Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/9dd0abd6-c30f-4f12-9541-e7db8e61136c/call-vcf/inputs/-261044475/upload.txt.gz --id ieu-b-4836 --json /data/cromwell-executions/qc/9dd0abd6-c30f-4f12-9541-e7db8e61136c/call-vcf/inputs/-261044475/ieu-b-4836_data.json --ref /data/cromwell-executions/qc/9dd0abd6-c30f-4f12-9541-e7db8e61136c/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/9dd0abd6-c30f-4f12-9541-e7db8e61136c/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4836/ieu-b-4836.vcf.gz --alias alias.txt; 1.3.0",
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}
LDSC
*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call:
./ldsc.py \
--h2 /data/cromwell-executions/qc/9dd0abd6-c30f-4f12-9541-e7db8e61136c/call-ldsc/inputs/-261044475/ieu-b-4836.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4836/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 10:00:33 2022
Reading summary statistics from /data/cromwell-executions/qc/9dd0abd6-c30f-4f12-9541-e7db8e61136c/call-ldsc/inputs/-261044475/ieu-b-4836.vcf.gz ...
Read summary statistics for 7209997 SNPs.
Dropped 19875 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1201526 SNPs remain.
After merging with regression SNP LD, 1201526 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1377 (0.0089)
Lambda GC: 1.4069
Mean Chi^2: 1.4362
Intercept: 1.1735 (0.0092)
Ratio: 0.3977 (0.0211)
Analysis finished at Wed Jan 5 10:02:16 2022
Total time elapsed: 1.0m:42.66sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.3726,
"mean_EFFECT": -0.0003,
"n": 102112,
"n_snps": 7210025,
"n_clumped_hits": 24,
"n_p_sig": 527,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 7210025,
"n_miss_AF_reference": 48695,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1201526,
"ldsc_nsnp_merge_regression_ld": 1201526,
"ldsc_observed_scale_h2_beta": 0.1377,
"ldsc_observed_scale_h2_se": 0.0089,
"ldsc_intercept_beta": 1.1735,
"ldsc_intercept_se": 0.0092,
"ldsc_lambda_gc": 1.4069,
"ldsc_mean_chisq": 1.4362,
"ldsc_ratio": 0.3978
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | FALSE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | FALSE |
| ldsc_intercept_beta | FALSE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations for<*>column.
se_n metrics
n_est: Estimated sample size value, \(\widehat{n}\).ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expectratio_se_nto be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).
LDSC metrics
Metrics from LD regression
ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.ldsc_observed_scale_h2_{beta,se}Coefficient value and SE for total observed scale h2.ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.ldsc_lambda_gc: Lambda GC statistics.ldsc_mean_chisq: Mean \(\chi^2\) statistics.ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).
Flags
When a metric needs attention, the flag should return TRUE.
af_correlation:abs(af_correlation)< 0.7.inflation_factor:inflation_factor> 1.2.n:n(max reported sample size) < 10000.is_snpid_non_unique: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_sum<*>:r2_sum<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| skim_type | skim_variable | n_missing | complete_rate | character.min | character.max | character.empty | character.n_unique | character.whitespace | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 11 | 0.9999985 | 3 | 58 | 0 | 7209987 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 7210025 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.638468e+00 | 5.748373e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.887007e+07 | 5.638044e+07 | 8.2800e+02 | 3.243537e+07 | 6.946602e+07 | 1.147268e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -2.807000e-04 | 1.090190e-02 | -1.0950e-01 | -5.600000e-03 | -2.000000e-04 | 5.200000e-03 | 1.324000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.233300e-03 | 4.810800e-03 | 4.0000e-03 | 4.700000e-03 | 6.100000e-03 | 1.020000e-02 | 2.800000e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.491242e-01 | 3.000722e-01 | 0.0000e+00 | 1.774999e-01 | 4.294000e-01 | 7.076003e-01 | 1.000000e+00 | ▇▆▆▅▅ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.490885e-01 | 3.001052e-01 | 0.0000e+00 | 1.773893e-01 | 4.291204e-01 | 7.076605e-01 | 1.000000e+00 | ▇▆▅▅▅ |
