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362
Affymetrix GeneChip
®
Genotyping Analysis Software User’s Guide
enable appropriate balancing of heterozygous and homozygous
performance – larger values of K make het calls more likely and
conversely, smaller values of K decrease the tendency towards het calls.
Calling Genotypes
We call genotypes by a template-matching procedure comparing the
transformed allele signal values observed in an experiment to the
typical values (prototype) we expect for each genotype. The genotype
that is closest in typical value is the one that is assigned (a minimum
distance classifier). The approximate confidence we have in that call is
based on the ratio of the nearest prototype to the second nearest
prototype. This allows us to rank the genotype assignments by quality
and hence make the decision not to call in cases of ambiguity.
Every SNP is expected to have three genotypes, AA, AB, and BB. For
each genotype of a given SNP, a prototype (typical observed values for
that genotype, or cluster center), with some scatter of values around
the prototype, is expected. The scatter is approximated by a
multivariate normal distribution, and the careful choice of the CCS
transformation ensures that this is a good approximation. For clusters
of this type, a standard method of evaluation of the distance from the
cluster center or prototype to a test point is to use the Mahalanobis
distance. The Mahalanobis distance takes into account the variation
(and covariation) in the cluster along each axis and is defined by
sqrt[(x
−μ
) t
Σ
-1 (x
−μ
)], where
μ
is the cluster center, x is the test value,
and
Σ
is the variance-covariance matrix describing the
multidimensional normal of the cluster.
Within any experiment, transformed values x for an SNP are derived
and compared to the three cluster centers
μ
ΑΑ
,
μ
ΑΒ
,
μ
ΒΒ
with
covariance matrices
Σ
ΑΑ
,
Σ
ΑΒ
,
Σ
ΒΒ
, obtaining distances d
AA
, d
AB
,
d
BB
. We call the genotype of the SNP the genotype with the smallest
such distance. In the clustering space, each prototype consists of two
components – a center and a variance. The center component consists
of a mean Contrast and Strength for the cluster,
μ
G
= (Contrast
G
,
Strength
G
) where G denotes the genotype. The variance component is
a 2x2 variance-covariance matrix
Σ
G
= (
σ
1,1
,
σ
1,2
,
σ
2,1
,
σ
2,2
), and is
GTYPE_manual.book Page 362 Wednesday, August 2, 2006 11:31 AM