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-20214/UKB-b-20214_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20214/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20214/UKB-b-20214_data.vcf.gz ...
Read summary statistics for 6962897 SNPs.
Dropped 4247 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, 1262473 SNPs remain.
After merging with regression SNP LD, 1262473 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0257 (0.0015)
Lambda GC: 1.2373
Mean Chi^2: 1.2687
Intercept: 1.0328 (0.0077)
Ratio: 0.122 (0.0286)
Analysis finished at Thu Oct 17 14:43:30 2019
Total time elapsed: 1.0m:23.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9355,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 8,
    "n_p_sig": 68,
    "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": 64044,
    "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": 1262473,
    "ldsc_nsnp_merge_regression_ld": 1262473,
    "ldsc_observed_scale_h2_beta": 0.0257,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0328,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.2373,
    "ldsc_mean_chisq": 1.2687,
    "ldsc_ratio": 0.1221
}

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 6958672 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 6962897 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 8.663962e+00 5.764053e+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 7.863282e+07 5.645485e+07 828.0000000 3.213083e+07 6.907604e+07 1.145233e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.090000e-05 8.823000e-04 -0.0075518 -4.779000e-04 4.900000e-06 4.911000e-04 1.034020e-02 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.427000e-04 3.424000e-04 0.0004145 4.676000e-04 5.997000e-04 9.315000e-04 4.107200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.684250e-01 2.970596e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.684282e-01 2.970337e-01 0.0000000 2.026896e-01 4.575596e-01 7.253387e-01 9.999995e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.771536e-01 2.596708e-01 0.0171360 6.101900e-02 1.812380e-01 4.345660e-01 9.828640e-01 ▇▃▂▁▁
numeric AF_reference 64044 0.9908021 NA NA NA NA NA NA NA 2.753812e-01 2.516950e-01 0.0000000 6.888980e-02 1.932910e-01 4.269170e-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 0.0004542 0.0007625 0.5500004 0.5514319 0.623753 0.7821490 NA
1 54676 rs2462492 C T -0.0002880 0.0007554 0.6999999 0.7029919 0.400435 NA NA
1 86028 rs114608975 T C 0.0008328 0.0012079 0.4899999 0.4905581 0.103548 0.0277556 NA
1 91536 rs6702460 G T 0.0000298 0.0007439 0.9699999 0.9680065 0.456835 0.4207270 NA
1 234313 rs8179466 C T 0.0017327 0.0014672 0.2399999 0.2376358 0.074495 NA NA
1 534192 rs6680723 C T 0.0007924 0.0008497 0.3500000 0.3510310 0.240974 NA NA
1 546697 rs12025928 A G 0.0009109 0.0010601 0.3900004 0.3901913 0.913470 NA NA
1 693731 rs12238997 A G 0.0002374 0.0007120 0.7400005 0.7388696 0.116360 0.1417730 NA
1 705882 rs72631875 G A -0.0006943 0.0010434 0.5099998 0.5058055 0.067283 0.0315495 NA
1 706368 rs55727773 A G 0.0006985 0.0005275 0.1900002 0.1854873 0.515638 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0002755 0.0006365 0.6700003 0.6651315 0.137953 0.2052720 NA
22 51219387 rs9616832 T C -0.0003726 0.0008263 0.6499995 0.6520475 0.073740 0.0654952 NA
22 51219704 rs147475742 G A 0.0004952 0.0011074 0.6499995 0.6547806 0.041940 0.0473243 NA
22 51221190 rs369304721 G A -0.0007998 0.0011054 0.4700002 0.4693429 0.049736 NA NA
22 51221731 rs115055839 T C -0.0004140 0.0008269 0.6200004 0.6165800 0.073230 0.0625000 NA
22 51222100 rs114553188 G T -0.0006931 0.0009732 0.4799997 0.4763755 0.054467 0.0880591 NA
22 51223637 rs375798137 G A -0.0007759 0.0009779 0.4299995 0.4275279 0.054097 0.0788738 NA
22 51229805 rs9616985 T C -0.0003171 0.0008298 0.6999999 0.7023923 0.073065 0.0730831 NA
22 51232488 rs376461333 A G -0.0015692 0.0019557 0.4199997 0.4223209 0.020028 NA NA
22 51237063 rs3896457 T C 0.0009057 0.0005075 0.0739997 0.0743101 0.297970 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623753 ES:SE:LP:AF:ID  0.000454169:0.00076252:0.259637:0.623753:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400435 ES:SE:LP:AF:ID  -0.000288021:0.000755396:0.154902:0.400435:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103548 ES:SE:LP:AF:ID  0.000832759:0.00120791:0.309804:0.103548:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456835 ES:SE:LP:AF:ID  2.98371e-05:0.000743907:0.0132283:0.456835:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074495 ES:SE:LP:AF:ID  0.0017327:0.00146725:0.619789:0.074495:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240974 ES:SE:LP:AF:ID  0.000792422:0.000849699:0.455932:0.240974:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91347  ES:SE:LP:AF:ID  0.000910904:0.00106009:0.408935:0.91347:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11636  ES:SE:LP:AF:ID  