Description Usage Arguments Value Author(s)

This function iteratively normalizes using K groups and then evaluates whether K is sufficient. If the maximum mode received from the GetK() function is larger than .1, K is increased to K + 1. Uses params sent from SCnorm.

1 2 3 4 5 6 7 8 9 10 11 | ```
normWrapper(
Data,
SeqDepth = NULL,
Slopes = NULL,
CondNum = NULL,
PrintProgressPlots,
PropToUse,
Tau,
Thresh,
ditherCounts
)
``` |

`Data` |
can be a matrix of single-cell expression with cells
where rows are genes and columns are samples. Gene names should
not be a column in this matrix, but should be assigned to rownames(Data).
Data can also be an object of class |

`SeqDepth` |
sequencing depth for each cell/sample. |

`Slopes` |
per gene estimates of the count-depth relationship. |

`CondNum` |
name of group being normalized, just for printing messages. |

`PrintProgressPlots` |
whether to automatically produce plot as SCnorm determines the optimal number of groups (default is FALSE, highly suggest using TRUE). Plots will be printed to the current device. |

`PropToUse` |
proportion of genes closest to the slope mode used for the group fitting, default is set at .25. This number #' mainly affects speed. |

`Tau` |
value of quantile for the quantile regression used to estimate gene-specific slopes (default is median, Tau = .5 ). |

`Thresh` |
threshold to use in evaluating the sufficiency of K, default is .1. |

`ditherCounts` |
whether to dither/jitter the counts, may be used for data with many ties, default is FALSE. |

matrix of normalized and scaled expression values for all conditions and the evaluation plots are output for each attempted value of K.

Rhonda Bacher

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