Description Usage Arguments Value Author(s)

Bin counts are normalized by regressing out the effect of the first Principal
Components. Beforehands, the average coverage is normalized. Then PC are computed
using `prcomp`

function and regressed out using linear regression.

1 |

`bc.df` |
a data.frame with 'chr', 'start', 'end' columns and then one column per sample with its bin counts. |

`nb.pcs` |
the number of Principal Components to include in the regression model. |

`nb.cores` |
the number of cores to use. Default is 1. |

`norm.stats.comp` |
Should some statistics on the normalized bin count be computed (mean, sd, outliers). Default is TRUE. |

a list with

`norm.stats` |
a data.frame witht some metrics about the normalization of each bin (row) : coverage average and standard deviation; number of outlier reference samples; principal components |

`bc.norm` |
a data.frame, similar to the input 'bc.df', with the normalized bin counts. |

Jean Monlong

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