Description Usage Arguments Details Value Author(s)

For an overview of outlier detection, please see the
corresponding section in the vignette *Advanced topics: Customizing arrayQualityMetrics
reports and programmatic processing of the output*.
These two functions are helper functions used by the different report
generating functions, such as `aqm.boxplot`

.

1 2 | ```
outliers(exprs, method = c("KS", "sum", "upperquartile"))
boxplotOutliers(x, coef = 1.5)
``` |

`exprs` |
A matrix whose columns correspond to arrays, rows to the array features. |

`method` |
A character string specifying the summary statistic to
be used for each column of |

`x` |
A vector of real numbers. |

`coef` |
A number is called an outlier if it is larger than the
upper hinge plus |

`outliers`

: with argument `method="KS"`

, the function first
computes for each column of `exprs`

(i.e. for each array)
the value of the `ks.test`

test statistic
between its distribution of intensities and the pooled distribution of
intensities from all arrays.
With `"sum"`

and `"upperquartile"`

, it computes the sum or
the 75 percent quantile. Subsequently, it calls `boxplotOutliers`

on these values to identify the outlying arrays.

`boxplotOutliers`

uses a criterion similar to that used in
`boxplot.stats`

to
detect outliers in a set of real numbers. The main difference is that
in `boxplotOutliers`

, only the outliers to the right
(i.e. extraordinarily large values) are detected.

For `outliers`

, an object of class `outlierDetection`

.
For `boxplotOutliers`

, a list with two elements:
`thresh`

, the threshold against which `x`

was compared, and
`outliers`

, an integer vector of indices.

Wolfgang Huber

Bioconductor-mirror/arrayQualityMetrics documentation built on July 28, 2017, 5:20 a.m.

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