R: The propd Method

propd {propr} | R Documentation

## The propd Method

### Description

Welcome to the `propd` method!

Let X and Y be non-zero positive feature vectors measured across N samples belonging to one of two groups, sized N1 and N2. We use VLR to denote the variance of the log of the ratio of the vectors X over Y. We define theta as the weighted sum of the within-group VLR divided by the weighted total VLR.

The `propd` method calculates theta. This fails in the setting of zero counts. The `propd` method will use a Box-Cox transformation to approximate VLR based on the parameter α, if provided. We refer the user to the vignette for more details.

Note that Group 1 always refers to the first element of the `group` vector argument supplied to `propd`.

### Usage

    ## S4 method for signature 'propd'
    show(object)

    propd(counts, group, alpha, p = 100, weighted = FALSE)

    setActive(propd, what = "theta_d")

    setDisjointed(propd)

    setEmergent(propd)

    updateCutoffs.propd(object, cutoff = seq(0.05, 0.95, 0.3))

    updateF(propd, moderated = FALSE, ivar = "clr")

### Arguments

`object` | A `propr` or `propd` object.
`counts` | A data.frame or matrix. A "count matrix" with subjects as rows and features as columns. Note that this matrix does not necessarily have to contain counts.
`group` | A character vector. Group or sub-group memberships, ordered according to the row names in `counts`.
`alpha` | A double. See vignette for details. Leave missing to skip Box-Cox transformation.
`p` | An integer. The number of permutation cycles.
`weighted` | A boolean. Toggles whether to calculate theta using `limma::voom` weights.
`propd` | A `propr` or `propd` object.
`what` | A character string. The theta type to set active.
`cutoff` | For `updateCutoffs`, a numeric vector. this argument provides the FDR cutoffs to test. For graph functions, a numeric scalar. This argument indicates the maximum theta to include in the figure. For graph functions, a large integer will instead retrieve the top N pairs as ranked by theta.
`moderated` | For `updateF`, a boolean. Toggles whether to calculate a moderated F-statistic.
`ivar` | A numeric scalar. Specifies reference feature(s) for additive log-ratio transformation. The argument will also accept feature name(s) instead of the index position(s). Set to "iqlr" to use inter-quartile log-ratio transformation. Ignore to use centered log-ratio transformation.

### Value

Returns a `propr` object.

### Slots

`counts`

  A data.frame. Stores the original "count matrix" input.

`alpha`

  A double. Stores the alpha value used for transformation.

`group`

  A character vector. Stores the original group labels.

`weighted`

  A logical. Stores whether the theta is weighted.

`weights`

  A matrix. If weighted, stores the limma-based weights.

`active`

  A character. Stores the name of the active theta type.

`Fivar`

  ANY. Stores the reference used to moderate theta.

`dfz`

  A double. Stores the prior df used to moderate theta.

`results`

  A data.frame. Stores the pairwise `propd` measurements.

`permutes`

  A data.frame. Stores the shuffled group labels, used to reproduce permutations of `propd`.

`fdr`

  A data.frame. Stores the FDR cutoffs for `propd`.

### Methods (by generic)

`show:` Method to show `propd` object.

### Functions

`setActive:` Build analyses and figures using a specific theta type. For example, set `what = "theta_d"` to analyze disjointed proportionality and `what = "theta_e"` to analyze emergent proportionality.

`setDisjointed:` A wrapper for `setActive(propd, what = "theta_d")`.

`setEmergent:` A wrapper for `setActive(propd, what = "theta_e")`.

`updateCutoffs:` Use the `propd` object to permute theta across a number of theta cutoffs. Since the permutations get saved when the object is created, calling `updateCutoffs` will use the same random seed each time.

`updateF:` Use the `propd` object to calculate the F-statistic from theta as described in the Erb et al. 2017 manuscript on differential proportionality. Optionally calculates a moderated F-statistic using the limma-voom method. Supports weighted and alpha transformed theta values.

[Package propr version 4.2.6 Index]