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-10807/UKB-b-10807_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10807/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-10807/UKB-b-10807_data.vcf.gz ...
Read summary statistics for 7429313 SNPs.
Dropped 5032 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, 1274589 SNPs remain.
After merging with regression SNP LD, 1274589 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0104 (0.0014)
Lambda GC: 1.1264
Mean Chi^2: 1.1271
Intercept: 1.0413 (0.0071)
Ratio: 0.3248 (0.056)
Analysis finished at Thu Oct 17 14:41:44 2019
Total time elapsed: 1.0m:25.98s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9392,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 1.8844e-06,
    "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": 68792,
    "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": 1274589,
    "ldsc_nsnp_merge_regression_ld": 1274589,
    "ldsc_observed_scale_h2_beta": 0.0104,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0413,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.1264,
    "ldsc_mean_chisq": 1.1271,
    "ldsc_ratio": 0.3249
}

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 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 7424303 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 7429313 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 8.663961e+00 5.763756e+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 7.864177e+07 5.643957e+07 828.0000000 3.218438e+07 6.906358e+07 1.145216e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.900000e-06 1.204600e-03 -0.0120301 -6.145000e-04 -4.000000e-07 6.133000e-04 1.123310e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.026000e-03 5.385000e-04 0.0005239 5.979000e-04 7.951000e-04 1.315500e-03 5.683100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.826964e-01 2.929481e-01 0.0000001 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.826970e-01 2.929229e-01 0.0000001 2.246666e-01 4.767864e-01 7.363413e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.622371e-01 2.607423e-01 0.0123460 4.800100e-02 1.602690e-01 4.132750e-01 9.876540e-01 ▇▂▂▁▁
numeric AF_reference 68792 0.9907405 NA NA NA NA NA NA NA 2.610005e-01 2.525971e-01 0.0000000 5.351440e-02 1.737220e-01 4.073480e-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 -0.0006414 0.0009647 0.5099998 0.5061485 0.623825 0.7821490 NA
1 54676 rs2462492 C T -0.0000511 0.0009549 0.9599999 0.9572985 0.400479 NA NA
1 86028 rs114608975 T C -0.0014092 0.0015268 0.3599996 0.3559931 0.103575 0.0277556 NA
1 91536 rs6702460 G T 0.0015382 0.0009405 0.1000000 0.1019334 0.456967 0.4207270 NA
1 234313 rs8179466 C T -0.0016934 0.0018555 0.3599996 0.3614272 0.074507 NA NA
1 534192 rs6680723 C T -0.0010002 0.0010747 0.3500000 0.3520255 0.241001 NA NA
1 546697 rs12025928 A G -0.0006414 0.0013396 0.6300007 0.6320682 0.913399 NA NA
1 693731 rs12238997 A G 0.0017594 0.0009006 0.0510000 0.0507437 0.116298 0.1417730 NA
1 705882 rs72631875 G A 0.0024770 0.0013190 0.0599998 0.0603758 0.067369 0.0315495 NA
1 706368 rs55727773 A G -0.0006204 0.0006672 0.3500000 0.3524921 0.515799 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0010538 0.0008049 0.1900002 0.1904522 0.137877 0.2052720 NA
22 51219387 rs9616832 T C -0.0004924 0.0010446 0.6400000 0.6373472 0.073725 0.0654952 NA
22 51219704 rs147475742 G A 0.0002843 0.0014000 0.8400000 0.8390908 0.041946 0.0473243 NA
22 51221190 rs369304721 G A 0.0001330 0.0013970 0.9199999 0.9241761 0.049733 NA NA
22 51221731 rs115055839 T C -0.0005305 0.0010452 0.6100002 0.6117585 0.073222 0.0625000 NA
22 51222100 rs114553188 G T -0.0013426 0.0012307 0.2800000 0.2753321 0.054409 0.0880591 NA
22 51223637 rs375798137 G A -0.0013160 0.0012366 0.2900000 0.2872424 0.054040 0.0788738 NA
22 51229805 rs9616985 T C -0.0004635 0.0010490 0.6600001 0.6585790 0.073057 0.0730831 NA
22 51232488 rs376461333 A G -0.0017129 0.0024703 0.4899999 0.4880568 0.020023 NA NA
22 51237063 rs3896457 T C -0.0002884 0.0006416 0.6499995 0.6530276 0.298139 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623825 ES:SE:LP:AF:ID  -0.000641369:0.000964687:0.29243:0.623825:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400479 ES:SE:LP:AF:ID  -5.11294e-05:0.000954905:0.0177288:0.400479:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103575 ES:SE:LP:AF:ID  -0.00140925:0.00152677:0.443698:0.103575:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456967 ES:SE:LP:AF:ID  0.00153824:0.000940502:1:0.456967:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074507 ES:SE:LP:AF:ID  -0.00169342:0.0018555:0.443698:0.074507:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241001 ES:SE:LP:AF:ID  -0.00100017:0.00107468:0.455932:0.241001:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913399 ES:SE:LP:AF:ID  -0.00064141:0.00133957:0.200659:0.913399:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116298 