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-7647/UKB-b-7647_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7647/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:48 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7647/UKB-b-7647_data.vcf.gz ...
Read summary statistics for 8030953 SNPs.
Dropped 6180 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, 1282633 SNPs remain.
After merging with regression SNP LD, 1282633 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0088 (0.0011)
Lambda GC: 1.1093
Mean Chi^2: 1.1199
Intercept: 1.0439 (0.0065)
Ratio: 0.3661 (0.0546)
Analysis finished at Thu Oct 17 14:42:15 2019
Total time elapsed: 1.0m:27.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9431,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -1.0033e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 2047,
    "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": 75003,
    "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": 1282633,
    "ldsc_nsnp_merge_regression_ld": 1282633,
    "ldsc_observed_scale_h2_beta": 0.0088,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0439,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.1093,
    "ldsc_mean_chisq": 1.1199,
    "ldsc_ratio": 0.3661
}

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 TRUE
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 8024800 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 8030953 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 8.660689e+00 5.763469e+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 7.870287e+07 5.640792e+07 828.0000000 3.227007e+07 6.917132e+07 1.145363e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.000000e-06 1.596200e-03 -0.0214293 -7.456000e-04 -2.800000e-06 7.434000e-04 1.736690e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.320800e-03 8.003000e-04 0.0005965 6.916000e-04 9.659000e-04 1.740100e-03 7.373900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.845838e-01 2.928421e-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 4.845855e-01 2.928174e-01 0.0000000 2.279625e-01 4.795024e-01 7.379381e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.446810e-01 2.606908e-01 0.0081070 3.481200e-02 1.353170e-01 3.877120e-01 9.918930e-01 ▇▂▂▁▁
numeric AF_reference 75003 0.9906608 NA NA NA NA NA NA NA 2.439750e-01 2.525356e-01 0.0000000 3.654150e-02 1.507590e-01 3.829870e-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 -0.0008772 0.0010976 0.4199997 0.4241512 0.623754 0.7821490 NA
1 54676 rs2462492 C T -0.0009043 0.0010874 0.4100001 0.4056378 0.400457 NA NA
1 86028 rs114608975 T C 0.0012700 0.0017388 0.4700002 0.4651472 0.103523 0.0277556 NA
1 91536 rs6702460 G T -0.0006197 0.0010704 0.5600000 0.5626571 0.456885 0.4207270 NA
1 234313 rs8179466 C T 0.0007249 0.0021120 0.7300002 0.7314146 0.074448 NA NA
1 534192 rs6680723 C T 0.0002382 0.0012233 0.8499999 0.8456025 0.240902 NA NA
1 546697 rs12025928 A G 0.0005835 0.0015266 0.6999999 0.7023168 0.913524 NA NA
1 693731 rs12238997 A G 0.0007078 0.0010251 0.4899999 0.4898773 0.116378 0.1417730 NA
1 705882 rs72631875 G A -0.0016036 0.0015022 0.2900000 0.2857435 0.067322 0.0315495 NA
1 706368 rs55727773 A G -0.0003207 0.0007593 0.6700003 0.6727309 0.515696 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0000792 0.0009158 0.9299999 0.9310452 0.138022 0.2052720 NA
22 51219387 rs9616832 T C 0.0007623 0.0011885 0.5199996 0.5212643 0.073792 0.0654952 NA
22 51219704 rs147475742 G A -0.0004658 0.0015926 0.7700005 0.7699200 0.041979 0.0473243 NA
22 51221190 rs369304721 G A 0.0002316 0.0015898 0.8800001 0.8841480 0.049773 NA NA
22 51221731 rs115055839 T C 0.0006546 0.0011893 0.5800000 0.5820429 0.073286 0.0625000 NA
22 51222100 rs114553188 G T -0.0014806 0.0014002 0.2900000 0.2903205 0.054505 0.0880591 NA
22 51223637 rs375798137 G A -0.0015089 0.0014070 0.2800000 0.2835563 0.054133 0.0788738 NA
22 51229805 rs9616985 T C 0.0006298 0.0011936 0.5999997 0.5977477 0.073122 0.0730831 NA
22 51232488 rs376461333 A G -0.0015716 0.0028112 0.5800000 0.5761358 0.020062 NA NA
22 51237063 rs3896457 T C 0.0022524 0.0007303 0.0020000 0.0020410 0.298103 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623754 ES:SE:LP:AF:ID  -0.00087723:0.00109758:0.376751:0.623754:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400457 ES:SE:LP:AF:ID  -0.000904251:0.00108737:0.387216:0.400457:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103523 ES:SE:LP:AF:ID  0.00127003:0.00173882:0.327902:0.103523:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456885 ES:SE:LP:AF:ID  -0.000619677:0.00107044:0.251812:0.456885:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074448 ES:SE:LP:AF:ID  0.000724922:0.00211197:0.136677:0.074448:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240902 ES:SE:LP:AF:ID  0.000238218:0.00122331:0.0705811:0.240902:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913524 ES:SE:LP:AF:ID  0.000583455:0.00152659:0.154902:0.913524:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116378 