Whole genome analysis for QTL/association enrichment
Running...
Version: Enrich S: beta v0.8
Data:
Number of colostrum production traits:
7
Number of QTL / associations found:
64
Number of chromosomes where QTL / associations are found:
15
Chi-squared (χ2) test: are colostrum production traits over-represented on some chromosomes?
Chromosomes
Total χ2
df
p-values
FDR *
Size of χ2
Chromosome 1
0.88228
14
0.9999996
9.999996e-01
Chromosome 2
8.42919
14
0.8657903
9.999996e-01
Chromosome 3
8.42919
14
0.8657903
9.999996e-01
Chromosome 4
2.63228
14
0.999566
9.999996e-01
Chromosome 5
17.50728
14
0.2301509
9.999996e-01
Chromosome 6
0.88228
14
0.9999996
9.999996e-01
Chromosome 10
4.92919
14
0.986774
9.999996e-01
Chromosome 11
8.42919
14
0.8657903
9.999996e-01
Chromosome 13
8.42919
14
0.8657903
9.999996e-01
Chromosome 15
0.88228
14
0.9999996
9.999996e-01
Chromosome 17
0.11669
14
0.998329325823115
9.999996e-01
Chromosome 18
8.42919
14
0.8657903
9.999996e-01
Chromosome 20
12.25728
14
0.5856496
9.999996e-01
Chromosome 21
266.00728
14
1.389921e-48
2.084881e-47
Chromosome 22
17.50728
14
0.2301509
9.999996e-01
Chi-squared (χ2) test: Which of the 7 colostrum production traits are over-represented in the QTLdb
Traits
Total χ2
df
p-values
FDR *
Size of χ2
Colostrum albumin concentration
34.32697
6
5.81669e-06
6.786138e-06
Colostrum immunoglobulin A concentration
35.40001
6
3.604783e-06
6.308370e-06
Colostrum immunoglobulin G concentration
44.00001
6
7.392057e-08
2.587220e-07
Colostrum immunoglobulin G1 concentration
50.33336
6
4.030425e-09
2.821298e-08
Colostrum immunoglobulin G2 concentration
42.95238
6
1.192020e-07
2.781380e-07
Colostrum immunoglobulin M concentration
34.48889
6
5.412112e-06
6.786138e-06
Colostrum quantity
21.95241
6
0.001235153
1.235153e-03
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
=
365.750070
Number of traits:
7
df
=
84
Number of QTLs:
64
p-value
=
8.15951e-37
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.