plink --file mydata --matrix
creates two files
plink.mdist
plink.pdist

which contain the IBS distances and p-value tests for all pairs of
individuals.
HINT See the FAQ
page for instructions on using using R to visualise these results.

**IBS clustering**
To perform the clustering:
plink --file mydata --cluster
The output is sent to four files
plink.cluster0
plink.cluster1
plink.cluster2
plink.cluster3

that contain similar information but in different formats. The
The `cluster0` file contains information on the merging process.
The `cluster1` file contains information on the final solution, listed by cluster: e.g. for 4 individuals in 3 clusters:
0 A
1 B C
2 D

The `cluster2` file contains the same information but listed by individual:
A 0
B 1
C 1
D 2

The `cluster3` file is in the same format as `cluster2` but contains all solutions, each column is a solution: e.g.
A 0 0 0 0
B 1 1 1 0
C 2 1 1 0
D 3 2 0 0

i.e. reading from left to right, we start with N clusters of size 1; moving right, we end with 1 cluster size N.

**Constraints on clustering**
The extra constraints that can be placed on the clustering, as options
that go along with the `--cluster` option. (Note:
`--matrix` and `--cluster` can be performed at the same
time)
To only merge clusters that do not contain individuals differing at a
certain p-value:
--merge 0.0001
To ensure that every cluster has at least one case and one control:
--cc
To set the maximum cluster size to a certain value, e.g. 2:
--mc 2
Putting these together with some of the association options
will probably be the most common usuage of this cluster option. Some
of these are illustrated in the association
analysis section.
WARNING! The calculation of p-values for all pairs
assumes that all SNPs are uncorrelated, i.e. not too close together. (The
basic IBS clustering does not make this assumption). Therefore, if this
option is used, it should only be performed on a subset of independent
SNPs.
HINT Also, this test is susceptible to non-random missingness
in genotypes, particularly if heterozygotes are more likely to be dropped.
It is therefore good practice to set the `--geno` very high for
this analysis, e.g. so only SNPs with virtually complete genotyping are
included.
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