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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"gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_2724.vcf.gz --id UKB-b:18105 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2724.txt.gz --cohort_cases 153820 --cohort_controls 57294 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
"file_date": "2019-09-12T19:36:25.322364",
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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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18105/UKB-b-18105_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18105/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18105/UKB-b-18105_data.vcf.gz ...
Read summary statistics for 9329877 SNPs.
Dropped 10459 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1288005 SNPs remain.
After merging with regression SNP LD, 1288005 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0196 (0.0032)
Lambda GC: 1.1163
Mean Chi^2: 1.1281
Intercept: 1.0443 (0.0068)
Ratio: 0.3457 (0.0527)
Analysis finished at Thu Oct 17 14:42:05 2019
Total time elapsed: 1.0m:46.58sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9487,
"inflation_factor": 1.0966,
"mean_EFFECT": -0.0001,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 12,
"n_p_sig": 572,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 114673,
"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": 1288005,
"ldsc_nsnp_merge_regression_ld": 1288005,
"ldsc_observed_scale_h2_beta": 0.0196,
"ldsc_observed_scale_h2_se": 0.0032,
"ldsc_intercept_beta": 1.0443,
"ldsc_intercept_se": 0.0068,
"ldsc_lambda_gc": 1.1163,
"ldsc_mean_chisq": 1.1281,
"ldsc_ratio": 0.3458
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| 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 | 0 | 1.0000000 | 3 | 58 | 0 | 9319471 | 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 | N | 9329877 | 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 | 8.633638e+00 | 5.753689e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.881659e+07 | 5.630970e+07 | 828.0000000 | 3.250552e+07 | 6.940141e+07 | 1.145463e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.156000e-04 | 5.251400e-03 | -0.0670471 | -1.941500e-03 | -3.190000e-05 | 1.847500e-03 | 6.955150e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.962400e-03 | 3.151200e-03 | 0.0013174 | 1.588800e-03 | 2.515300e-03 | 5.428000e-03 | 4.699170e-02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.851732e-01 | 2.924909e-01 | 0.0000000 | 2.300001e-01 | 4.799997e-01 | 7.400005e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.851734e-01 | 2.924664e-01 | 0.0000000 | 2.284725e-01 | 4.793080e-01 | 7.387339e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.132630e-01 | 2.577479e-01 | 0.0022760 | 1.726200e-02 | 9.177900e-02 | 3.347370e-01 | 9.977240e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 114673 | 0.9877091 | NA | NA | NA | NA | NA | NA | NA | 2.143366e-01 | 2.495333e-01 | 0.0000000 | 1.457670e-02 | 1.104230e-01 | 3.348640e-01 | 1.000000e+00 | ▇▂▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 49298 | rs200943160 | T | C | 0.0012522 | 0.0024309 | 0.6100002 | 0.6064606 | 0.623233 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | -0.0001077 | 0.0024014 | 0.9599999 | 0.9642311 | 0.400954 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | -0.0017648 | 0.0038467 | 0.6499995 | 0.6463844 | 0.103705 | 0.0277556 | NA |
| 1 | 91536 | rs6702460 | G | T | -0.0017118 | 0.0023670 | 0.4700002 | 0.4695685 | 0.456870 | 0.4207270 | NA |
| 1 | 234313 | rs8179466 | C | T | 0.0013813 | 0.0046772 | 0.7700005 | 0.7677405 | 0.074441 | NA | NA |
