Whole genome analysis for QTL/association enrichment
Running...
Version: Enrich S: beta v0.8
Data:
Number of meat/fat color traits:
2
Number of QTL / associations found:
4,861
Number of chromosomes where QTL / associations are found:
19
Chi-squared (χ2) test: are meat/fat color traits over-represented on some chromosomes?
Chromosomes
Total χ2
df
p-values
FDR *
Size of χ2
Chromosome X
461.00534
18
1.603691e-86
1.523506e-85
Chromosome 1
4600.73790
18
9e-41
1.315385e-40
Chromosome 2
20.45894
18
0.3075828
3.437690e-01
Chromosome 3
258.49186
18
1.522431e-44
2.629654e-44
Chromosome 4
3.17650
18
0.999957
9.999570e-01
Chromosome 5
331.22752
18
1.751754e-59
5.547221e-59
Chromosome 6
127.76320
18
1.416113e-18
1.681634e-18
Chromosome 7
309.08268
18
6.50595e-55
1.545163e-54
Chromosome 8
370.97242
18
1.010120e-67
3.838456e-67
Chromosome 9
230.84324
18
6.261876e-39
8.498260e-39
Chromosome 10
457.21640
18
9.984666e-86
6.323622e-85
Chromosome 11
318.47952
18
7.519315e-57
2.040957e-56
Chromosome 12
293.73400
18
9.34315e-52
1.775199e-51
Chromosome 13
182.61818
18
2.903298e-29
3.677511e-29
Chromosome 14
305.98168
18
2.830657e-54
5.975831e-54
Chromosome 15
15.02590
18
0.660188
6.968651e-01
Chromosome 16
31556.30260
18
9e-41
1.315385e-40
Chromosome 17
384.72104
18
1.395216e-70
6.627276e-70
Chromosome 18
476.31742
18
9.844002e-90
1.870360e-88
Chi-squared (χ2) test: Which of the 2 meat/fat color traits are over-represented in the QTLdb
Traits
Total χ2
df
p-values
FDR *
Size of χ2
Fat color
14.83386
1
0.0001174085
0.000234817
Meat color
0.00303
1
0.9561023
0.956102300
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.:
19
χ2
=
40704.156340
Number of traits:
2
df
=
18
Number of QTLs:
4,861
p-value
=
0
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.