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/afbb0c63-22cb-486a-897a-163f8de3411d/call-vcf/inputs/-261044507/upload.txt.gz --id ieu-b-4825 --json /data/cromwell-executions/qc/afbb0c63-22cb-486a-897a-163f8de3411d/call-vcf/inputs/-261044507/ieu-b-4825_data.json --ref /data/cromwell-executions/qc/afbb0c63-22cb-486a-897a-163f8de3411d/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/afbb0c63-22cb-486a-897a-163f8de3411d/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4825/ieu-b-4825.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/afbb0c63-22cb-486a-897a-163f8de3411d/call-ldsc/inputs/-261044507/ieu-b-4825.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4825/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 08:43:27 2022
Reading summary statistics from /data/cromwell-executions/qc/afbb0c63-22cb-486a-897a-163f8de3411d/call-ldsc/inputs/-261044507/ieu-b-4825.vcf.gz ...
Read summary statistics for 7227274 SNPs.
Dropped 35625 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, 1182558 SNPs remain.
After merging with regression SNP LD, 1182558 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0617 (0.0491)
Lambda GC: 1.0146
Mean Chi^2: 1.0153
Intercept: 1.0043 (0.0062)
Ratio: 0.2819 (0.4039)
Analysis finished at Wed Jan 5 08:45:05 2022
Total time elapsed: 1.0m:38.39sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.0174,
"mean_EFFECT": -0.0004,
"n": 9000,
"n_snps": 7227329,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 252547,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 7227329,
"n_miss_AF_reference": 146003,
"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": 1182558,
"ldsc_nsnp_merge_regression_ld": 1182558,
"ldsc_observed_scale_h2_beta": 0.0617,
"ldsc_observed_scale_h2_se": 0.0491,
"ldsc_intercept_beta": 1.0043,
"ldsc_intercept_se": 0.0062,
"ldsc_lambda_gc": 1.0146,
"ldsc_mean_chisq": 1.0153,
"ldsc_ratio": 0.281
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| 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 | 13 | 0.9999982 | 3 | 58 | 0 | 7227213 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 43 | 0 | 14891 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 44 | 0 | 5406 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 7227329 | 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 | 8.649468e+00 | 5.755541e+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 | 7.899276e+07 | 5.639184e+07 | 3.0200e+02 | 3.266801e+07 | 6.969762e+07 | 1.147510e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -4.348000e-04 | 2.134214e-01 | -1.9116e+00 | -1.101000e-01 | 2.000000e-04 | 1.089000e-01 | 2.466200e+00 | ▁▂▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.885128e-01 | 9.627220e-02 | 8.0300e-02 | 1.172000e-01 | 1.466000e-01 | 2.285000e-01 | 7.521000e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.974665e-01 | 2.893504e-01 | 1.0000e-07 | 2.462000e-01 | 4.962997e-01 | 7.483004e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.974666e-01 | 2.893504e-01 | 1.0000e-07 | 2.462089e-01 | 4.962732e-01 | 7.482734e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF_reference | 146003 | 0.9797985 | NA | NA | NA | NA | NA | NA | NA | 2.851437e-01 | 2.502800e-01 | 1.9970e-04 | 7.987220e-02 | 2.064700e-01 | 4.404950e-01 | 1.000000e+00 | ▇▃▂▂▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.105477e+03 | 1.043829e+03 | 5.2830e+03 | 7.200000e+03 | 8.701000e+03 | 9.000000e+03 | 9.000000e+03 | ▁▃▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 797440 | rs58013264 | T | C | 0.0245 | 0.1703 | 0.8856999 | 0.8856080 | NA | 0.189497 | 7797 |
