Description Usage Arguments Details Value Examples

Identifies outliers left and right of a fitted Michaelis-Menten curve. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.

1 2 | ```
M3DropGetExtremes(expr_mat, fdr_threshold=0.1, percent=NA, v_threshold=c(0.05,0.95), suppress.plot=FALSE)
bg__get_extreme_residuals(expr_mat, fit=NA, fdr_threshold=0.1, percent=NA, v_threshold=c(0.05, 0.95), direction="right", suppress.plot=FALSE)
``` |

`expr_mat` |
a numeric matrix of normalized (not log-transformed) expression values, columns = samples, rows = genes. |

`fit` |
output from fitting the Michaelis-Menten equation, see |

`fdr_threshold` |
the threshold for identifying significant outliers after multiple testing correction. |

`percent` |
identify this percentage of data that is most extreme in each direction. |

`v_threshold` |
restrict to this range of dropout rates to avoid poorly fit regions of the data. |

`direction` |
"left" or "right", which tail of outliers to examine. |

`suppress.plot` |
logical, whether to plot the fitted Michaelis-Menten curve and highlight to identified most extreme outliers. |

Fits a Michaelis-Menten function to the dropout-rate of the provided data, then identifies the most extreme left and/or right outliers from the curve. Horizontal residuals are calculated as :

*log_10(S) - log_10( (K * (1 - P)) / P )*

. Extreme left[right] outliers are identified either as the `percent`

smallest[largest] horizontal residuals. If `percent`

is undefined (default) a normal distribution is fitted to the horizontal residuals and a Z-test is used to identify significant outliers after FDR multiple testing correction.

Only genes with dropout rates within v_threshold will be considered to avoid the skewing of residuals due to the exponential parts of the MM curve near P = 0 & P = 1.

`M3DropGetExtremes`

identifies both left and right residuals using the provided thresholds in each direction. Eg. will return the `percent`

smallest and `percent`

largest residuals. It also plots the fitted MM curve and highlights the left and right extreme outliers unless suppress.plot=TRUE .
`bg__get_extreme_residuals`

identifies one-sided extreme outliers.

`M3DropGetExtremes`

List containing elements left and right, vectors of the names of the extreme genes to the left and right of the curve respectively.
`bg__get_extreme_residuals`

A vector of names of the extreme genes in the specified direction.

1 2 3 4 5 | ```
library(M3DExampleData)
norm <- M3DropConvertData(Mmus_example_list$data, is.counts=TRUE)
extreme_gene_lists <- M3DropGetExtremes(norm, fdr_threshold=0.1)
extreme_gene_lists <- M3DropGetExtremes(norm, percent=0.01)
# Lextremes <- bg__get_extreme_residuals(norm, fdr_threshold=0.1, direction="left")
``` |

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