Description Usage Arguments Details Value Author(s) References

Perform quantile normalization between arrays

1 | ```
qnNormalize(eData, snr, method = 'quantile', snThresh = 3, ties = TRUE)
``` |

`eData` |
matrix of gene expression values |

`snr` |
Optional signal/noise ratio. Only used for trimAMean method |

`method` |
The normalization method desired. Default method is quantile |

`snThresh` |
Signal/noise threshold (default = 3) to indicate presence or absence of a probe signal |

`ties` |
handle values with same rank |

This function performs various normalization for the array data. The default is quantile normalization method (adapted from Bioconductor limma package). Other normalization methods include median, mean, trimMean (trimmed mean), trimAMean (mean with absent gene removed).

For the median normalizaiton, the median signal of each array is scaled to the same value (this value is calculated to equal to the median of all values in the data). The signal values for each array are then adjusted by the scaling factor.

For the mean normalization, the approach is similar to the median normalization procedure except that the mean signal of each array is scaled to the same value (this value is median of all signals in the data).

For the trimMean normalization, the approach is similar to the mean normalization except that the mean for each array is calculated after trimming the top and botton 5% of signals (a total of 10% of values).

For the trimAMean normalization, the signal values for absent probes are not considered. If the s/n of a probe is less than snThresh (default = 3), the expression of the probe is considered not present (absent). The remaining values are then trimmed (top and botton 2.5%, a total of 5%), and the mean value for each array after trimming is scaled to the same value (median of all values in the data).

data matrix with quantile normalized data values

Yongming Sun

bioconductor limma package for quantile normalization

ABarray documentation built on May 2, 2018, 3:42 a.m.

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