Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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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/dev/ukb-d-import/processed/ukb-d-22613_0/ukb-d-22613_0.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22613_0/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 16:43:36 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22613_0/ukb-d-22613_0.vcf.gz ...
Read summary statistics for 13566571 SNPs.
Dropped 12680 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.017 (0.0055)
Lambda GC: 1.0245
Mean Chi^2: 1.0281
Intercept: 0.9983 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:46:17 2019
Total time elapsed: 2.0m:40.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0231,
    "mean_EFFECT": -2.9461e-06,
    "n": 88636,
    "n_snps": 13566571,
    "n_clumped_hits": 0,
    "n_p_sig": 6,
    "n_mono": 0,
    "n_ns": 1251234,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 563000,
    "n_est": 88956.9642,
    "ratio_se_n": 1.0018,
    "mean_diff": -0,
    "ratio_diff": 16.4557,
    "sd_y_est1": 0.1969,
    "sd_y_est2": 0.1973,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.017,
    "ldsc_observed_scale_h2_se": 0.0055,
    "ldsc_intercept_beta": 0.9983,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0245,
    "ldsc_mean_chisq": 1.0281,
    "ldsc_ratio": -0.0605
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
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 between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations 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 expect ratio_se_n to 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 of diff and the mean of diff2 (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<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 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: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 13554555 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57046 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33332 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051436e+00 6.184992e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902432e+07 5.591631e+07 3.02000e+02 3.292812e+07 7.013376e+07 1.148612e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.900000e-06 5.469300e-03 -7.91069e-02 -1.416100e-03 2.300000e-05 1.493500e-03 6.804890e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.914700e-03 3.772600e-03 7.71600e-04 1.118600e-03 2.057300e-03 5.621200e-03 1.894560e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.962347e-01 2.894442e-01 0.00000e+00 2.449390e-01 4.950887e-01 7.464539e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.962329e-01 2.894452e-01 0.00000e+00 2.449361e-01 4.950873e-01 7.464527e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910720e-01 2.544759e-01 1.00000e-03 7.500400e-03 6.030440e-02 2.957870e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563000 0.9585009 NA NA NA NA NA 1.965268e-01 2.471466e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.863600e+04 0.000000e+00 8.86360e+04 8.863600e+04 8.863600e+04 8.863600e+04 8.863600e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0018116 0.0016338 0.2674847 0.2674827 0.1114080 0.1894970 88636
1 693731 rs12238997 A G -0.0023640 0.0015474 0.1265820 0.1265786 0.1163920 0.1417730 88636
1 707522 rs371890604 G C -0.0016755 0.0017392 0.3353583 0.3353542 0.0978656 0.1293930 88636
1 717587 rs144155419 G A 0.0030179 0.0041506 0.4671765 0.4671729 0.0157506 0.0045926 88636
1 723329 rs189787166 A T -0.0255478 0.0120911 0.0346083 0.0346057 0.0017788 0.0003994 88636
1 730087 rs148120343 T C -0.0009382 0.0021444 0.6617638 0.6617623 0.0570097 0.0127796 88636
1 731718 rs142557973 T C -0.0021246 0.0014687 0.1480110 0.1480084 0.1222310 0.1543530 88636
1 732032 rs61770163 A C -0.0016425 0.0015662 0.2943120 0.2943088 0.1219180 0.1555510 88636
1 734349 rs141242758 T C -0.0021304 0.0014698 0.1472211 0.1472180 0.1214630 0.1525560 88636
1 740284 rs61770167 C T 0.0001119 0.0067414 0.9867620 0.9867620 0.0057429 0.0023962 88636
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0028734 0.0017175 0.0943170 0.0943136 0.0552063 0.0309934 88636
23 154923374 rs111332691 T A 0.0005703 0.0018696 0.7603333 0.7603328 0.0448294 0.0116556 88636
23 154925045 rs509981 C T -0.0003849 0.0009001 0.6689059 0.6689051 0.2447590 0.3634440 88636
23 154925895 rs538470 C T -0.0004459 0.0009202 0.6279889 0.6279876 0.2412380 0.3634440 88636
23 154927581 rs644138 G A -0.0010625 0.0008468 0.2095748 0.2095732 0.3003780 0.4635760 88636
23 154929412 rs557132 C T -0.0004061 0.0009003 0.6519931 0.6519917 0.2446130 0.3568210 88636
23 154929637 rs35185538 CT C -0.0004307 0.0009402 0.6469042 0.6469029 0.2289200 0.3011920 88636
23 154929952 rs4012982 CAA C -0.0007359 0.0009475 0.4373479 0.4373465 0.2385370 0.3165560 88636
23 154930230 rs781880 A G -0.0004796 0.0009000 0.5941184 0.5941162 0.2450670 0.3618540 88636
23 154930487 rs781879 T A -0.0009908 0.0030460 0.7449755 0.7449743 0.0197331 0.1263580 88636

