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-11605/UKB-b-11605_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11605/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11605/UKB-b-11605_data.vcf.gz ...
Read summary statistics for 7398491 SNPs.
Dropped 4980 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, 1273992 SNPs remain.
After merging with regression SNP LD, 1273992 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0189 (0.0013)
Lambda GC: 1.1964
Mean Chi^2: 1.2086
Intercept: 1.0417 (0.007)
Ratio: 0.2 (0.0335)
Analysis finished at Thu Oct 17 14:42:20 2019
Total time elapsed: 1.0m:25.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.939,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 3.8687e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 17,
    "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": 68479,
    "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": 1273992,
    "ldsc_nsnp_merge_regression_ld": 1273992,
    "ldsc_observed_scale_h2_beta": 0.0189,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0417,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.1964,
    "ldsc_mean_chisq": 1.2086,
    "ldsc_ratio": 0.1999
}

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 7393533 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 7398491 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 8.664007e+00 5.763678e+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 7.863826e+07 5.644229e+07 828.0000000 3.218042e+07 6.905633e+07 1.145166e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.900000e-06 1.117600e-03 -0.0098252 -5.749000e-04 0.000000e+00 5.823000e-04 1.209210e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.365000e-04 4.875000e-04 0.0004812 5.487000e-04 7.276000e-04 1.198900e-03 5.227700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.740750e-01 2.957217e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.740753e-01 2.956954e-01 0.0000000 2.112296e-01 4.648548e-01 7.303312e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.631812e-01 2.606945e-01 0.0126140 4.879200e-02 1.616080e-01 4.147270e-01 9.873850e-01 ▇▂▂▁▁
numeric AF_reference 68479 0.9907442 NA NA NA NA NA NA NA 2.619140e-01 2.525586e-01 0.0000000 5.451280e-02 1.751200e-01 4.085460e-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 0.0003099 0.0008856 0.7300002 0.7263960 0.623783 0.7821490 NA
1 54676 rs2462492 C T 0.0003045 0.0008773 0.7300002 0.7285297 0.400457 NA NA
1 86028 rs114608975 T C 0.0007121 0.0014028 0.6100002 0.6117257 0.103543 0.0277556 NA
1 91536 rs6702460 G T 0.0009078 0.0008638 0.2900000 0.2932803 0.456874 0.4207270 NA
1 234313 rs8179466 C T 0.0017934 0.0017030 0.2900000 0.2923225 0.074519 NA NA
1 534192 rs6680723 C T -0.0003039 0.0009866 0.7600007 0.7580976 0.240975 NA NA
1 546697 rs12025928 A G 0.0015718 0.0012308 0.2000000 0.2015904 0.913488 NA NA
1 693731 rs12238997 A G 0.0004975 0.0008266 0.5500004 0.5473041 0.116354 0.1417730 NA
1 705882 rs72631875 G A -0.0027768 0.0012114 0.0219999 0.0218965 0.067296 0.0315495 NA
1 706368 rs55727773 A G -0.0009681 0.0006125 0.1100001 0.1140011 0.515658 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0002095 0.0007391 0.7800007 0.7768020 0.137921 0.2052720 NA
22 51219387 rs9616832 T C 0.0009275 0.0009594 0.3300000 0.3336919 0.073721 0.0654952 NA
22 51219704 rs147475742 G A 0.0017178 0.0012856 0.1800002 0.1814590 0.041945 0.0473243 NA
22 51221190 rs369304721 G A 0.0011669 0.0012833 0.3599996 0.3631859 0.049724 NA NA
22 51221731 rs115055839 T C 0.0009969 0.0009600 0.2999998 0.2990532 0.073211 0.0625000 NA
22 51222100 rs114553188 G T -0.0005774 0.0011302 0.6100002 0.6094546 0.054450 0.0880591 NA
22 51223637 rs375798137 G A -0.0006683 0.0011357 0.5600000 0.5562137 0.054078 0.0788738 NA
22 51229805 rs9616985 T C 0.0011527 0.0009635 0.2300001 0.2315241 0.073046 0.0730831 NA
22 51232488 rs376461333 A G 0.0002370 0.0022682 0.9199999 0.9167935 0.020055 NA NA
22 51237063 rs3896457 T C 0.0001563 0.0005892 0.7899998 0.7908001 0.297942 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623783 ES:SE:LP:AF:ID  0.000309905:0.000885636:0.136677:0.623783:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400457 ES:SE:LP:AF:ID  0.000304503:0.000877323:0.136677:0.400457:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103543 ES:SE:LP:AF:ID  0.000712103:0.00140285:0.21467:0.103543:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456874 ES:SE:LP:AF:ID  0.000907835:0.000863821:0.537602:0.456874:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  0.00179337:0.00170304:0.537602:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240975 ES:SE:LP:AF:ID  -0.000303866:0.000986642:0.119186:0.240975:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913488 ES:SE:LP:AF:ID  0.00157176:0.00123079:0.69897:0.913488:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  