Download Haplo Stats (version 1.5.0) Statistical Methods for

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p-val is the asymptotic χ21 p-value, calculated from the square of the score statistic.
5.2
Binary Trait Analysis
Let us assume that ”low” responders are of primary interest, so we create a binary trait that has
values of 1 when resp.cat is ”low”, and 0 otherwise. Then in haplo.score specify the parameter
trait.type=”binomial”.
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# scores, binary trait
y.bin <- 1*(resp.cat=="low")
score.bin <- haplo.score(y.bin, geno, trait.type="binomial",
x.adj = NA, min.count=5,
haplo.effect="additive", locus.label=label,
miss.val=0, simulate=FALSE)
print(score.bin, nlines=10)
-------------------------------------------------------------------------------Haplotype Effect Model: additive
--------------------------------------------------------------------------------------------------------------------------------------------------------------Global Score Statistics
-------------------------------------------------------------------------------global-stat = 33.70125, df = 18, p-val = 0.01371
-------------------------------------------------------------------------------Haplotype-specific Scores
--------------------------------------------------------------------------------
[1,]
[2,]
[3,]
[4,]
[5,]
[6,]
[7,]
[8,]
[9,]
[10,]
5.3
DQB
62
51
63
21
32
32
51
31
31
51
DRB
2
1
13
7
4
4
1
11
11
1
B
7
35
7
7
7
62
27
35
51
44
Hap-Freq
0.05098
0.03018
0.01655
0.01246
0.01678
0.02349
0.01505
0.01754
0.01137
0.01731
Hap-Score
-2.19387
-1.58421
-1.56008
-1.47495
-1.00091
-0.6799
-0.66509
-0.5838
-0.43721
0.00826
p-val
0.02824
0.11315
0.11874
0.14023
0.31687
0.49657
0.50599
0.55936
0.66196
0.99341
Ordinal Trait Analysis
To create an ordinal trait, here we convert resp.cat (described above) to numeric values, y.ord (with
levels 1, 2, 3). For haplo.score, use y.ord as the response variable, and set the parameter trait.type
= ”ordinal”.
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