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-15903/UKB-b-15903_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15903/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15903/UKB-b-15903_data.vcf.gz ...
Read summary statistics for 6164236 SNPs.
Dropped 2975 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, 1225187 SNPs remain.
After merging with regression SNP LD, 1225187 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 4.4253e-05 (0.0011)
Lambda GC: 1.0524
Mean Chi^2: 1.048
Intercept: 1.0476 (0.0065)
Ratio: 0.9917 (0.1348)
Analysis finished at Thu Oct 17 14:45:44 2019
Total time elapsed: 1.0m:10.27s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9268,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 9.0872e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 56263,
    "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": 1225187,
    "ldsc_nsnp_merge_regression_ld": 1225187,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0476,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0524,
    "ldsc_mean_chisq": 1.048,
    "ldsc_ratio": 0.9917
}

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 TRUE
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 6161280 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 6164236 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 8.668503e+00 5.762765e+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 7.859416e+07 5.651980e+07 828.0000000 3.200549e+07 6.903155e+07 1.145279e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.000000e-07 5.514000e-04 -0.0042613 -3.254000e-04 -2.000000e-06 3.220000e-04 4.855400e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.106000e-04 1.818000e-04 0.0003261 3.616000e-04 4.388000e-04 6.156000e-04 1.815500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.930811e-01 2.906246e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.930807e-01 2.906014e-01 0.0000001 2.390423e-01 4.902179e-01 7.453205e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.054468e-01 2.548648e-01 0.0301960 8.977600e-02 2.211505e-01 4.698472e-01 9.698040e-01 ▇▃▂▂▁
numeric AF_reference 56263 0.9908727 NA NA NA NA NA NA NA 3.023354e-01 2.477252e-01 0.0000000 9.904150e-02 2.292330e-01 4.608630e-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 0.0008010 0.0006001 0.1800002 0.1819050 0.623737 0.7821490 NA
1 54676 rs2462492 C T -0.0010196 0.0005946 0.0860003 0.0863757 0.400408 NA NA
1 86028 rs114608975 T C 0.0001952 0.0009505 0.8400000 0.8372802 0.103545 0.0277556 NA
1 91536 rs6702460 G T 0.0003636 0.0005853 0.5300002 0.5344412 0.456863 0.4207270 NA
1 234313 rs8179466 C T 0.0014301 0.0011550 0.2200002 0.2156782 0.074434 NA NA
1 534192 rs6680723 C T 0.0008599 0.0006687 0.2000000 0.1985233 0.240911 NA NA
1 546697 rs12025928 A G -0.0008989 0.0008342 0.2800000 0.2811896 0.913467 NA NA
1 693731 rs12238997 A G -0.0000885 0.0005605 0.8700001 0.8745021 0.116343 0.1417730 NA
1 705882 rs72631875 G A -0.0007039 0.0008212 0.3900004 0.3913309 0.067346 0.0315495 NA
1 706368 rs55727773 A G -0.0000650 0.0004152 0.8800001 0.8756509 0.515747 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0000580 0.0006484 0.9299999 0.9287081 0.073666 0.0826677 NA
22 51219006 rs28729663 G A -0.0000753 0.0005006 0.8800001 0.8803989 0.138023 0.2052720 NA
22 51219387 rs9616832 T C -0.0001946 0.0006497 0.7600007 0.7645835 0.073793 0.0654952 NA
22 51219704 rs147475742 G A -0.0000535 0.0008705 0.9500000 0.9510109 0.041992 0.0473243 NA
22 51221190 rs369304721 G A 0.0001178 0.0008690 0.8900000 0.8921283 0.049777 NA NA
22 51221731 rs115055839 T C -0.0001867 0.0006501 0.7700005 0.7739627 0.073287 0.0625000 NA
22 51222100 rs114553188 G T -0.0000969 0.0007656 0.9000000 0.8992897 0.054502 0.0880591 NA
22 51223637 rs375798137 G A -0.0000658 0.0007693 0.9299999 0.9317871 0.054130 0.0788738 NA
22 51229805 rs9616985 T C -0.0001014 0.0006525 0.8800001 0.8765283 0.073125 0.0730831 NA
22 51237063 rs3896457 T C 0.0008189 0.0003992 0.0400000 0.0402321 0.298159 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623737 ES:SE:LP:AF:ID  0.000801049:0.000600076:0.744727:0.623737:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400408 ES:SE:LP:AF:ID  -0.00101957:0.000594559:1.0655:0.400408:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103545 ES:SE:LP:AF:ID  0.000195199:0.000950458:0.0757207:0.103545:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  0.000363616:0.000585306:0.275724:0.456863:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074434 ES:SE:LP:AF:ID  0.00143007:0.00115505:0.657577:0.074434:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240911 ES:SE:LP:AF:ID  0.000859851:0.000668744:0.69897:0.240911:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913467 ES:SE:LP:AF:ID  -0.000898931:0.000834158:0.552842:0.913467:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116343 ES:SE:LP:AF:ID  -8.85326e-05:0.000560537:0.0604807:0.116343:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067346 