Whole genome analysis for QTL/association enrichment
Running...
Version: Enrich S: beta v0.8
Data:
Number of conductivity & impedance traits:
2
Number of QTL / associations found:
423
Number of chromosomes where QTL / associations are found:
19
Chi-squared (χ2) test: are conductivity & impedance traits over-represented on some chromosomes?
Chromosomes
Total χ2
df
p-values
FDR *
Size of χ2
Chromosome X
40.61616
18
0.001719264
1.088867e-02
Chromosome 1
5.37738
18
0.998139
9.999752e-01
Chromosome 2
0.27100
18
0.998329325823115
9.999752e-01
Chromosome 3
18.27572
18
0.4376328
8.315023e-01
Chromosome 4
6.13388
18
0.9956237
9.999752e-01
Chromosome 5
9.46248
18
0.9480477
9.999752e-01
Chromosome 6
1679.63270
18
9e-41
1.710000e-39
Chromosome 7
7.70834
18
0.9826692
9.999752e-01
Chromosome 8
196.22844
18
5.680567e-32
5.396539e-31
Chromosome 9
4.73908
18
0.9992108
9.999752e-01
Chromosome 10
29.96366
18
0.0378013
1.197041e-01
Chromosome 11
15.80292
18
0.6062994
9.999752e-01
Chromosome 12
36.88566
18
0.005423169
2.060804e-02
Chromosome 13
7.70834
18
0.9826692
9.999752e-01
Chromosome 14
18.27572
18
0.4376328
8.315023e-01
Chromosome 15
2.95658
18
0.9999752
9.999752e-01
Chromosome 16
20.92820
18
0.2830509
6.722459e-01
Chromosome 17
26.77218
18
0.0833688
2.262867e-01
Chromosome 18
36.88566
18
0.005423169
2.060804e-02
Chi-squared (χ2) test: Which of the 2 conductivity & impedance traits are over-represented in the QTLdb
Traits
Total χ2
df
p-values
FDR *
Size of χ2
Muscle conductivity
6.08008
1
0.01367146
1.367146e-02
Muscle impedance
49.83023
1
1.676411e-12
3.352822e-12
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
=
2164.624100
Number of traits:
2
df
=
18
Number of QTLs:
423
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.