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/public/UKB-b-3759/UKB-b-3759_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3759/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3759/UKB-b-3759_data.vcf.gz ...
Read summary statistics for 8516907 SNPs.
Dropped 7156 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, 1285356 SNPs remain.
After merging with regression SNP LD, 1285356 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0084 (0.0014)
Lambda GC: 1.1541
Mean Chi^2: 1.1627
Intercept: 1.0879 (0.0072)
Ratio: 0.5398 (0.044)
Analysis finished at Thu Oct 17 14:45:23 2019
Total time elapsed: 1.0m:37.11s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9457,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 9.2408e-08,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 81222,
    "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": 1285356,
    "ldsc_nsnp_merge_regression_ld": 1285356,
    "ldsc_observed_scale_h2_beta": 0.0084,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0879,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.1541,
    "ldsc_mean_chisq": 1.1627,
    "ldsc_ratio": 0.5403
}

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 TRUE
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 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 8509783 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 8516907 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 8.652106e+00 5.761465e+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 7.875614e+07 5.637672e+07 828.0000000 3.236218e+07 6.926876e+07 1.145597e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-07 2.018800e-03 -0.0198546 -8.684000e-04 -5.000000e-07 8.644000e-04 2.198240e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.597700e-03 1.069100e-03 0.0006495 7.629000e-04 1.113500e-03 2.151400e-03 1.150650e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.796045e-01 2.940771e-01 0.0000001 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.796045e-01 2.940511e-01 0.0000001 2.201351e-01 4.723373e-01 7.342592e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.318037e-01 2.597705e-01 0.0057900 2.673700e-02 1.174960e-01 3.670040e-01 9.942100e-01 ▇▂▁▁▁
numeric AF_reference 81222 0.9904634 NA NA NA NA NA NA NA 2.314552e-01 2.517113e-01 0.0000000 2.515970e-02 1.339860e-01 3.638180e-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 0.0009410 0.0011947 0.4299995 0.4309161 0.623741 0.7821490 NA
1 54676 rs2462492 C T -0.0009440 0.0011837 0.4299995 0.4251498 0.400415 NA NA
1 86028 rs114608975 T C -0.0016997 0.0018919 0.3700002 0.3689487 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0003443 0.0011652 0.7700005 0.7676174 0.456863 0.4207270 NA
1 234313 rs8179466 C T 0.0012672 0.0022994 0.5800000 0.5815765 0.074441 NA NA
1 534192 rs6680723 C T -0.0000722 0.0013313 0.9599999 0.9567288 0.240950 NA NA
1 546697 rs12025928 A G -0.0013158 0.0016606 0.4299995 0.4281204 0.913469 NA NA
1 693731 rs12238997 A G 0.0006659 0.0011158 0.5500004 0.5506388 0.116343 0.1417730 NA
1 705882 rs72631875 G A 0.0022248 0.0016345 0.1700000 0.1734729 0.067343 0.0315495 NA
1 706368 rs55727773 A G -0.0023091 0.0008265 0.0052000 0.0052090 0.515710 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0006150 0.0009969 0.5400003 0.5372887 0.138013 0.2052720 NA
22 51219387 rs9616832 T C -0.0005090 0.0012938 0.6899999 0.6940473 0.073783 0.0654952 NA
22 51219704 rs147475742 G A -0.0016888 0.0017339 0.3300000 0.3300591 0.041973 0.0473243 NA
22 51221190 rs369304721 G A -0.0006475 0.0017308 0.7099994 0.7083249 0.049761 NA NA
22 51221731 rs115055839 T C -0.0004998 0.0012946 0.6999999 0.6994642 0.073278 0.0625000 NA
22 51222100 rs114553188 G T 0.0002021 0.0015243 0.8900000 0.8945285 0.054514 0.0880591 NA
22 51223637 rs375798137 G A 0.0002338 0.0015316 0.8800001 0.8786621 0.054143 0.0788738 NA
22 51229805 rs9616985 T C -0.0004674 0.0012994 0.7199992 0.7190414 0.073114 0.0730831 NA
22 51232488 rs376461333 A G -0.0031053 0.0030616 0.3100002 0.3104616 0.020058 NA NA
22 51237063 rs3896457 T C 0.0009901 0.0007949 0.2099999 0.2129558 0.298138 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623741 ES:SE:LP:AF:ID  0.000941007:0.00119474:0.366532:0.623741:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400415 ES:SE:LP:AF:ID  -0.000944015:0.00118369:0.366532:0.400415:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  -0.00169974:0.00189187:0.431798:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  0.000344323:0.00116525:0.113509:0.456863:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074441 ES:SE:LP:AF:ID  0.00126715:0.00229938:0.236572:0.074441:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24095  ES:SE:LP:AF:ID  -7.22366e-05:0.00133133:0.0177288:0.24095:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913469 ES:SE:LP:AF:ID  -0.00131584:0.00166055:0.366532:0.913469:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116343 ES:SE:LP:AF:ID  