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-5911/UKB-b-5911_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5911/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5911/UKB-b-5911_data.vcf.gz ...
Read summary statistics for 6133891 SNPs.
Dropped 2934 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, 1223337 SNPs remain.
After merging with regression SNP LD, 1223337 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0058 (0.0011)
Lambda GC: 1.0864
Mean Chi^2: 1.0868
Intercept: 1.0323 (0.0065)
Ratio: 0.3727 (0.0755)
Analysis finished at Thu Oct 17 14:46:40 2019
Total time elapsed: 59.98s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9264,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 1.2896e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 10,
    "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": 55921,
    "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": 1223337,
    "ldsc_nsnp_merge_regression_ld": 1223337,
    "ldsc_observed_scale_h2_beta": 0.0058,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0323,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0864,
    "ldsc_mean_chisq": 1.0868,
    "ldsc_ratio": 0.3721
}

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 6130976 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 6133891 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 8.669888e+00 5.762494e+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 7.858217e+07 5.651618e+07 828.0000000 3.199909e+07 6.901769e+07 1.145145e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-07 5.279000e-04 -0.0047348 -3.119000e-04 -5.000000e-07 3.102000e-04 4.896600e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.828000e-04 1.701000e-04 0.0003098 3.433000e-04 4.159000e-04 5.812000e-04 1.724400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.881502e-01 2.919869e-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 4.881506e-01 2.919619e-01 0.0000000 2.321912e-01 4.841237e-01 7.411759e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.065983e-01 2.546012e-01 0.0308430 9.108300e-02 2.227750e-01 4.711380e-01 9.691570e-01 ▇▃▂▂▁
numeric AF_reference 55921 0.9908833 NA NA NA NA NA NA NA 3.034179e-01 2.475168e-01 0.0000000 1.002400e-01 2.306310e-01 4.620610e-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 0.0000989 0.0005702 0.8600001 0.8623511 0.623765 0.7821490 NA
1 54676 rs2462492 C T 0.0000543 0.0005649 0.9199999 0.9233554 0.400401 NA NA
1 86028 rs114608975 T C -0.0005501 0.0009032 0.5400003 0.5424720 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0009041 0.0005562 0.1000000 0.1040526 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0024567 0.0010967 0.0250000 0.0250881 0.074506 NA NA
1 534192 rs6680723 C T 0.0008406 0.0006353 0.1900002 0.1858145 0.240959 NA NA
1 546697 rs12025928 A G 0.0009267 0.0007926 0.2399999 0.2423309 0.913475 NA NA
1 693731 rs12238997 A G 0.0003243 0.0005324 0.5400003 0.5424447 0.116329 0.1417730 NA
1 705882 rs72631875 G A -0.0006763 0.0007802 0.3900004 0.3860750 0.067288 0.0315495 NA
1 706368 rs55727773 A G -0.0001379 0.0003944 0.7300002 0.7266326 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0002507 0.0006164 0.6800001 0.6842455 0.073622 0.0826677 NA
22 51219006 rs28729663 G A 0.0001172 0.0004758 0.8100000 0.8054012 0.137950 0.2052720 NA
22 51219387 rs9616832 T C 0.0002144 0.0006176 0.7300002 0.7284792 0.073744 0.0654952 NA
22 51219704 rs147475742 G A 0.0005233 0.0008276 0.5300002 0.5272463 0.041954 0.0473243 NA
22 51221190 rs369304721 G A 0.0000250 0.0008263 0.9800000 0.9758173 0.049731 NA NA
22 51221731 rs115055839 T C 0.0002202 0.0006180 0.7199992 0.7216393 0.073235 0.0625000 NA
22 51222100 rs114553188 G T 0.0002345 0.0007276 0.7499995 0.7471935 0.054460 0.0880591 NA
22 51223637 rs375798137 G A 0.0002137 0.0007311 0.7700005 0.7700910 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 0.0003009 0.0006202 0.6300007 0.6275880 0.073071 0.0730831 NA
