Whole genome analysis for QTL/association enrichment
Running...
Version: Enrich S: beta v0.8
Data:
Number of semen quality traits:
5
Number of QTL / associations found:
37
Number of chromosomes where QTL / associations are found:
15
Chi-squared (χ2) test: are semen quality traits over-represented on some chromosomes?
Chromosomes
Total χ2
df
p-values
FDR *
Size of χ2
Chromosome 1
41.65765
14
0.0001400733
0.002101100
Chromosome 3
13.00900
14
0.5258151
0.998329326
Chromosome 4
4.36035
14
0.9928787
0.998329326
Chromosome 5
0.44145
14
0.998329325823115
0.998329326
Chromosome 6
0.44145
14
0.998329325823115
0.998329326
Chromosome 8
4.36035
14
0.9928787
0.998329326
Chromosome 9
25.30630
14
0.03166122
0.237459150
Chromosome 12
4.36035
14
0.9928787
0.998329326
Chromosome 15
4.36035
14
0.9928787
0.998329326
Chromosome 19
4.36035
14
0.9928787
0.998329326
Chromosome 20
0.44145
14
0.998329325823115
0.998329326
Chromosome 21
0.57660
14
0.998329325823115
0.998329326
Chromosome 22
0.57660
14
0.998329325823115
0.998329326
Chromosome 26
4.36035
14
0.9928787
0.998329326
Chromosome 28
4.36035
14
0.9928787
0.998329326
Chi-squared (χ2) test: Which of the 5 semen quality traits are over-represented in the QTLdb
Traits
Total χ2
df
p-values
FDR *
Size of χ2
Number of progressively motile sperm
16.16428
4
0.002806463
0.004085440
Semen volume
15.82145
4
0.003268352
0.004085440
Sperm concentration
20.41074
4
0.0004142765
0.002071382
Sperm count
14.98004
4
0.004742795
0.004742795
Sperm progressive motility
17.69713
4
0.001414132
0.003535330
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.:
15
χ2
=
112.972950
Number of traits:
5
df
=
56
Number of QTLs:
37
p-value
=
1.009652e-05
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.
Running...
