findHighestChis {beadarray} | R Documentation

## Find least randomly distributed beads

### Description

Function for finding which bead types on an array are least randomly positioned.

### Usage

    findHighestChis(BLData, array, limit = 14)

### Arguments

`BLData` | an BeadLevelList object containing bead level data
`array` | numeric value for which array we want to use
`limit` | numeric value which determines the threshold value for the chi-statistic.

### Details

The $chi^2$ statistic is defined as:

begin{center}

$chi^2 = sum^k_{i=1} (O_i - E_i)^2 / E_i$ end{center}

where O and E are vectors of length 8 defining the observed and expected number of beads in each section respectively. This provides a means of systematically testing the distribution of every bead type on a given array and we can record each bead type with a sufficiently high value of $chi^2$.

If the value for a particular bead type is found to be greater than 'limit' then we add the ProbeID for that bead type to a list which we later return.

Default is to use 14 as the limit as this is the 95th quantile for the chi-square distribution in question

### Value

numeric vector giving ProbeIDs for all bead types on the array which give a chi-statistic > 'limit'

### Author(s)

Mark Dunning

### Examples

    data(BLData)

    ##Default setting is to find all bead types with a chi-statistic greater than 14

    findHighestChis(BLData, 1)

    ##Now find all beads with chi-statistic for their distribution greater than 16

    findHighestChis(BLData, 1, limit=16)

    ##ProbeIDs returned by the function can be examined in more detail

    plotBeadLocations(BLData, ProbeID=278, array=1)

    probeDiagnostics(BLData, 278, 1)

[Package beadarray version 1.0.0 Index]