Description Usage Arguments Value Author(s)

Median quantile regression is fit for each gene using the normalized gene expression values. A slope near zero indicate the sequencing depth effect has been successfully removed. Genes are divided into ten equally sized groups based on their non-zero median expression. Slope densities are plot for each group and estimated modes are calculated. If any of the ten group modes is larger than .1, the K is not sufficient to normalize the data.

1 2 3 4 5 6 7 8 9 10 | ```
evaluateK(
Data,
SeqDepth,
OrigData,
Slopes,
Name,
Tau,
PrintProgressPlots,
ditherCounts
)
``` |

`Data` |
matrix of normalized expression counts. Rows are genes and columns are samples. |

`SeqDepth` |
vector of sequencing depths estimated as columns sums of un-normalized expression matrix. |

`OrigData` |
matrix of un-normalized expression counts. Rows are genes and columns are samples. |

`Slopes` |
vector of slopes estimated in the GetSlopes() function. Only used here to obtain the names of genes considered in the normalization. |

`Name` |
plot title |

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

`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. |

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

value of largest mode and a plot of the ten normalized slope densities.

Rhonda Bacher

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