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-6445/UKB-b-6445_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6445/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-6445/UKB-b-6445_data.vcf.gz ...
Read summary statistics for 6795587 SNPs.
Dropped 3989 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, 1256463 SNPs remain.
After merging with regression SNP LD, 1256463 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0224 (0.0027)
Lambda GC: 1.0996
Mean Chi^2: 1.1058
Intercept: 1.0059 (0.007)
Ratio: 0.0557 (0.0665)
Analysis finished at Thu Oct 17 14:41:38 2019
Total time elapsed: 1.0m:20.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9339,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -2.1686e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 65,
    "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": 62419,
    "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": 1256463,
    "ldsc_nsnp_merge_regression_ld": 1256463,
    "ldsc_observed_scale_h2_beta": 0.0224,
    "ldsc_observed_scale_h2_se": 0.0027,
    "ldsc_intercept_beta": 1.0059,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0996,
    "ldsc_mean_chisq": 1.1058,
    "ldsc_ratio": 0.0558
}

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 6791620 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 6795587 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 8.663820e+00 5.764455e+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 7.860554e+07 5.647099e+07 828.0000000 3.208877e+07 6.905070e+07 1.145002e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.000000e-07 1.554300e-03 -0.0139838 -8.633000e-04 -1.600000e-06 8.609000e-04 1.403250e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.382200e-03 6.060000e-04 0.0007939 8.934000e-04 1.131300e-03 1.719200e-03 6.921000e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.861621e-01 2.922771e-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 4.861640e-01 2.922504e-01 0.0000000 2.301286e-01 4.810955e-01 7.390066e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.827096e-01 2.589275e-01 0.0192620 6.619050e-02 1.891630e-01 4.417590e-01 9.807380e-01 ▇▃▂▂▁
numeric AF_reference 62419 0.9908148 NA NA NA NA NA NA NA 2.807003e-01 2.510698e-01 0.0000000 7.488020e-02 2.002800e-01 4.341050e-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 -0.0004918 0.0014642 0.7400005 0.7369779 0.623259 0.7821490 NA
1 54676 rs2462492 C T 0.0015985 0.0014466 0.2700001 0.2691764 0.401007 NA NA
1 86028 rs114608975 T C -0.0006957 0.0023167 0.7600007 0.7639431 0.103669 0.0277556 NA
1 91536 rs6702460 G T 0.0009895 0.0014259 0.4899999 0.4876970 0.456923 0.4207270 NA
1 234313 rs8179466 C T -0.0009371 0.0028184 0.7400005 0.7395284 0.074411 NA NA
1 534192 rs6680723 C T -0.0010665 0.0016279 0.5099998 0.5123904 0.241538 NA NA
1 546697 rs12025928 A G 0.0007960 0.0020336 0.6999999 0.6954877 0.913541 NA NA
1 693731 rs12238997 A G -0.0002042 0.0013635 0.8800001 0.8809547 0.116876 0.1417730 NA
1 705882 rs72631875 G A -0.0020875 0.0020023 0.2999998 0.2971517 0.067078 0.0315495 NA
1 706368 rs55727773 A G -0.0014837 0.0010107 0.1400000 0.1420943 0.514918 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0011804 0.0012216 0.3300000 0.3338990 0.138084 0.2052720 NA
22 51219387 rs9616832 T C 0.0017625 0.0015861 0.2700001 0.2664816 0.073629 0.0654952 NA
22 51219704 rs147475742 G A 0.0008739 0.0021234 0.6800001 0.6806771 0.041928 0.0473243 NA
22 51221190 rs369304721 G A 0.0031490 0.0021225 0.1400000 0.1379033 0.049639 NA NA
22 51221731 rs115055839 T C 0.0015628 0.0015870 0.3200000 0.3247402 0.073152 0.0625000 NA
22 51222100 rs114553188 G T 0.0011077 0.0018605 0.5500004 0.5516019 0.054833 0.0880591 NA
22 51223637 rs375798137 G A 0.0010647 0.0018694 0.5700002 0.5690041 0.054462 0.0788738 NA
22 51229805 rs9616985 T C 0.0016630 0.0015923 0.2999998 0.2963265 0.073044 0.0730831 NA
22 51232488 rs376461333 A G -0.0028674 0.0037309 0.4400003 0.4421561 0.020156 NA NA
22 51237063 rs3896457 T C 0.0007828 0.0009726 0.4199997 0.4209390 0.297565 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623259 ES:SE:LP:AF:ID  -0.00049176:0.00146419:0.130768:0.623259:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.401007 ES:SE:LP:AF:ID  0.00159847:0.00144663:0.568636:0.401007:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103669 ES:SE:LP:AF:ID  -0.000695712:0.00231667:0.119186:0.103669:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456923 ES:SE:LP:AF:ID  0.000989527:0.00142588:0.309804:0.456923:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074411 ES:SE:LP:AF:ID  -0.000937069:0.00281844:0.130768:0.074411:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241538 ES:SE:LP:AF:ID  -0.00106647:0.0016279:0.29243:0.241538:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913541 ES:SE:LP:AF:ID  0.000795997:0.00203362:0.154902:0.913541:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116876 