NPARCfit {NPARC} | R Documentation

## Fit null and alternative models for Non-parametric analysis of response curves

### Description

Fit melting curve and return model metrics as well as predictions for the null and alternative models.

### Usage

    NPARCfit(x, y, id, control = getParams(), groupsNull = NULL, groupsAlt,
      BPPARAM = BiocParallel::SerialParam(progressbar = TRUE),
      returnModels = FALSE)

### Arguments

`x` | numeric vector of the independent variables (typically temperature)
`y` | numeric vector of the dependent variables (typically relative abundance measurements)
`id` | character vector with the protein ID to which each each data point belongs.
`control` | list of parameters used to control specific parts of the analyse
`groupsNull` | one or more vectors with grouping variables for the null models. See details.
`groupsAlt` | one or more vectors with grouping variables for the alternative models. See details.
`BPPARAM` | BiocParallel parameter object to invoke curve fitting in parallel. Default: BiocParallel::SerialParam()
`returnModels` | boolean value. If true, the fitted models are returned together with the test results

### Details

`groupsNull` or `groupsAlt` can either be a single vector each, or data.frames of the same length as `x` and `y` with one column per factor

### Value

data frame with fitted model parameters and additional columns listing e.g. residuals sum of squares

### Examples

    data(stauro_TPP_data_tidy)
    df <- dplyr::filter(stauro_TPP_data_tidy, grepl("CDK|GTP|CRK", uniqueID))
    testResults <- NPARCfit(x = df$temperature,
                         y = df$relAbundance,
                         id = df$uniqueID,
                         groupsAlt = df$compoundConcentration)

[Package NPARC version 1.4.0 Index]