This function assesses the within-replicate precision for each feature.

1 2 3 4 |

`object1` |
a list containing two elements: ct (the expression estiamtes) and qc (quality scores) |

`qcThreshold1` |
a numeric threshold corresponding to object1$qc below which values are considered low quality. |

`object2` |
an optional second list of the same format as object1, used to compare two methods. |

`qcThreshold2` |
a numeric threshold corresponding to object2$qc below which values are considered low quality. |

`commonFeatures` |
if TRUE and object2 is non-NULL, only high quality non-NA features in common between both objects are used. |

`statistic` |
whether to compute the standard deviation (sd) or coefficient of variation (cv). |

`scale` |
optional scaling of the values. This can help with visualizing the distributions. |

`bins` |
the number of bins to divide the data into. |

`label1` |
optional label corresponding to object 1 to be used in plotting. |

`label2` |
optional label corresponding to object 2 to be used in plotting. |

A boxplot of either the standard deviation or coefficient of variation stratified by expression is produced. The values plotted in each box of the boxplot are returned.

Matthew N. McCall

1 2 3 4 5 | ```
data(lifetech)
tmp1 <- precision(object1=lifetech,qcThreshold1=1.25)
data(qpcRdefault)
tmp2 <- precision(object1=lifetech,qcThreshold1=1.25,
object2=qpcRdefault,qcThreshold2=0.99)
``` |

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