| 1 | 798400 | rs10900604 | A | G | 0.0724 | 0.1417 | 0.6089996 | 0.6093940 | NA | 0.410543 | 7942 |
| 1 | 798959 | rs11240777 | G | A | 0.0736 | 0.1417 | 0.6031995 | 0.6034768 | NA | 0.409944 | 7942 |
| 1 | 801467 | rs61768212 | G | C | 0.0098 | 0.1701 | 0.9538000 | 0.9540568 | NA | 0.193091 | 7797 |
| 1 | 804759 | rs7526310 | C | T | -0.0035 | 0.1705 | 0.9837000 | 0.9836223 | NA | 0.193890 | 7797 |
| 1 | 808223 | rs4951933 | G | C | -0.1585 | 0.1521 | 0.2976001 | 0.2973757 | NA | 0.452077 | 6349 |
| 1 | 808631 | rs11240779 | G | A | -0.0465 | 0.1396 | 0.7390997 | 0.7390629 | NA | 0.453474 | 7649 |
| 1 | 808928 | rs11240780 | C | T | -0.0391 | 0.1396 | 0.7796003 | 0.7794116 | NA | 0.452276 | 7649 |
| 1 | 845274 | rs112856858 | G | T | -0.0368 | 0.1566 | 0.8142999 | 0.8142137 | NA | 0.374002 | 6349 |
| 1 | 845635 | rs117086422 | C | T | -0.0941 | 0.1414 | 0.5060006 | 0.5057384 | NA | 0.158546 | 7942 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51172460 | rs5770824 | T | C | 0.1620 | 0.4725 | 0.7316999 | 0.7317059 | NA | 0.0684904 | 6349 |
| 22 | 51177257 | rs73174437 | C | T | -0.3110 | 0.3771 | 0.4095001 | 0.4095335 | NA | 0.0091853 | 6349 |
| 22 | 51178607 | rs6010067 | G | C | 0.1120 | 0.4845 | 0.8171000 | 0.8171857 | NA | 0.0814696 | 6349 |
| 22 | 51180878 | rs6010069 | A | G | -0.0541 | 0.1727 | 0.7539994 | 0.7540831 | NA | 0.1589460 | 6349 |
| 22 | 51180959 | rs6010070 | A | G | -0.0542 | 0.1727 | 0.7537998 | 0.7536433 | NA | 0.2056710 | 6349 |
| 22 | 51181685 | rs34756634 | G | A | -0.1311 | 0.1953 | 0.5020997 | 0.5020454 | NA | 0.7118610 | 6349 |
| 22 | 51181687 | rs9616955 | A | T | 0.1562 | 0.2760 | 0.5714997 | 0.5714332 | NA | 0.0485224 | 6349 |
| 22 | 51181759 | rs13056621 | A | G | -0.1916 | 0.1835 | 0.2965002 | 0.2964198 | NA | 0.6761180 | 8290 |
| 22 | 51182090 | rs28516879 | G | A | 0.0802 | 0.2307 | 0.7282995 | 0.7281123 | NA | 0.0467252 | 8145 |
| 22 | 51185848 | rs3865764 | G | A | -0.0888 | 0.3079 | 0.7728995 | 0.7730365 | NA | 0.9776360 | 6349 |
bcf preview
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID 0.0245:0.1703:0.0527134:7797:rs58013264
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID 0.0724:0.1417:0.215383:7942:rs10900604
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID 0.0736:0.1417:0.219539:7942:rs11240777
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID 0.0098:0.1701:0.0205427:7797:rs61768212
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID -0.0035:0.1705:0.00713733:7797:rs7526310
1 808223 rs1557576983 G C . PASS . ES:SE:LP:SS:ID -0.1585:0.1521:0.526367:6349:rs1557576983
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID -0.0465:0.1396:0.131297:7649:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID -0.0391:0.1396:0.108128:7649:rs1247187939
1 845274 rs1324283754 G T . PASS . ES:SE:LP:SS:ID -0.0368:0.1566:0.0892156:6349:rs1324283754
1 845635 rs117086422 C T . PASS . ES:SE:LP:SS:ID -0.0941:0.1414:0.295849:7942:rs117086422
1 845938 rs57760052 G A . PASS . ES:SE:LP:SS:ID -0.0809:0.1408:0.247567:7942:rs57760052
1 846078 rs778265812 C T . PASS . ES:SE:LP:SS:ID -0.0954:0.1479:0.284833:7942:rs778265812
