.1 A,m,0.08 A,m,-1.16 A,f,-0.77 A,m,1.58 A,f,-0.92 A,m,0.59 A,f,-0.35 A,f,0.26 A,f,-0.78 A,f,1.2 A,f,0.06 A,f,-0.68 A,m,-0.19 A,f,-0.44 A,m,0.56 A,f,0.93 A,f,-0.35 A,f,0.11 A,m,-0.22 A,f,-0.12 A,f,-0.22 A,f,0.29 B,f,-0.67 B,m,-0.77 B,f,-0.03 B,m,-0.12 B,f,-0.57 B,m,-0.76 B,f,0.19 B,f,-1.8 B,m,0.35 B,f,-0.81 B,f,1.8 B,f,-0.99 B,f,-2.22 B,f,-1.06 B,m,-0.69 B,f,0.06 B,m,-0.2 B,f,-1.68 B,f,-0.64 B,m,-0.44 B,f,0.29 B,f,-0.13 B,m,-1.98 B,f,-0.84 B,f,0.44 B,m,0 B,f,-1.32 B,f,-0.54 B,f,-0.05 B,m,-0.54 B,f,0.23 B,f,0.38 B,f,0.35 B,m,-0.61 B,f,0.3 B,f,-0.33 B,f,0.79 B,m,-1.39 B,f,-0.06 B,f,-0.88 B,m,0.44 B,f,0.32 B,f,-0.45 B,f,0.21 B,m,0.2 B,f,-2.03 B,f,0.59 B,m,-0.78 B,f,-0.92 B,m,-0.96 B,m,-0.1 B,f,-0.07 B,m,0.39 B,f,-0.39 B,m,-1.11 B,f,-0.98 B,f,-0.11 B,m,-1.78 B,f,-0.73 B,f,-1.01 B,f,-0.5 B,f,-0.16 B,f,-0.59 B,m,-1.46 B,f,1.13 B,f,1.01 B,m,1 B,f,0.21 B,f,-0.21 B,f,-1.05 B,m,-1.34 B,m,-0.72 B,m,-0.47 B,f,0.1 B,m,0.15 C,m,1.67 C,m,0.81 C,f,-1.81 C,f,-1.18 C,f,0.49 C,f,-1.74 C,f,-1.57 C,f,0.46 C,f,1.31 C,m,0.16 C,m,-0.39 C,m,-0.4 C,f,0.44 C,m,1.18 C,f,-2.08 C,f,-1.62 C,m,-0.3 C,f,-1.53 C,f,0.03 C,f,-0.42 C,m,-1.91 C,f,-1.86 C,f,-1.99 C,f,-0.25 C,m,-1.14 C,f,-2.11 C,f,-0.93 C,f,0.42 C,f,-1.13 C,m,0.13 C,f,-0.92 C,m,-0.34 C,f,0.38 C,f,-2.01 C,f,1.42 C,f,0.1 C,m,-0.44 C,f,-2.17 C,f,0.13 C,f,-1.75 C,m,0.52 C,f,-1.18 C,f,0.85 C,m,1.11 C,f,0.64 C,f,0.97 C,f,-0.72 C,f,-0.04 C,f,0.38 C,f,-1.87 C,m,-0.89 C,f,-2.09 C,f,-1.54 C,m,-0.17 C,f,0.09 C,f,-0.25 C,f,0.51 C,f,0.33 C,f,-1.29 C,f,-0.51 C,m,-1.62 C,f,-0.5 C,f,-0.52 (Download the data file)

Let first read in the data from the file:

>x <- read.csv("anova.csv",header=T,sep="\t")

One way ANOVA analysis:

> a = aov(Expression~Subtype, data=x)
> summary(a)

Df Sum Sq Mean Sq F value Pr(>F)
Subtype 2 4.75 2.3769 3.991 0.0196 *
Residuals 278 165.59 0.5956
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Please pay attention to the formula format, dependant variance "Expression" is in front of the independant variance "Subtype".

Report the means and the number of subjects:

>print(model.tables(a,"means"),digits=2)

Tables of means
Grand mean
-0.3053381
Subtype
A B C
-0.18 -0.39 -0.49
rep 143.00 75.00 63.00

Two way ANOVA analysis:

> a = aov(Expression~Subtype*Age, data=x)
> summary(a)

Df Sum Sq Mean Sq F value Pr(>F)
Subtype 2 4.75 2.377 3.975 0.0199 *
Age 1 0.09 0.095 0.159 0.6905
Subtype:Age 2 1.04 0.518 0.866 0.4217
Residuals 275 164.46 0.598
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Here, dependant variance is "Expression", "Subtype" and "Age" are independant variances.

Report the means and the number of subjects:

>print(model.tables(a,"means"),digits=2)

Tables of means
Grand mean
-0.3053381
Gender
f m
-0.39 -0.22
rep 135.00 146.00
Subtype
A B C
-0.22 -0.36 -0.44
rep 143.00 75.00 63.00
Gender:Subtype
Subtype
Gender A B C
f 0 0 -1
rep 40 49 46
m 0 -1 0
rep 103 26 17