Whole genome analysis for QTL/association enrichment
Running...
Version: Enrich S: beta v0.8
Data:
Number of fertility traits:
2
Number of QTL / associations found:
84
Number of chromosomes where QTL / associations are found:
20
Chi-squared (χ2) test: are fertility traits over-represented on some chromosomes?
Chromosomes
Total χ2
df
p-values
FDR *
Size of χ2
Chromosome 1
2.30476
19
0.9999988
9.999988e-01
Chromosome 2
4.87620
19
0.9995264
9.999988e-01
Chromosome 3
2.30476
19
0.9999988
9.999988e-01
Chromosome 4
36.87620
19
0.008222627
5.481751e-02
Chromosome 5
0.68572
19
0.998329325823115
9.999988e-01
Chromosome 6
55.54286
19
1.91874e-05
1.918740e-04
Chromosome 7
0.68572
19
0.998329325823115
9.999988e-01
Chromosome 8
0.01904
19
0.998329325823115
9.999988e-01
Chromosome 9
2.30476
19
0.9999988
9.999988e-01
Chromosome 10
2.30476
19
0.9999988
9.999988e-01
Chromosome 13
104.30476
19
8.833983e-14
1.766797e-12
Chromosome 14
4.87620
19
0.9995264
9.999988e-01
Chromosome 15
4.87620
19
0.9995264
9.999988e-01
Chromosome 17
0.30476
19
0.998329325823115
9.999988e-01
Chromosome 18
0.68572
19
0.998329325823115
9.999988e-01
Chromosome 20
2.30476
19
0.9999988
9.999988e-01
Chromosome 22
2.30476
19
0.9999988
9.999988e-01
Chromosome 23
2.30476
19
0.9999988
9.999988e-01
Chromosome 24
4.87620
19
0.9995264
9.999988e-01
Chromosome 25
4.87620
19
0.9995264
9.999988e-01
Chi-squared (χ2) test: Which of the 2 fertility traits are over-represented in the QTLdb
Traits
Total χ2
df
p-values
FDR *
Size of χ2
female fertility
35.43867
1
2.63209e-09
5.264180e-09
male fertility
17.71932
1
2.560132e-05
2.560132e-05
Correlations found between some of these traits for your reference
No correlation data found on these traits
Overall Test
Data
Chi'Square Test
Fisher's Exact Test
Number of chrom.:
20
χ2
=
239.619100
Number of traits:
2
df
=
19
Number of QTLs:
84
p-value
=
3.88691e-40
FOOT NOTE: * : FDR is short for "false
discovery rate", representing the expected proportion of type I errors. A type I
error is where you incorrectly reject the null hypothesis, i.e. you get a false
positive. It's statistical definition is FDR = E(V/R | R > 0) P(R > 0), where
V = Number of Type I errors (false positives); R = Number of rejected hypotheses.
Benjamini–Hochberg procedure is a practical way to estimate FDR.