Description Usage Arguments Value Author(s)

For each group K, a quantile regression is fit over all genes (PropToUse) for a grid of possible degree's d and quantile's tau. For each value of tau and d, the predicted expression values are obtained and regressed against the original sequencing depths. The optimal tau and d combination is chosen as that closest to the mode of the gene slopes.

1 | ```
SCnormFit(Data, SeqDepth, Slopes, K, PropToUse = 0.25, Tau = 0.5, 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. |

`K` |
the number of groups for normalizing. If left unspecified, an evaluation procedure will determine the optimal value of K (recommended). |

`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 ). |

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

normalized expression matrix and matrix of scaling factors.

Rhonda Bacher

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