ES:SE:LP:AF:ID  -0.000204198:0.00136351:0.0555173:0.116876:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067078 ES:SE:LP:AF:ID  -0.00208753:0.00200231:0.522879:0.067078:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514918 ES:SE:LP:AF:ID  -0.00148373:0.00101069:0.853872:0.514918:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033046 ES:SE:LP:AF:ID  -0.00411542:0.00254881:0.958607:0.033046:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036632 ES:SE:LP:AF:ID  -0.003979:0.00231695:1.0655:0.036632:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036745 ES:SE:LP:AF:ID  -0.00381215:0.00230866:1.00436:0.036745:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03643  ES:SE:LP:AF:ID  -0.00383545:0.00232584:1.00436:0.03643:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036965 ES:SE:LP:AF:ID  -0.00362867:0.00230021:0.958607:0.036965:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037064 ES:SE:LP:AF:ID  -0.00359082:0.00229234:0.920819:0.037064:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100898 ES:SE:LP:AF:ID  0.00174553:0.00167107:0.522879:0.100898:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959064 ES:SE:LP:AF:ID  0.00311706:0.00220965:0.79588:0.959064:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031427 ES:SE:LP:AF:ID  0.00377414:0.00399748:0.455932:0.031427:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053353 ES:SE:LP:AF:ID  0.00572826:0.00318238:1.14267:0.053353:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036601 ES:SE:LP:AF:ID  -0.00360963:0.00230576:0.920819:0.036601:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036938 ES:SE:LP:AF:ID  -0.00329801:0.00228467:0.823909:0.036938:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84257  ES:SE:LP:AF:ID  0.000875121:0.00118204:0.337242:0.84257:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056106 ES:SE:LP:AF:ID  -4.03753e-05:0.00191362:0.00877392:0.056106:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122963 ES:SE:LP:AF:ID  0.000152513:0.00129265:0.0409586:0.122963:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025509 ES:SE:LP:AF:ID  -0.00167162:0.0031967:0.221849:0.025509:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122185 ES:SE:LP:AF:ID  0.00018128:0.00129318:0.05061:0.122185:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132867 ES:SE:LP:AF:ID  -0.000643832:0.00127531:0.21467:0.132867:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036854 ES:SE:LP:AF:ID  -0.00358017:0.00226158:0.958607:0.036854:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838361 ES:SE:LP:AF:ID  0.000599421:0.00114453:0.221849:0.838361:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837986 ES:SE:LP:AF:ID  0.000676207:0.00114344:0.259637:0.837986:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86917  ES:SE:LP:AF:ID  -0.000434453:0.00122605:0.142668:0.86917:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130492 ES:SE:LP:AF:ID  0.000479334:0.00122884:0.154902:0.130492:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.00350643:0.0022243:0.958607:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037583 ES:SE:LP:AF:ID  -0.00320612:0.0022094:0.823909:0.037583:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8685   ES:SE:LP:AF:ID  -0.00035587:0.00122382:0.113509:0.8685:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868579 ES:SE:LP:AF:ID  -0.000371813:0.00122429:0.119186:0.868579:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037529 ES:SE:LP:AF:ID  -0.00338326:0.00221917:0.886057:0.037529:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868499 ES:SE:LP:AF:ID  -0.000360733:0.00122378:0.113509:0.868499:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837419 ES:SE:LP:AF:ID  0.000676278:0.00114013:0.259637:0.837419:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.00338316:0.00222265:0.886057:0.037539:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838057 ES:SE:LP:AF:ID  0.000625581:0.00114334:0.236572:0.838057:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839229 ES:SE:LP:AF:ID  0.000581714:0.00115869:0.207608:0.839229:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868799 ES:SE:LP:AF:ID  -0.000525866:0.00122218:0.173925:0.868799:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86835  ES:SE:LP:AF:ID  -0.000458318:0.00121916:0.148742:0.86835:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867321 ES:SE:LP:AF:ID  -0.000405871:0.00121722:0.130768:0.867321:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868496 ES:SE:LP:AF:ID  -0.000466608:0.00122018:0.154902:0.868496:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868505 ES:SE:LP:AF:ID  -0.000467255:0.00122027:0.154902:0.868505:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868513 ES:SE:LP:AF:ID  -0.000461511:0.0012203:0.148742:0.868513:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868981 ES:SE:LP:AF:ID  -0.000500384:0.00122357:0.167491:0.868981:rs3131954