0.000497459:0.000826612:0.259637:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067296 ES:SE:LP:AF:ID  -0.00277679:0.00121143:1.65758:0.067296:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515658 ES:SE:LP:AF:ID  -0.000968101:0.000612543:0.958607:0.515658:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033001 ES:SE:LP:AF:ID  0.000383902:0.00154423:0.09691:0.033001:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036622 ES:SE:LP:AF:ID  0.000298001:0.00140257:0.0809219:0.036622:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036733 ES:SE:LP:AF:ID  0.000245833:0.00139737:0.0655015:0.036733:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036435 ES:SE:LP:AF:ID  0.000373741:0.0014074:0.102373:0.036435:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016407 ES:SE:LP:AF:ID  -0.00299407:0.00216725:0.769551:0.016407:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036977 ES:SE:LP:AF:ID  0.000271441:0.00139174:0.0705811:0.036977:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037074 ES:SE:LP:AF:ID  0.000474647:0.00138696:0.136677:0.037074:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101246 ES:SE:LP:AF:ID  0.00155351:0.00101029:0.920819:0.101246:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959089 ES:SE:LP:AF:ID  4.40039e-06:0.0013376:-0:0.959089:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  -0.00141696:0.00242851:0.251812:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053273 ES:SE:LP:AF:ID  0.00111793:0.00193089:0.251812:0.053273:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  0.000247529:0.00139598:0.0655015:0.03659:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036906 ES:SE:LP:AF:ID  0.000295706:0.00138324:0.0809219:0.036906:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843184 ES:SE:LP:AF:ID  -0.00056248:0.000716463:0.366532:0.843184:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055947 ES:SE:LP:AF:ID  0.000333335:0.00115976:0.113509:0.055947:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122327 ES:SE:LP:AF:ID  0.000315228:0.000784164:0.161151:0.122327:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025697 ES:SE:LP:AF:ID  0.00115267:0.00192989:0.259637:0.025697:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121571 ES:SE:LP:AF:ID  0.000315997:0.000784491:0.161151:0.121571:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132347 ES:SE:LP:AF:ID  0.000898193:0.000773273:0.60206:0.132347:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036824 ES:SE:LP:AF:ID  -0.000134217:0.00136922:0.0362122:0.036824:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838927 ES:SE:LP:AF:ID  -0.000320511:0.000693866:0.19382:0.838927:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838554 ES:SE:LP:AF:ID  -0.000312493:0.000693115:0.187087:0.838554:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869761 ES:SE:LP:AF:ID  -0.00012561:0.000743725:0.0604807:0.869761:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129894 ES:SE:LP:AF:ID  7.48341e-05:0.000745219:0.0362122:0.129894:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037335 ES:SE:LP:AF:ID  -4.19009e-05:0.001346:0.00877392:0.037335:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  -7.07236e-05:0.0013375:0.0177288:0.037578:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000104405:0.000742267:0.05061:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  -6.96903e-05:0.000742563:0.0315171:0.869199:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -8.62221e-05:0.00134326:0.0222764:0.037539:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -9.55729e-05:0.000742252:0.0457575:0.869104:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838003 ES:SE:LP:AF:ID  -0.000271452:0.000691183:0.161151:0.838003:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  -2.21913e-05:0.00134514:0.00436481:0.037552:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838632 ES:SE:LP:AF:ID  -0.000308883:0.000693125:0.180456:0.838632:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013784 ES:SE:LP:AF:ID  0.0021611:0.00241872:0.431798:0.013784:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839742 ES:SE:LP:AF:ID  -0.000252493:0.000702504:0.142668:0.839742:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869381 ES:SE:LP:AF:ID  -0.000150948:0.000741382:0.0757207:0.869381:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868926 ES:SE:LP:AF:ID  -0.000156468:0.000739513:0.0809219:0.868926:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867879 ES:SE:LP:AF:ID  -0.000188355:0.000738099:0.09691:0.867879:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869071 ES:SE:LP:AF:ID  -0.000170738:0.000740122:0.0861861:0.869071:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86908  ES:SE:LP:AF:ID  -0.000175973:0.000740179:0.091515:0.86908:rs4951862