0.000665895:0.00111577:0.259637:0.116343:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067343 ES:SE:LP:AF:ID  0.00222482:0.00163454:0.769551:0.067343:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51571  ES:SE:LP:AF:ID  -0.00230912:0.000826511:2.284:0.51571:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033056 ES:SE:LP:AF:ID  0.00282883:0.00208205:0.769551:0.033056:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036676 ES:SE:LP:AF:ID  0.00251555:0.00189134:0.744727:0.036676:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036792 ES:SE:LP:AF:ID  0.00258715:0.00188418:0.769551:0.036792:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036486 ES:SE:LP:AF:ID  0.00245723:0.00189791:0.69897:0.036486:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01643  ES:SE:LP:AF:ID  0.00134969:0.00292263:0.19382:0.01643:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037028 ES:SE:LP:AF:ID  0.00253876:0.00187685:0.744727:0.037028:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037128 ES:SE:LP:AF:ID  0.0024874:0.00187024:0.744727:0.037128:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101209 ES:SE:LP:AF:ID  0.000795724:0.00136375:0.251812:0.101209:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959055 ES:SE:LP:AF:ID  -0.00244755:0.00180427:0.769551:0.959055:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031456 ES:SE:LP:AF:ID  7.59046e-05:0.00327463:0.00877392:0.031456:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053321 ES:SE:LP:AF:ID  -0.00103206:0.0026027:0.161151:0.053321:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036638 ES:SE:LP:AF:ID  0.00275806:0.0018826:0.853872:0.036638:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036955 ES:SE:LP:AF:ID  0.00249559:0.00186545:0.744727:0.036955:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843138 ES:SE:LP:AF:ID  -0.00151624:0.000966861:0.920819:0.843138:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055909 ES:SE:LP:AF:ID  0.000457884:0.00156578:0.113509:0.055909:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122346 ES:SE:LP:AF:ID  0.000700619:0.00105825:0.29243:0.122346:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025668 ES:SE:LP:AF:ID  -0.00491949:0.00260615:1.22915:0.025668:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121584 ES:SE:LP:AF:ID  0.000737664:0.00105869:0.309804:0.121584:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13241  ES:SE:LP:AF:ID  0.0016392:0.00104337:0.920819:0.13241:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011144 ES:SE:LP:AF:ID  0.00333657:0.00379124:0.420216:0.011144:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036869 ES:SE:LP:AF:ID  0.00263203:0.00184661:0.823909:0.036869:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838828 ES:SE:LP:AF:ID  -0.00148583:0.000936109:0.958607:0.838828:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83845  ES:SE:LP:AF:ID  -0.0014659:0.000935066:0.920819:0.83845:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869703 ES:SE:LP:AF:ID  -0.000609833:0.0010034:0.267606:0.869703:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129961 ES:SE:LP:AF:ID  0.000759817:0.00100541:0.346787:0.129961:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037381 ES:SE:LP:AF:ID  0.00242496:0.00181523:0.744727:0.037381:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037626 ES:SE:LP:AF:ID  0.00258645:0.00180371:0.823909:0.037626:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869042 ES:SE:LP:AF:ID  -0.000606833:0.00100141:0.267606:0.869042:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869142 ES:SE:LP:AF:ID  -0.000649662:0.00100181:0.283997:0.869142:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037585 ES:SE:LP:AF:ID  0.00227284:0.00181155:0.677781:0.037585:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869046 ES:SE:LP:AF:ID  -0.000598991:0.00100139:0.259637:0.869046:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8379   ES:SE:LP:AF:ID  -0.00138524:0.000932469:0.853872:0.8379:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037599 ES:SE:LP:AF:ID  0.00237767:0.00181406:0.721246:0.037599:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838532 ES:SE:LP:AF:ID  -0.00136188:0.000935085:0.823909:0.838532:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013754 ES:SE:LP:AF:ID  -0.00211467:0.00326726:0.283997:0.013754:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839656 ES:SE:LP:AF:ID  -0.00135787:0.00094779:0.823909:0.839656:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869328 ES:SE:LP:AF:ID  -0.00060542:0.00100026:0.259637:0.869328:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868878 ES:SE:LP:AF:ID  -0.000577438:0.000997781:0.251812:0.868878:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867823 ES:SE:LP:AF:ID  -0.000705855:0.000995818:0.318759:0.867823:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869019 ES:SE:LP:AF:ID  -0.000610212:0.000998581:0.267606:0.869019:rs4951929