ES:SE:LP:AF:ID  0.000707815:0.00102507:0.309804:0.116378:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067322 ES:SE:LP:AF:ID  -0.00160365:0.00150224:0.537602:0.067322:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515696 ES:SE:LP:AF:ID  -0.000320739:0.00075932:0.173925:0.515696:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033049 ES:SE:LP:AF:ID  0.000763711:0.00191315:0.161151:0.033049:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036666 ES:SE:LP:AF:ID  0.000293788:0.00173794:0.0604807:0.036666:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036783 ES:SE:LP:AF:ID  0.000117856:0.00173136:0.0222764:0.036783:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036479 ES:SE:LP:AF:ID  0.000158398:0.00174392:0.0315171:0.036479:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016431 ES:SE:LP:AF:ID  0.00312233:0.00268554:0.619789:0.016431:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037018 ES:SE:LP:AF:ID  0.000123358:0.00172465:0.0268721:0.037018:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037119 ES:SE:LP:AF:ID  1.97967e-05:0.00171854:0.00436481:0.037119:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101255 ES:SE:LP:AF:ID  0.000930099:0.00125251:0.337242:0.101255:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959066 ES:SE:LP:AF:ID  0.000235701:0.00165798:0.05061:0.959066:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031437 ES:SE:LP:AF:ID  -0.00275406:0.0030107:0.443698:0.031437:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053303 ES:SE:LP:AF:ID  -1.29037e-05:0.00239191:-0:0.053303:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036627 ES:SE:LP:AF:ID  0.000127636:0.00172992:0.0268721:0.036627:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  0.000334042:0.00171414:0.0705811:0.036944:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843118 ES:SE:LP:AF:ID  -0.000218598:0.000888354:0.091515:0.843118:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055922 ES:SE:LP:AF:ID  -0.00184705:0.00143833:0.69897:0.055922:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122369 ES:SE:LP:AF:ID  0.00032017:0.000972293:0.130768:0.122369:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025679 ES:SE:LP:AF:ID  -0.00216392:0.00239385:0.431798:0.025679:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121611 ES:SE:LP:AF:ID  0.000388066:0.000972698:0.161151:0.121611:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132421 ES:SE:LP:AF:ID  -9.72237e-05:0.000958655:0.0362122:0.132421:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011133 ES:SE:LP:AF:ID  0.000560342:0.00348585:0.0604807:0.011133:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036855 ES:SE:LP:AF:ID  0.000354343:0.00169694:0.0809219:0.036855:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838807 ES:SE:LP:AF:ID  5.42491e-06:0.00086006:0.00436481:0.838807:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838428 ES:SE:LP:AF:ID  3.93954e-05:0.000859102:0.0177288:0.838428:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869675 ES:SE:LP:AF:ID  6.63394e-05:0.000921857:0.0268721:0.869675:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129989 ES:SE:LP:AF:ID  -0.000104946:0.000923698:0.0409586:0.129989:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037371 ES:SE:LP:AF:ID  0.000440506:0.00166805:0.102373:0.037371:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037616 ES:SE:LP:AF:ID  0.000526015:0.00165748:0.124939:0.037616:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869014 ES:SE:LP:AF:ID  0.00014541:0.000920027:0.0604807:0.869014:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  9.13396e-05:0.000920401:0.0362122:0.869114:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037577 ES:SE:LP:AF:ID  0.00044391:0.0016646:0.102373:0.037577:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869018 ES:SE:LP:AF:ID  0.000133249:0.000920011:0.0555173:0.869018:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837877 ES:SE:LP:AF:ID  9.63355e-05:0.000856711:0.0409586:0.837877:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037591 ES:SE:LP:AF:ID  0.000493173:0.00166691:0.113509:0.037591:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838507 ES:SE:LP:AF:ID  5.35349e-05:0.000859114:0.0222764:0.838507:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  0.00194979:0.00300045:0.283997:0.013772:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839626 ES:SE:LP:AF:ID  -0.000200632:0.000870776:0.0861861:0.839626:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869302 ES:SE:LP:AF:ID  1.87447e-05:0.000918988:0.00877392:0.869302:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868851 ES:SE:LP:AF:ID  -5.25976e-05:0.000916702:0.0222764:0.868851:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867793 ES:SE:LP:AF:ID  6.53246e-05:0.000914885:0.0268721:0.867793:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86899  ES:SE:LP:AF:ID  -2.27317e-05:0.000917434:0.00877392:0.86899:rs4951929