1 846398 rs58781670 G A . PASS . ES:SE:LP:SS:ID -0.0617:0.1421:0.177636:7942:rs58781670
1 846808 rs4475691 C T . PASS . ES:SE:LP:SS:ID -0.0721:0.1477:0.203842:7942:rs4475691
1 846864 rs1269142199 G C . PASS . ES:SE:LP:SS:ID -0.0838:0.1481:0.243136:7942:rs1269142199
1 847228 rs3905286 C T . PASS . ES:SE:LP:SS:ID -0.0668:0.1452:0.190104:7942:rs3905286
1 847491 rs1158719307 G A . PASS . ES:SE:LP:SS:ID -0.0962:0.1429:0.300249:7942:rs1158719307
1 848090 rs4246505 G A . PASS . ES:SE:LP:SS:ID -0.1249:0.1434:0.416008:7942:rs4246505
1 848445 rs1156895099 G A . PASS . ES:SE:LP:SS:ID -0.1015:0.1433:0.319846:7942:rs1156895099
1 848456 rs11507767 A G . PASS . ES:SE:LP:SS:ID -0.1023:0.1433:0.322758:7942:rs11507767
1 848738 rs3829741 C T . PASS . ES:SE:LP:SS:ID -0.1231:0.1435:0.407823:7942:rs3829741
1 850062 rs28723578 A T . PASS . ES:SE:LP:SS:ID -0.0897:0.1426:0.276134:7942:rs28723578
1 850123 rs28622257 C T . PASS . ES:SE:LP:SS:ID -0.1129:0.1431:0.366431:7942:rs28622257
1 851190 rs28609852 G A . PASS . ES:SE:LP:SS:ID -0.0884:0.1427:0.271078:7942:rs28609852
1 851204 rs28552953 G C . PASS . ES:SE:LP:SS:ID -0.0771:0.1425:0.230327:7942:rs28552953
1 852664 rs28605311 C T . PASS . ES:SE:LP:SS:ID -0.0951:0.1442:0.292771:7942:rs28605311
1 852758 rs4970462 G C . PASS . ES:SE:LP:SS:ID -0.0943:0.1443:0.289629:7942:rs4970462
1 853239 rs4970380 A G . PASS . ES:SE:LP:SS:ID -0.0929:0.1443:0.284164:7942:rs4970380
1 854250 rs7537756 A G . PASS . ES:SE:LP:SS:ID -0.0727:0.1438:0.212398:7942:rs7537756
1 856436 rs34105146 TG T . PASS . ES:SE:LP:SS:ID -0.0269:0.163:0.0609302:6349:rs34105146
1 856476 rs4040605 A G . PASS . ES:SE:LP:SS:ID 0.0172:0.1191:0.0530077:7942:rs4040605
1 858040 rs4970460 C A . PASS . ES:SE:LP:SS:ID -0.1117:0.1409:0.368658:7942:rs4970460
1 858051 rs4970459 C T . PASS . ES:SE:LP:SS:ID -0.1115:0.1408:0.368252:7942:rs4970459
1 858801 rs7418179 A G . PASS . ES:SE:LP:SS:ID 0.1154:0.1346:0.407823:7942:rs7418179
1 859685 rs111572704 G A . PASS . ES:SE:LP:SS:ID -0.1011:0.1573:0.283663:6349:rs111572704
1 860416 rs61464428 G A . PASS . ES:SE:LP:SS:ID 0.1257:0.1345:0.455932:7942:rs61464428
1 860461 rs57465118 G A . PASS . ES:SE:LP:SS:ID 0.2139:0.3462:0.270268:6349:rs57465118
1 860521 rs57924093 C A . PASS . ES:SE:LP:SS:ID 0.2139:0.3462:0.270268:6349:rs57924093
1 860688 rs60837925 G A . PASS . ES:SE:LP:SS:ID 0.126:0.1345:0.45705:7942:rs60837925
1 861008 rs28521172 G C . PASS . ES:SE:LP:SS:ID 0.2139:0.3462:0.270268:6349:rs28521172
1 861630 rs2879816 G A . PASS . ES:SE:LP:SS:ID 0.124:0.1345:0.448062:7942:rs2879816
1 861808 rs13302982 A G . PASS . ES:SE:LP:SS:ID 0.2139:0.3462:0.270268:6349:rs13302982
1 862093 rs1210451934 T C . PASS . ES:SE:LP:SS:ID 0.2216:0.3459:0.282662:6349:rs1210451934
1 862124 rs13303101 A G . PASS . ES:SE:LP:SS:ID 0.2026:0.3449:0.254145:6349:rs13303101
1 862383 rs6680268 C T . PASS . ES:SE:LP:SS:ID 0.2131:0.3456:0.269622:6349:rs6680268
1 862389 rs534606253 A G . PASS . ES:SE:LP:SS:ID 0.2139:0.3462:0.270268:6349:rs534606253
1 862866 rs3892970 C T . PASS . ES:SE:LP:SS:ID 0.1038:0.1332:0.360613:7942:rs3892970
1 863124 rs4040604 G T . PASS . ES:SE:LP:SS:ID 0.2245:0.346:0.28693:6349:rs4040604
1 864002 rs1806501 G C . PASS . ES:SE:LP:SS:ID -0.0981:0.1417:0.310869:7942:rs1806501
1 864938 rs1185651409 G A . PASS . ES:SE:LP:SS:ID 0.1035:0.1321:0.363412:7942:rs1185651409