| numeric | AF_reference | 48695 | 0.9932462 | NA | NA | NA | NA | NA | NA | NA | 2.663141e-01 | 2.522568e-01 | 1.9970e-04 | 5.930510e-02 | 1.809110e-01 | 4.147360e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 9.471564e+04 | 9.955105e+03 | 6.1273e+04 | 9.385900e+04 | 9.865800e+04 | 1.015540e+05 | 1.021120e+05 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 693731 | rs12238997 | A | G | -0.0080 | 0.0084 | 0.3387997 | 0.3409038 | NA | 0.141773 | 61428 |
| 1 | 731718 | rs142557973 | T | C | -0.0071 | 0.0083 | 0.3886002 | 0.3923177 | NA | 0.154353 | 61428 |
| 1 | 734349 | rs141242758 | T | C | -0.0074 | 0.0083 | 0.3723000 | 0.3726255 | NA | 0.152556 | 61428 |
| 1 | 736289 | rs79010578 | T | A | -0.0037 | 0.0081 | 0.6448994 | 0.6478219 | NA | 0.139577 | 62093 |
| 1 | 752566 | rs3094315 | G | A | 0.0052 | 0.0075 | 0.4911001 | 0.4881004 | NA | 0.718251 | 61286 |
| 1 | 753541 | rs2073813 | G | A | -0.0081 | 0.0079 | 0.3064997 | 0.3052139 | NA | 0.301917 | 62755 |
| 1 | 766007 | rs61768174 | A | C | -0.0043 | 0.0086 | 0.6199005 | 0.6170751 | NA | 0.091254 | 61428 |
| 1 | 768253 | rs2977608 | A | C | 0.0015 | 0.0063 | 0.8059001 | 0.8118072 | NA | 0.489417 | 62093 |
| 1 | 768448 | rs12562034 | G | A | 0.0073 | 0.0090 | 0.4130000 | 0.4173019 | NA | 0.191893 | 62093 |
| 1 | 769223 | rs60320384 | C | G | -0.0087 | 0.0080 | 0.2775000 | 0.2768159 | NA | 0.191294 | 62197 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51198906 | rs6010079 | G | A | -0.0002 | 0.0105 | 0.9813000 | 0.9848031 | NA | 0.0421326 | 65299 |
| 22 | 51202748 | rs9616963 | A | G | -0.0026 | 0.0105 | 0.8009000 | 0.8044292 | NA | 0.0391374 | 65299 |
| 22 | 51208537 | rs72619593 | G | A | -0.0086 | 0.0082 | 0.2941000 | 0.2942792 | NA | 0.1142170 | 62093 |
| 22 | 51208568 | rs148425445 | G | T | -0.0146 | 0.0114 | 0.2006998 | 0.2002984 | NA | 0.1160140 | 69370 |
| 22 | 51210289 | rs112565862 | C | T | -0.0112 | 0.0083 | 0.1743998 | 0.1772093 | NA | 0.1018370 | 62093 |
| 22 | 51211031 | rs9616968 | A | G | 0.0043 | 0.0108 | 0.6866999 | 0.6905210 | NA | 0.0373403 | 65299 |
| 22 | 51213613 | rs34726907 | C | T | -0.0085 | 0.0082 | 0.2963002 | 0.2999291 | NA | 0.1727240 | 64843 |
| 22 | 51216564 | rs9616970 | T | C | -0.0088 | 0.0081 | 0.2775997 | 0.2772933 | NA | 0.1563500 | 64843 |
| 22 | 51222100 | rs114553188 | G | T | -0.0198 | 0.0119 | 0.0966407 | 0.0961393 | NA | 0.0880591 | 64443 |
| 22 | 51223637 | rs375798137 | G | A | -0.0172 | 0.0119 | 0.1489999 | 0.1483517 | NA | 0.0788738 | 64443 |
bcf preview
1 693731 rs12238997 A G . PASS . ES:SE:LP:SS:ID -0.008:0.0084:0.470057:61428:rs12238997
1 731718 rs58276399 T C . PASS . ES:SE:LP:SS:ID -0.0071:0.0083:0.410497:61428:rs58276399
1 734349 rs141242758 T C . PASS . ES:SE:LP:SS:ID -0.0074:0.0083:0.429107:61428:rs141242758
1 736289 rs1254887344 T A . PASS . ES:SE:LP:SS:ID -0.0037:0.0081:0.190508:62093:rs1254887344
1 752566 rs3094315 G A . PASS . ES:SE:LP:SS:ID 0.0052:0.0075:0.30883:61286:rs3094315
1 753541 rs1388595942 G A . PASS . ES:SE:LP:SS:ID -0.0081:0.0079:0.51357:62755:rs1388595942
1 766007 rs61768174 A C . PASS . ES:SE:LP:SS:ID -0.0043:0.0086:0.207678:61428:rs61768174
1 768253 rs2977608 A C . PASS . ES:SE:LP:SS:ID 0.0015:0.0063:0.0937188:62093:rs2977608