| 1 | 534192 | rs6680723 | C | T | -0.0011760 | 0.0027025 | 0.6600001 | 0.6634520 | 0.241470 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | -0.0020372 | 0.0033712 | 0.5500004 | 0.5456478 | 0.913426 | NA | NA |
| 1 | 693731 | rs12238997 | A | G | -0.0000041 | 0.0022631 | 1.0000000 | 0.9985672 | 0.116857 | 0.1417730 | NA |
| 1 | 705882 | rs72631875 | G | A | 0.0075312 | 0.0033233 | 0.0230001 | 0.0234423 | 0.067083 | 0.0315495 | NA |
| 1 | 706368 | rs55727773 | A | G | -0.0010725 | 0.0016777 | 0.5199996 | 0.5226469 | 0.514845 | 0.2751600 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51219006 | rs28729663 | G | A | -0.0032469 | 0.0020274 | 0.1100001 | 0.1092670 | 0.138076 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | -0.0029547 | 0.0026314 | 0.2599998 | 0.2614978 | 0.073794 | 0.0654952 | NA |
| 22 | 51219704 | rs147475742 | G | A | -0.0076686 | 0.0035221 | 0.0290001 | 0.0294569 | 0.042032 | 0.0473243 | NA |
| 22 | 51221190 | rs369304721 | G | A | -0.0021969 | 0.0035212 | 0.5300002 | 0.5326833 | 0.049748 | NA | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0028288 | 0.0026329 | 0.2800000 | 0.2826392 | 0.073319 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | -0.0007892 | 0.0030915 | 0.8000000 | 0.7985008 | 0.054668 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | -0.0011737 | 0.0031064 | 0.7099994 | 0.7055595 | 0.054294 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0027986 | 0.0026418 | 0.2900000 | 0.2894478 | 0.073209 | 0.0730831 | NA |
| 22 | 51232488 | rs376461333 | A | G | -0.0033284 | 0.0062090 | 0.5900000 | 0.5919173 | 0.020073 | NA | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0027171 | 0.0016148 | 0.0920005 | 0.0924513 | 0.297674 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.623233 ES:SE:LP:AF:ID 0.00125223:0.00243089:0.21467:0.623233:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400954 ES:SE:LP:AF:ID -0.000107691:0.00240142:0.0177288:0.400954:rs2462492
1 86028 rs114608975 T C . PASS AF=0.103705 ES:SE:LP:AF:ID -0.00176484:0.00384672:0.187087:0.103705:rs114608975
1 91536 rs6702460 G T . PASS AF=0.45687 ES:SE:LP:AF:ID -0.00171177:0.002367:0.327902:0.45687:rs6702460
1 234313 rs8179466 C T . PASS AF=0.074441 ES:SE:LP:AF:ID 0.00138134:0.00467725:0.113509:0.074441:rs8179466
1 534192 rs6680723 C T . PASS AF=0.24147 ES:SE:LP:AF:ID -0.00117599:0.00270248:0.180456:0.24147:rs6680723
1 546697 rs12025928 A G . PASS AF=0.913426 ES:SE:LP:AF:ID -0.00203721:0.00337122:0.259637:0.913426:rs12025928
1 693731 rs12238997 A G . PASS AF=0.116857 ES:SE:LP:AF:ID -4.06382e-06:0.00226308:-0:0.116857:rs12238997
1 705882 rs72631875 G A . PASS AF=0.067083 ES:SE:LP:AF:ID 0.00753118:0.00332334:1.63827:0.067083:rs72631875
1 706368 rs12029736 A G . PASS AF=0.514845 ES:SE:LP:AF:ID -0.00107253:0.00167774:0.283997:0.514845:rs12029736
1 714596 rs149887893 T C . PASS AF=0.033098 ES:SE:LP:AF:ID -0.00436926:0.00422681:0.522879:0.033098:rs149887893
1 715265 rs12184267 C T . PASS AF=0.036692 ES:SE:LP:AF:ID -0.00443464:0.00384251:0.60206:0.036692:rs12184267
1 715367 rs12184277 A G . PASS AF=0.03681 ES:SE:LP:AF:ID -0.00435331:0.00382839:0.585027:0.03681:rs12184277
1 717485 rs12184279 C A . PASS AF=0.036501 ES:SE:LP:AF:ID -0.00441788:0.00385647:0.60206:0.036501:rs12184279
1 717587 rs144155419 G A . PASS AF=0.016423 ES:SE:LP:AF:ID 0.00131894:0.00593627:0.0861861:0.016423:rs144155419
1 720381 rs116801199 G T . PASS AF=0.037035 ES:SE:LP:AF:ID -0.00460578:0.00381407:0.638272:0.037035:rs116801199
1 721290 rs12565286 G C . PASS AF=0.037133 ES:SE:LP:AF:ID -0.0046515:0.00380111:0.657577:0.037133:rs12565286
