|
Haplotyping level
|
GBS
|
MACE
|
WGS
|
---|
RMSE
|
SNP level
|
–
|
0.07
|
0.15
|
GH level
|
0.11
|
0.04
|
0.03
|
MH level
|
0.06
|
0.04
|
0.03
|
Contig level
|
0.03
|
0.04
|
0.03
|
Stat test negative binomial level
|
SNP level
|
–
|
0.67
|
0.02
|
GH level
|
0.35
|
0.99
|
0.57
|
MH level
|
0.47
|
0.94
|
0.39
|
Contig level
|
0.59
|
0.28
|
0.46
|
Stat test zero inflated level
|
SNP level
|
–
|
0.68
|
0.09
|
GH level
|
0.15
|
0.64
|
0.64
|
MH level
|
0.62
|
0.67
|
0.63
|
Contig level
|
0.44
|
0.62
|
0.53
|
Pearson Residual width
|
SNP level
|
–
|
3.85%
|
3.37%
|
GH level
|
3.78%
|
3.70%
|
3.49%
|
MH level
|
3.77%
|
3.89%
|
3.40%
|
Contig level
|
3.60%
|
3.92%
|
3.95%
|
Pearson correlation
|
SNP level
|
–
|
0.79
|
0.93
|
GH level
|
0
|
0.9
|
0.97
|
MH level
|
0.83
|
0.93
|
0.96
|
Contig level
|
0.94
|
0.88
|
0.95
|
Median read coverage of haplotypes in pool sample per KASP marker
|
SNP level
|
41
|
51
|
7
|
GH level
|
51
|
82
|
607
|
MH level
|
575
|
158
|
7749
|
Contig level
|
10,122
|
917
|
81,186
|
Count of matched KASP markers to pool seq
|
SNP level
|
1
|
19
|
11
|
GH level
|
15
|
16
|
15
|
MH level
|
17
|
17
|
17
|
Contig level
|
19
|
19
|
19
|
- Genotyping by sequencing (GBS), MACE transcriptome sequencing (MACE), and whole-genome re-sequencing (WGS) (P1 sample). Haplotyping levels are: SNP—single nucleotide polymorphism (single data point); GH—gene-based haplotype (origin gene annotation model); MH—marker-based haplotype (origin from 9KiSelect genotyping chip); Contig – Contig haplotypes, in the text referred to as CH, windows of 100 kb size. RMSE = root mean square error of pool to individual genotyping on different haplotyping levels for three different genotyping approaches. Stat test rows present the probability value, where p < 0.05 indicates significant variations between individual and pool genotyping. Pearson residual width—average deviation of pool haplotype allele frequency estimate to individual genotyping. Pearson correlation—correlation of pool to individual genotyping, for each haplotyping level and genotyping approach