ES:SE:LP:AF:ID  0.0017594:0.000900575:1.29243:0.116298:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067369 ES:SE:LP:AF:ID  0.00247704:0.00131895:1.22185:0.067369:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515799 ES:SE:LP:AF:ID  -0.000620354:0.000667215:0.455932:0.515799:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033008 ES:SE:LP:AF:ID  0.000946532:0.00168135:0.244125:0.033008:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036643 ES:SE:LP:AF:ID  0.000877552:0.0015267:0.244125:0.036643:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036753 ES:SE:LP:AF:ID  0.000665093:0.0015211:0.180456:0.036753:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036456 ES:SE:LP:AF:ID  0.000957471:0.00153204:0.275724:0.036456:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016437 ES:SE:LP:AF:ID  0.00320518:0.00235758:0.769551:0.016437:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036993 ES:SE:LP:AF:ID  0.000847354:0.00151505:0.236572:0.036993:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03709  ES:SE:LP:AF:ID  0.000983505:0.00150991:0.29243:0.03709:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10127  ES:SE:LP:AF:ID  -0.00175111:0.00110016:0.958607:0.10127:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  -0.00035214:0.00145673:0.091515:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031476 ES:SE:LP:AF:ID  -0.00328823:0.00264215:0.677781:0.031476:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053303 ES:SE:LP:AF:ID  0.000691307:0.00210062:0.130768:0.053303:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  0.00102016:0.00151971:0.30103:0.036606:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036918 ES:SE:LP:AF:ID  0.000912942:0.00150604:0.267606:0.036918:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843206 ES:SE:LP:AF:ID  -0.00114117:0.000780278:0.853872:0.843206:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055916 ES:SE:LP:AF:ID  0.00059676:0.00126356:0.19382:0.055916:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122294 ES:SE:LP:AF:ID  0.00130386:0.000854202:0.886057:0.122294:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  0.000391613:0.00209866:0.0705811:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121542 ES:SE:LP:AF:ID  0.001348:0.000854554:0.958607:0.121542:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132343 ES:SE:LP:AF:ID  0.00132317:0.000842174:0.920819:0.132343:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036845 ES:SE:LP:AF:ID  0.000931346:0.00149052:0.275724:0.036845:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83892  ES:SE:LP:AF:ID  -0.00113497:0.000755711:0.886057:0.83892:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838546 ES:SE:LP:AF:ID  -0.00110255:0.000754855:0.853872:0.838546:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869799 ES:SE:LP:AF:ID  -0.00125329:0.0008102:0.920819:0.869799:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129855 ES:SE:LP:AF:ID  0.00121085:0.000811837:0.853872:0.129855:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037342 ES:SE:LP:AF:ID  0.000637:0.00146559:0.180456:0.037342:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037584 ES:SE:LP:AF:ID  0.000699285:0.00145638:0.200659:0.037584:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869141 ES:SE:LP:AF:ID  -0.00118561:0.000808583:0.853872:0.869141:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869239 ES:SE:LP:AF:ID  -0.00120677:0.000808898:0.853872:0.869239:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037544 ES:SE:LP:AF:ID  0.000592978:0.00146261:0.161151:0.037544:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869142 ES:SE:LP:AF:ID  -0.00120227:0.000808567:0.853872:0.869142:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837995 ES:SE:LP:AF:ID  -0.00107563:0.000752755:0.823909:0.837995:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037554 ES:SE:LP:AF:ID  0.000506457:0.00146472:0.136677:0.037554:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83863  ES:SE:LP:AF:ID  -0.00110392:0.000754888:0.853872:0.83863:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013745 ES:SE:LP:AF:ID  -0.00263687:0.00263779:0.49485:0.013745:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.83974  ES:SE:LP:AF:ID  -0.00114321:0.000765085:0.853872:0.83974:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869425 ES:SE:LP:AF:ID  -0.00125417:0.000807679:0.920819:0.869425:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86897  ES:SE:LP:AF:ID  -0.00124589:0.000805644:0.920819:0.86897:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86792  ES:SE:LP:AF:ID  -0.00112898:0.000804061:0.79588:0.86792:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  -0.001241:0.000806305:0.920819:0.869115:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869124 ES:SE:LP:AF:ID  -0.00124399:0.000806367:0.920819:0.869124:rs4951862