22 51237063 rs3896457 T C 0.0005035 0.0003794 0.1800002 0.1844079 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  9.88637e-05:0.000570207:0.0655015:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  5.43479e-05:0.0005649:0.0362122:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  -0.000550094:0.000903157:0.267606:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.00090413:0.000556211:1:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074506 ES:SE:LP:AF:ID  0.0024567:0.00109672:1.60206:0.074506:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  0.000840596:0.000635341:0.721246:0.240959:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  0.000926717:0.000792621:0.619789:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116329 ES:SE:LP:AF:ID  0.000324317:0.000532435:0.267606:0.116329:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  -0.000676264:0.000780223:0.408935:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000137888:0.000394407:0.136677:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033009 ES:SE:LP:AF:ID  -0.00124608:0.000994265:0.677781:0.033009:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036624 ES:SE:LP:AF:ID  -0.00112186:0.000903138:0.677781:0.036624:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036741 ES:SE:LP:AF:ID  -0.00105799:0.000899721:0.619789:0.036741:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036439 ES:SE:LP:AF:ID  -0.0010201:0.000906213:0.585027:0.036439:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.03698  ES:SE:LP:AF:ID  -0.00111914:0.000896153:0.677781:0.03698:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037077 ES:SE:LP:AF:ID  -0.000950345:0.000893083:0.537602:0.037077:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.1012   ES:SE:LP:AF:ID  0.000402365:0.000650748:0.267606:0.1012:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959091 ES:SE:LP:AF:ID  0.000799279:0.000861359:0.455932:0.959091:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03145  ES:SE:LP:AF:ID  0.00300687:0.00156379:1.25964:0.03145:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  -0.00283642:0.00124397:1.63827:0.053255:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  -0.00111117:0.000898877:0.657577:0.036594:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03691  ES:SE:LP:AF:ID  -0.00113267:0.000890695:0.69897:0.03691:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  -0.000104652:0.000461424:0.0861861:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055912 ES:SE:LP:AF:ID  -0.000109536:0.00074712:0.0555173:0.055912:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  0.000170305:0.000505068:0.130768:0.122312:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  0.000161536:0.00050528:0.124939:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  -3.89773e-05:0.000498004:0.0268721:0.132335:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  -0.00106632:0.000881685:0.638272:0.036825:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  -0.000304288:0.000446858:0.30103:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838573 ES:SE:LP:AF:ID  -0.000323744:0.000446377:0.327902:0.838573:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  -0.000446711:0.000478978:0.455932:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  0.000437913:0.000479959:0.443698:0.129876:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  -0.000946312:0.000866735:0.568636:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03758  ES:SE:LP:AF:ID  -0.000963337:0.000861259:0.585027:0.03758:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000457542:0.00047804:0.468521:0.869117:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.000467433:0.000478229:0.481486:0.869215:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  -0.000972515:0.000864984:0.585027:0.037538:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  -0.000448263:0.000478031:0.455932:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  -0.000296463:0.000445138:0.29243:0.838026:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -0.000985776:0.000866206:0.585027:0.03755:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838657 ES:SE:LP:AF:ID  -0.000274344:0.000446389:0.267606:0.838657:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83977  ES:SE:LP:AF:ID  -0.000261998:0.000452426:0.251812:0.83977:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  -0.000381624:0.000477478:0.376751:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868947 ES:SE:LP:AF:ID  -0.000370726:0.000476276:0.356547:0.868947:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867898 ES:SE:LP:AF:ID  -0.000410924:0.000475363:0.408935:0.867898:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86909  ES:SE:LP:AF:ID  -0.00037095:0.000476666:0.356547:0.86909:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869098 ES:SE:LP:AF:ID  -0.000372228:0.000476703:0.366532:0.869098:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  -0.00036971:0.000476714:0.356547:0.869106:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869584 ES:SE:LP:AF:ID  -0.000375256:0.000478023:0.366532:0.869584:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037599 ES:SE:LP:AF:ID  -0.00091509:0.000861134:0.537602:0.037599:rs114525117