1 722670 rs116030099 T C . PASS AF=0.100878 ES:SE:LP:AF:ID 0.00275377:0.00277399:0.49485:0.100878:rs116030099
1 723891 rs2977670 G C . PASS AF=0.958968 ES:SE:LP:AF:ID 0.00528339:0.00366304:0.823909:0.958968:rs2977670
1 724849 rs12126395 C A . PASS AF=0.031453 ES:SE:LP:AF:ID -0.0018367:0.00663745:0.107905:0.031453:rs12126395
1 725060 rs865924913 A T . PASS AF=0.053368 ES:SE:LP:AF:ID -0.00197107:0.00528347:0.148742:0.053368:rs865924913
1 726794 rs28454925 C G . PASS AF=0.036678 ES:SE:LP:AF:ID -0.00406261:0.003823:0.537602:0.036678:rs28454925
1 729632 rs116720794 C T . PASS AF=0.037016 ES:SE:LP:AF:ID -0.00343438:0.00378805:0.443698:0.037016:rs116720794
1 729679 rs4951859 C G . PASS AF=0.842523 ES:SE:LP:AF:ID 0.000729953:0.00196179:0.148742:0.842523:rs4951859
1 730087 rs148120343 T C . PASS AF=0.056101 ES:SE:LP:AF:ID -0.000698775:0.00317699:0.0809219:0.056101:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122922 ES:SE:LP:AF:ID 0.000512798:0.00214583:0.091515:0.122922:rs58276399
1 732989 rs369030935 C T . PASS AF=0.025553 ES:SE:LP:AF:ID 0.00141922:0.00530135:0.102373:0.025553:rs369030935
1 734349 rs141242758 T C . PASS AF=0.12214 ES:SE:LP:AF:ID 0.000651688:0.00214667:0.119186:0.12214:rs141242758
1 736289 rs79010578 T A . PASS AF=0.132962 ES:SE:LP:AF:ID -0.000530529:0.00211556:0.09691:0.132962:rs79010578
1 736689 rs181876450 T C . PASS AF=0.01129 ES:SE:LP:AF:ID 0.000948172:0.007656:0.0457575:0.01129:rs181876450
1 740284 rs61770167 C T . PASS AF=0.005827 ES:SE:LP:AF:ID 0.00138349:0.00980457:0.05061:0.005827:rs61770167
1 752478 rs146277091 G A . PASS AF=0.036934 ES:SE:LP:AF:ID -0.00414454:0.00374989:0.568636:0.036934:rs146277091
1 752566 rs3094315 G A . PASS AF=0.838276 ES:SE:LP:AF:ID 0.000944933:0.00189943:0.207608:0.838276:rs3094315
1 752721 rs3131972 A G . PASS AF=0.837896 ES:SE:LP:AF:ID 0.0009851:0.00189767:0.221849:0.837896:rs3131972
1 753405 rs3115860 C A . PASS AF=0.869165 ES:SE:LP:AF:ID 9.97447e-05:0.00203517:0.0177288:0.869165:rs3115860
1 753541 rs2073813 G A . PASS AF=0.130501 ES:SE:LP:AF:ID -0.000294397:0.00203995:0.05061:0.130501:rs2073813
1 754063 rs12184312 G T . PASS AF=0.03739 ES:SE:LP:AF:ID -0.00392241:0.00368855:0.537602:0.03739:rs12184312
1 754105 rs12184325 C T . PASS AF=0.037656 ES:SE:LP:AF:ID -0.0037647:0.00366398:0.522879:0.037656:rs12184325
1 754182 rs3131969 A G . PASS AF=0.868491 ES:SE:LP:AF:ID 0.0002274:0.00203158:0.0409586:0.868491:rs3131969
1 754192 rs3131968 A G . PASS AF=0.868571 ES:SE:LP:AF:ID 0.000220363:0.00203239:0.0409586:0.868571:rs3131968
1 754211 rs12184313 G A . PASS AF=0.037605 ES:SE:LP:AF:ID -0.00383291:0.0036799:0.522879:0.037605:rs12184313
1 754334 rs3131967 T C . PASS AF=0.86849 ES:SE:LP:AF:ID 0.000202385:0.00203151:0.0362122:0.86849:rs3131967
1 754433 rs150578204 G A . PASS AF=0.005114 ES:SE:LP:AF:ID -0.0150736:0.0104677:0.823909:0.005114:rs150578204
1 754458 rs142682604 G T . PASS AF=0.005083 ES:SE:LP:AF:ID -0.0151916:0.0104924:0.823909:0.005083:rs142682604
1 754503 rs3115859 G A . PASS AF=0.83733 ES:SE:LP:AF:ID 0.00108527:0.00189215:0.244125:0.83733:rs3115859
1 754629 rs10454459 A G . PASS AF=0.037617 ES:SE:LP:AF:ID -0.00380309:0.00368551:0.522879:0.037617:rs10454459
1 754964 rs3131966 C T . PASS AF=0.837971 ES:SE:LP:AF:ID 0.00106688:0.00189747:0.244125:0.837971:rs3131966
1 755240 rs181660517 T G . PASS AF=0.013777 ES:SE:LP:AF:ID -0.00885159:0.00663165:0.744727:0.013777:rs181660517
1 755435 rs184270342 T G . PASS AF=0.005566 ES:SE:LP:AF:ID 0.0033414:0.0102204:0.130768:0.005566:rs184270342
1 755775 rs3131965 A G . PASS AF=0.839143 ES:SE:LP:AF:ID 0.00124492:0.00192295:0.283997:0.839143:rs3131965