Description Usage Arguments Value Author(s) Examples

This function calculates the mean and the coefficient of variation to each row (genes or probesets) in an expression matrix in two ways: i) in the whole matrix ii) for the specific phenotype (case or control).

1 |

`expData` |
The whole normalized expression matrix, rows: genes or probeset, columns: samples, it may be stored in a SummarizedExperiment object. |

`complete` |
Boolean to define if the function uses the whole expression matrix, by default TRUE. |

`treatment` |
A numeric vector with 0s and 1s for each sample in the expression matrix, the 0 expresses the control samples and 1 expresses the case samples, by default is NULL. |

`type` |
It can be "case" to calculate the mean and the coefficient of variation for the case samples or, otherwise, "control" to obtain these two values for the control samples. |

The expression matrix with two new columns, the first one with the averages and the other one with the coefficient of variation values.

Juan David Henao <judhenaosa@unal.edu.co>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
## Creating the expression matrix
# The matrix have 200 genes and 20 samples
n <- 200
m <- 20
# The vector with treatment and control samples
treat <- c(rep(0,10),rep(1,10))
# Calculating the expression values normalized
mat <- as.matrix(rexp(n, rate = 1))
norm <- t(apply(mat, 1, function(nm) rnorm(m, mean=nm, sd=1)))
## Calculating the mean and the coefficient of variation
# For the whole expression matrix
complete <- cofVar(norm)
head(complete)
# For the case samples
case <- cofVar(expData = norm,complete = FALSE,treatment = treat,type = "case")
head(case)
``` |

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