Description Usage Arguments Details Value

View source: R/testProtLMContrast.R

This function can test a contrast based on a protLM object `protLM`

and a contrast matrix `L`

.

1 2 3 4 5 | ```
test.protLMcontrast(protLM, L, add.annotations = TRUE, simplify = TRUE,
lfc = 0, anova = FALSE, anova.na.ignore = TRUE, type_dfs = "residual",
custom_dfs = NULL, exp_unit = NULL, pars_between = NULL,
lmerModFun = NULL, gradMethod = "simple", printProgress = FALSE,
shiny = FALSE, message_extract = NULL, message_test = NULL)
``` |

`protLM` |
An object of class |

`L` |
A contrast matrix with the parameter levels as rows and a column for each contrast. |

`add.annotations` |
A logical indicating whether the |

`simplify` |
A logical indicating wheter, if there is only one contrast, a matrix should be returned instead of a list containing one matrix. Defaults to |

`lfc` |
The minimum (log2) fold-change that is considered scientifically meaningful. Defaults to |

`anova` |
A logical indicating whether the contrasts should be tested simultaneously in one F-test ( |

`anova.na.ignore` |
A logical indicating whether contrasts that cannot be fitted due to missing observations should be ignored when calculating an F value ( |

`type_dfs` |
Either one of |

`custom_dfs` |
Only used if |

`exp_unit` |
Only used if |

`pars_between` |
Only used if |

`lmerModFun` |
Only used when |

`gradMethod` |
Only used when |

`printProgress` |
A logical indicating whether the R should print a message before calculating the contrasts for each accession. Defaults to |

`shiny` |
A logical indicating whether this function is being used by a Shiny app. Setting this to |

`message_extract` |
Only used when |

`message_test` |
Only used when |

Calculating degrees of freedom (and hence p values) for mixed models with unbalanced designs is an unresolved issue in the field (see for example here https://stat.ethz.ch/pipermail/r-help/2006-May/094765.html and here https://stat.ethz.ch/pipermail/r-sig-mixed-models/2008q2/000904.html).
We offer different approximations and leave it up to the user to select his/her preferred approach.
`"residual"`

calculates approximative degrees of freedom by subtracting the trace of the hat matrix from the number of observations. It is the default setting, but this approach might be somewhat too liberal.
`"Satterthwaite"`

calculates approximative degrees of freedom using Satterthwaite's approximation (Satterthwaite, 1946). This approximative approach is used in many applications but is rather slow to calculate and might lead to some missing values due difficulties in calculating the Hessian.
`"exp_between"`

calculates approximative degrees of freedom by defining on which level the treatments were executed and substracting all degrees of freedom lost due to between-treatement effects (`pars_between`

) from the number of experimental units `exp_unit`

. This allows to mimick the behaviour of `type_dfs="between-within"`

for more complex designs.
`"custom"`

Allows the user to provide his/her own degrees of freedom for each contrast and each protein. Custom degrees of freedom should be entered in the `custom_dfs`

field.

A list of data frames, with each data frame in the list corresponding to a contrast in `L`

. Each row of the data frame corresponds to a protein in the `protLM`

object.
The `estimate`

column contains the size estimate of the contrast, the `se`

column contains the estimated standard error on the contrast, the `Tval`

column contains the T-value corresponding to the contrast and the `pval`

column holds the p-value corresponding to the contrast.
If `simplify=TRUE`

and the `protLM`

object contains only one element, the data frame is not present in a list.

statOmics/MSqRob documentation built on Nov. 24, 2018, 6:52 a.m.

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