0.00023736:0.000712043:0.130768:0.11636:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  -0.000694274:0.00104342:0.29243:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515638 ES:SE:LP:AF:ID  0.000698476:0.000527531:0.721246:0.515638:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033022 ES:SE:LP:AF:ID  0.000127232:0.00132952:0.0362122:0.033022:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036635 ES:SE:LP:AF:ID  -0.000195543:0.00120774:0.0604807:0.036635:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03675  ES:SE:LP:AF:ID  -0.000292062:0.00120319:0.091515:0.03675:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03645  ES:SE:LP:AF:ID  -0.000173739:0.00121186:0.05061:0.03645:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036993 ES:SE:LP:AF:ID  -0.000175139:0.00119838:0.0555173:0.036993:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037089 ES:SE:LP:AF:ID  -0.000139132:0.00119429:0.0409586:0.037089:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101215 ES:SE:LP:AF:ID  -0.00166638:0.000870171:1.25964:0.101215:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959096 ES:SE:LP:AF:ID  0.00025893:0.00115207:0.0861861:0.959096:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  -0.000860318:0.0020911:0.167491:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053246 ES:SE:LP:AF:ID  -0.00288778:0.00166389:1.08092:0.053246:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  -0.000287884:0.00120204:0.091515:0.036606:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036923 ES:SE:LP:AF:ID  -0.000185414:0.00119106:0.0555173:0.036923:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843184 ES:SE:LP:AF:ID  -0.000220289:0.00061711:0.142668:0.843184:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055962 ES:SE:LP:AF:ID  0.000917122:0.000998822:0.443698:0.055962:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122347 ES:SE:LP:AF:ID  0.000457466:0.000675428:0.30103:0.122347:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025694 ES:SE:LP:AF:ID  0.00481651:0.00166213:2.42022:0.025694:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12159  ES:SE:LP:AF:ID  0.000477266:0.000675711:0.318759:0.12159:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132378 ES:SE:LP:AF:ID  0.000675086:0.00066598:0.508638:0.132378:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036835 ES:SE:LP:AF:ID  1.13359e-05:0.0011791:0.00436481:0.036835:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838931 ES:SE:LP:AF:ID  -5.71512e-06:0.000597683:0.00436481:0.838931:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838562 ES:SE:LP:AF:ID  -4.36458e-06:0.000597035:0.00436481:0.838562:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869765 ES:SE:LP:AF:ID  -7.84372e-05:0.000640664:0.0457575:0.869765:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129888 ES:SE:LP:AF:ID  9.17587e-05:0.000641961:0.05061:0.129888:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037344 ES:SE:LP:AF:ID  -0.000112589:0.00115913:0.0362122:0.037344:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037587 ES:SE:LP:AF:ID  -0.00016543:0.00115181:0.05061:0.037587:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  -6.49275e-05:0.000639409:0.0362122:0.86911:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869209 ES:SE:LP:AF:ID  -2.58505e-05:0.000639665:0.0132283:0.869209:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.000151982:0.0011568:0.0457575:0.037545:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869113 ES:SE:LP:AF:ID  -6.91599e-05:0.000639396:0.0409586:0.869113:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838015 ES:SE:LP:AF:ID  4.04297e-06:0.000595382:0.00436481:0.838015:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037558 ES:SE:LP:AF:ID  -0.000125221:0.00115843:0.0409586:0.037558:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838644 ES:SE:LP:AF:ID  1.21814e-05:0.000597055:0.00877392:0.838644:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839751 ES:SE:LP:AF:ID  -4.57501e-05:0.000605127:0.0268721:0.839751:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.86939  ES:SE:LP:AF:ID  -9.31539e-05:0.000638656:0.0555173:0.86939:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868936 ES:SE:LP:AF:ID  -0.000113145:0.000637045:0.0655015:0.868936:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867895 ES:SE:LP:AF:ID  -5.82182e-05:0.000635826:0.0315171:0.867895:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86908  ES:SE:LP:AF:ID  -8.10097e-05:0.000637569:0.0457575:0.86908:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  -8.1707e-05:0.000637618:0.0457575:0.869088:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869096 ES:SE:LP:AF:ID  -8.2893e-05:0.000637633:0.0457575:0.869096:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869575 ES:SE:LP:AF:ID  -6.95052e-05:0.000639388:0.0409586:0.869575:rs3131954