ES:SE:LP:AF:ID  -0.000703906:0.000821163:0.408935:0.067346:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515747 ES:SE:LP:AF:ID  -6.49681e-05:0.000415172:0.0555173:0.515747:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033041 ES:SE:LP:AF:ID  -0.000936451:0.00104612:0.431798:0.033041:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036662 ES:SE:LP:AF:ID  -0.00106659:0.000950219:0.585027:0.036662:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036778 ES:SE:LP:AF:ID  -0.00102725:0.000946637:0.552842:0.036778:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036473 ES:SE:LP:AF:ID  -0.000911052:0.000953525:0.468521:0.036473:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037011 ES:SE:LP:AF:ID  -0.000948378:0.000942991:0.508638:0.037011:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037112 ES:SE:LP:AF:ID  -0.00103057:0.000939651:0.568636:0.037112:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101232 ES:SE:LP:AF:ID  0.000671751:0.000684938:0.481486:0.101232:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959074 ES:SE:LP:AF:ID  0.000959633:0.000906524:0.537602:0.959074:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  0.00255879:0.0016457:0.920819:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05331  ES:SE:LP:AF:ID  -0.00178235:0.00130777:0.769551:0.05331:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03662  ES:SE:LP:AF:ID  -0.00100689:0.000945878:0.537602:0.03662:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036937 ES:SE:LP:AF:ID  -0.00104206:0.000937251:0.568636:0.036937:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843156 ES:SE:LP:AF:ID  0.000208507:0.000485726:0.173925:0.843156:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055897 ES:SE:LP:AF:ID  -0.000193678:0.000786605:0.091515:0.055897:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122335 ES:SE:LP:AF:ID  -7.09027e-05:0.000531651:0.05061:0.122335:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121578 ES:SE:LP:AF:ID  -1.69181e-05:0.00053187:0.0132283:0.121578:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132387 ES:SE:LP:AF:ID  -0.000284655:0.000524149:0.229148:0.132387:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.03685  ES:SE:LP:AF:ID  -0.000959189:0.000927809:0.522879:0.03685:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838849 ES:SE:LP:AF:ID  0.000119533:0.000470282:0.09691:0.838849:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83847  ES:SE:LP:AF:ID  0.000128819:0.000469757:0.107905:0.83847:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869716 ES:SE:LP:AF:ID  -2.45377e-06:0.000504091:-0:0.869716:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129947 ES:SE:LP:AF:ID  3.94225e-05:0.000505098:0.0268721:0.129947:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037366 ES:SE:LP:AF:ID  -0.00114404:0.000911998:0.677781:0.037366:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03761  ES:SE:LP:AF:ID  -0.00110986:0.000906235:0.657577:0.03761:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869056 ES:SE:LP:AF:ID  -5.98128e-06:0.000503089:0.00436481:0.869056:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869156 ES:SE:LP:AF:ID  -1.80978e-05:0.000503294:0.0132283:0.869156:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037571 ES:SE:LP:AF:ID  -0.00109144:0.000910128:0.638272:0.037571:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869059 ES:SE:LP:AF:ID  -1.84116e-05:0.00050308:0.0132283:0.869059:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837922 ES:SE:LP:AF:ID  0.00014452:0.000468453:0.119186:0.837922:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037586 ES:SE:LP:AF:ID  -0.00106035:0.000911387:0.619789:0.037586:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838552 ES:SE:LP:AF:ID  0.000155579:0.000469768:0.130768:0.838552:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839673 ES:SE:LP:AF:ID  8.87899e-05:0.000476151:0.0705811:0.839673:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869347 ES:SE:LP:AF:ID  1.01228e-05:0.000502527:0.00877392:0.869347:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.8689   ES:SE:LP:AF:ID  4.05078e-06:0.000501288:0.00436481:0.8689:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867842 ES:SE:LP:AF:ID  9.81319e-06:0.00050029:0.00877392:0.867842:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869038 ES:SE:LP:AF:ID  -1.44595e-07:0.000501688:-0:0.869038:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869047 ES:SE:LP:AF:ID  -1.96895e-07:0.000501726:-0:0.869047:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869055 ES:SE:LP:AF:ID  5.37936e-07:0.000501738:-0:0.869055:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86953  ES:SE:LP:AF:ID  8.14925e-06:0.000503097:0.00436481:0.86953:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037637 ES:SE:LP:AF:ID  -0.00109222:0.000906024:0.638272:0.037637:rs114525117