1 768448 rs12562034 G A . PASS . ES:SE:LP:SS:ID 0.0073:0.009:0.38405:62093:rs12562034
1 769223 rs60320384 C G . PASS . ES:SE:LP:SS:ID -0.0087:0.008:0.556737:62197:rs60320384
1 771967 rs59066358 G A . PASS . ES:SE:LP:SS:ID -0.0098:0.008:0.66615:62755:rs59066358
1 777232 rs112618790 C T . PASS . ES:SE:LP:SS:ID 0.0097:0.0094:0.514279:62093:rs112618790
1 778745 rs1055606 A G . PASS . ES:SE:LP:SS:ID -0.0089:0.008:0.571217:62197:rs1055606
1 779322 rs4040617 A G . PASS . ES:SE:LP:SS:ID -0.0087:0.008:0.555487:62197:rs4040617
1 781845 rs1391043716 A G . PASS . ES:SE:LP:SS:ID -0.0061:0.0087:0.31399:61428:rs1391043716
1 782981 rs6594026 C T . PASS . ES:SE:LP:SS:ID -0.0096:0.008:0.635637:62197:rs6594026
1 787606 rs3863622 G T . PASS . ES:SE:LP:SS:ID -0.0098:0.008:0.651111:62197:rs3863622
1 790465 rs61768207 G A . PASS . ES:SE:LP:SS:ID -0.0116:0.0089:0.72262:61428:rs61768207
1 791191 rs111818025 G A . PASS . ES:SE:LP:SS:ID -0.01:0.008:0.668573:62197:rs111818025
1 791853 rs6684487 G A . PASS . ES:SE:LP:SS:ID 0.0086:0.0095:0.440093:62093:rs6684487
1 794332 rs12127425 G A . PASS . ES:SE:LP:SS:ID 0.0057:0.0103:0.236947:61428:rs12127425
1 795222 rs12131377 C G . PASS . ES:SE:LP:SS:ID 0.0063:0.0102:0.26825:61428:rs12131377
1 795988 rs59380221 C T . PASS . ES:SE:LP:SS:ID -0.0056:0.0081:0.306625:61428:rs59380221
1 796100 rs12132398 C T . PASS . ES:SE:LP:SS:ID 0.0053:0.0102:0.216597:61428:rs12132398
1 796375 rs1338880683 T C . PASS . ES:SE:LP:SS:ID -0.011:0.0082:0.741123:61986:rs1338880683
1 797281 rs1347695410 G C . PASS . ES:SE:LP:SS:ID 0.0043:0.0102:0.173213:61428:rs1347695410
1 797325 rs1338750774 T C . PASS . ES:SE:LP:SS:ID 0.0043:0.0102:0.173213:61428:rs1338750774
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID -0.0028:0.0068:0.164246:87290:rs58013264
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID -0.0041:0.0055:0.334982:89282:rs10900604
1 798801 rs12132517 G A . PASS . ES:SE:LP:SS:ID 0.0045:0.0102:0.181774:61428:rs12132517
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID -0.0031:0.0054:0.248259:93153:rs11240777
1 799499 rs147634896 T C . PASS . ES:SE:LP:SS:ID 0.0029:0.0102:0.108463:61428:rs147634896
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID -0.0018:0.0069:0.102758:86625:rs61768212
1 801661 rs12132974 C T . PASS . ES:SE:LP:SS:ID 0.0022:0.0103:0.080399:61428:rs12132974
1 801680 rs12134490 A C . PASS . ES:SE:LP:SS:ID 0.0017:0.0103:0.0607304:61428:rs12134490
1 801858 rs17276806 C T . PASS . ES:SE:LP:SS:ID 0.0021:0.0103:0.0769633:61428:rs17276806
1 802856 rs139867617 C T . PASS . ES:SE:LP:SS:ID 0.0017:0.0103:0.0626828:61428:rs139867617
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID -0.0019:0.0069:0.104191:86625:rs7526310
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID 0.0067:0.0053:0.672028:87955:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID 0.0073:0.0053:0.75721:87955:rs1247187939
1 809876 rs57181708 A G . PASS . ES:SE:LP:SS:ID -0.0091:0.0091:0.497573:61428:rs57181708
1 810286 rs28410559 G A . PASS . ES:SE:LP:SS:ID -0.008:0.0083:0.474566:61428:rs28410559
1 812743 rs6605064 C T . PASS . ES:SE:LP:SS:ID -0.0092:0.0083:0.56671:61428:rs6605064
1 824398 rs7538305 A C . PASS . ES:SE:LP:SS:ID 0.0011:0.0081:0.0475466:61428:rs7538305
1 830181 rs28444699 A G . PASS . ES:SE:LP:SS:ID 0.0077:0.006:0.6874:62093:rs28444699
1 831489 rs4970385 C T . PASS . ES:SE:LP:SS:ID 0.0103:0.006:1.07702:62093:rs4970385
1 831909 rs9697642 C T . PASS . ES:SE:LP:SS:ID 0.0103:0.006:1.06485:62093:rs9697642
1 832066 rs9697380 G C . PASS . ES:SE:LP:SS:ID 0.0101:0.006:1.04278:62093:rs9697380
1 832318 rs4500250 C A . PASS . ES:SE:LP:SS:ID 0.0102:0.006:1.05394:62093:rs4500250
1 832398 rs4553118 T C . PASS . ES:SE:LP:SS:ID 0.0123:0.0061:1.34361:62093:rs4553118