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111408 ES:SE:LP:AF:SS:ID   -0.00181163:0.00163375:0.572701:0.111408:88636:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116392 ES:SE:LP:AF:SS:ID   -0.002364:0.00154739:0.897628:0.116392:88636:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978656    ES:SE:LP:AF:SS:ID   -0.00167551:0.00173919:0.474491:0.0978656:88636:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157506    ES:SE:LP:AF:SS:ID   0.00301786:0.00415062:0.330519:0.0157506:88636:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177883   ES:SE:LP:AF:SS:ID   -0.0255478:0.0120911:1.46082:0.00177883:88636:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570097    ES:SE:LP:AF:SS:ID   -0.000938157:0.00214445:0.179297:0.0570097:88636:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122231 ES:SE:LP:AF:SS:ID   -0.00212461:0.00146869:0.829706:0.122231:88636:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121918 ES:SE:LP:AF:SS:ID   -0.00164252:0.00156622:0.531192:0.121918:88636:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121463 ES:SE:LP:AF:SS:ID   -0.00213037:0.0014698:0.83203:0.121463:88636:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00574292   ES:SE:LP:AF:SS:ID   0.000111855:0.00674143:0.00578758:0.00574292:88636:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00182982   ES:SE:LP:AF:SS:ID   0.00169907:0.0128678:0.0481998:0.00182982:88636:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869051 ES:SE:LP:AF:SS:ID   0.00321711:0.00144578:1.58383:0.869051:88636:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00161562   ES:SE:LP:AF:SS:ID   -0.0120409:0.0126967:0.464763:0.00161562:88636:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12358  ES:SE:LP:AF:SS:ID   -0.00280146:0.00143341:1.29536:0.12358:88636:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14311  ES:SE:LP:AF:SS:ID   -0.0028113:0.00141871:1.32305:0.14311:88636:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123719 ES:SE:LP:AF:SS:ID   -0.00279629:0.0014313:1.29462:0.123719:88636:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870012 ES:SE:LP:AF:SS:ID   0.00287077:0.00139452:1.40303:0.870012:88636:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874648 ES:SE:LP:AF:SS:ID   0.00272628:0.00141714:1.26453:0.874648:88636:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129411 ES:SE:LP:AF:SS:ID   -0.00285605:0.00139889:1.38522:0.129411:88636:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0357642    ES:SE:LP:AF:SS:ID   -0.00105464:0.00255671:0.167508:0.0357642:88636:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869654 ES:SE:LP:AF:SS:ID   0.00283139:0.00139334:1.37523:0.869654:88636:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869732 ES:SE:LP:AF:SS:ID   0.00281656:0.00139395:1.36322:0.869732:88636:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86965  ES:SE:LP:AF:SS:ID   0.00283468:0.00139328:1.37778:0.86965:88636:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00530984   ES:SE:LP:AF:SS:ID   -0.0127433:0.00696105:1.17292:0.00530984:88636:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00527473   ES:SE:LP:AF:SS:ID   -0.0129066:0.00697843:1.19118:0.00527473:88636:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00565822   ES:SE:LP:AF:SS:ID   -0.00814112:0.00685769:0.628616:0.00565822:88636:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869652 ES:SE:LP:AF:SS:ID   0.00291228:0.00139045:1.44105:0.869652:88636:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126798 ES:SE:LP:AF:SS:ID   -0.00308774:0.0014194:1.52864:0.126798:88636:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86919  ES:SE:LP:AF:SS:ID   0.00302012:0.00138692:1.53105:0.86919:88636:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868559 ES:SE:LP:AF:SS:ID   0.00277373:0.00138598:1.34328:0.868559:88636:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869336 ES:SE:LP:AF:SS:ID   0.0029142:0.00138818:1.44619:0.869336:88636:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869342 ES:SE:LP:AF:SS:ID   0.00291675:0.00138827:1.44802:0.869342:88636:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869344 ES:SE:LP:AF:SS:ID   0.00291568:0.00138828:1.44717:0.869344:88636:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869812 ES:SE:LP:AF:SS:ID   0.00293158:0.00139193:1.4535:0.869812:88636:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991245    ES:SE:LP:AF:SS:ID   -0.00210864:0.00161974:0.714501:0.0991245:88636:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00651101   ES:SE:LP:AF:SS:ID   -0.00849038:0.0062408:0.760233:0.00651101:88636:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873787 ES:SE:LP:AF:SS:ID   0.00278486:0.00141246:1.31288:0.873787:88636:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863188 ES:SE:LP:AF:SS:ID   0.00302384:0.00138578:1.53598:0.863188:88636:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868596 ES:SE:LP:AF:SS:ID   0.00302183:0.00139927:1.51133:0.868596:88636:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865494 ES:SE:LP:AF:SS:ID   0.0030227:0.00139947:1.51168:0.865494:88636:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993712    ES:SE:LP:AF:SS:ID   -0.00339933:0.00167624:1.37092:0.0993712:88636:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870771 ES:SE:LP:AF:SS:ID   0.00289449:0.00141547:1.38862:0.870771:88636:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870771 ES:SE:LP:AF:SS:ID   0.00289447:0.00141547:1.38861:0.870771:88636:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870768 ES:SE:LP:AF:SS:ID   0.00289445:0.00141547:1.38858:0.870768:88636:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871141 ES:SE:LP:AF:SS:ID   0.00288075:0.00141615:1.37744:0.871141:88636:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126401 ES:SE:LP:AF:SS:ID   -0.00289225:0.00141772:1.38357:0.126401:88636:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106    ES:SE:LP:AF:SS:ID   -0.00330635:0.0015407:1.49655:0.106:88636:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854538 ES:SE:LP:AF:SS:ID   0.00251591:0.0013852:1.15907:0.854538:88636:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00169026   ES:SE:LP:AF:SS:ID   -0.0208916:0.0121283:1.07072:0.00169026:88636:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839456 ES:SE:LP:AF:SS:ID   -0.000836869:0.00136919:0.266755:0.839456:88636:rs376645387