Description Usage Arguments Value Examples

Set the discretized expression attribute Uses the discretize_exprs function of the FCBF package

1 2 3 4 5 6 7 | ```
discretize(fc, number_of_bins = 4, method = "varying_width",
alpha = 1, centers = 3, min_max_cutoff = 0.25, show_pb = TRUE)
## S4 method for signature 'fcoex'
discretize(fc, number_of_bins = 4,
method = "varying_width", alpha = 1, centers = 3,
min_max_cutoff = 0.25, show_pb = TRUE)
``` |

`fc` |
Object of class |

`number_of_bins` |
Number of equal-width bins for discretization. Note: it is a binary discretization, with the first bin becoming one class ('low') and the other bins, another class ('high').#' Defaults to 4. |

`method` |
Method applied to all genes for discretization. Methods available: "varying_width" (Binarization modulated by the number_of_bins param), "mean" (Split in ON/OFF by each gene mean expression), "median" (Split in ON/OFF by each gene median expression), "mean_sd"(Split in low/medium/high by each assigning "medium" to the interval between mean +- standard_deviation. Modulated by the alpha param, which enlarges (>1) or shrinks (<1) the "medium" interval. ), ), "kmeans"(Split in different groups by the kmeans algorithm. As many groups as specified by the centers param) and "min_max_%" (Similat to the "varying width", a binarization threshold in a "GMM" (A Gaussian Mixture Model as implemented by the package mclust, trying to fit 2:5 Gaussians). Default is "varying_width" |

`alpha` |
Modulator for the "mean_sd" method.Enlarges (>1) or shrinks (<1) the "medium" interval. Defaults to 1. |

`centers` |
Modulator for the "kmeans" method. Defaults to 3. |

`min_max_cutoff` |
<- Modulator for the "min_max_%" method. Defaults to 0.25. |

`show_pb` |
Enables a progress bar for the discretization. Defaults to TRUE. |

A data frame with the discretized features in the same order as previously

1 2 3 4 5 6 | ```
library(SingleCellExperiment)
data("mini_pbmc3k")
targets <- colData(mini_pbmc3k)$clusters
exprs <- as.data.frame(assay(mini_pbmc3k, "logcounts"))
fc <- new_fcoex(exprs, targets)
fc <- discretize(fc)
``` |

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