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-8446/UKB-b-8446_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8446/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8446/UKB-b-8446_data.vcf.gz ...
Read summary statistics for 7876576 SNPs.
Dropped 5893 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, 1281148 SNPs remain.
After merging with regression SNP LD, 1281148 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0242 (0.0015)
Lambda GC: 1.2308
Mean Chi^2: 1.2615
Intercept: 1.0402 (0.0075)
Ratio: 0.1538 (0.0287)
Analysis finished at Thu Oct 17 14:44:03 2019
Total time elapsed: 2.0m:9.63s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9422,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 16,
    "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": 73451,
    "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": 1281148,
    "ldsc_nsnp_merge_regression_ld": 1281148,
    "ldsc_observed_scale_h2_beta": 0.0242,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0402,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.2308,
    "ldsc_mean_chisq": 1.2615,
    "ldsc_ratio": 0.1537
}

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 7870710 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 7876576 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 8.661283e+00 5.763742e+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 7.870338e+07 5.642582e+07 828.0000000 3.224459e+07 6.917072e+07 1.145580e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.100000e-05 1.465100e-03 -0.0127046 -6.985000e-04 9.900000e-06 7.309000e-04 1.408010e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.188700e-03 6.958000e-04 0.0005546 6.402000e-04 8.823000e-04 1.556200e-03 6.827900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.699900e-01 2.965140e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.699900e-01 2.964906e-01 0.0000000 2.058746e-01 4.588933e-01 7.269027e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.489823e-01 2.608048e-01 0.0090410 3.779100e-02 1.413820e-01 3.940852e-01 9.909590e-01 ▇▂▂▁▁
numeric AF_reference 73451 0.9906748 NA NA NA NA NA NA NA 2.481586e-01 2.526410e-01 0.0000000 4.053510e-02 1.565500e-01 3.889780e-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 0.0005124 0.0010204 0.6200004 0.6155854 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0004735 0.0010109 0.6400000 0.6395298 0.400410 NA NA
1 86028 rs114608975 T C -0.0002559 0.0016163 0.8700001 0.8741955 0.103551 0.0277556 NA
1 91536 rs6702460 G T -0.0009606 0.0009954 0.3300000 0.3345221 0.456857 0.4207270 NA
1 234313 rs8179466 C T 0.0007907 0.0019625 0.6899999 0.6870170 0.074510 NA NA
1 534192 rs6680723 C T -0.0011385 0.0011370 0.3200000 0.3166768 0.240954 NA NA
1 546697 rs12025928 A G 0.0025443 0.0014184 0.0729995 0.0728413 0.913470 NA NA
1 693731 rs12238997 A G -0.0013030 0.0009528 0.1700000 0.1714605 0.116333 0.1417730 NA
1 705882 rs72631875 G A 0.0003611 0.0013962 0.8000000 0.7959420 0.067286 0.0315495 NA
1 706368 rs55727773 A G 0.0001058 0.0007058 0.8800001 0.8808428 0.515637 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0003789 0.0008517 0.6600001 0.6563508 0.137942 0.2052720 NA
22 51219387 rs9616832 T C 0.0001375 0.0011055 0.9000000 0.9010241 0.073736 0.0654952 NA
22 51219704 rs147475742 G A 0.0007703 0.0014814 0.5999997 0.6030726 0.041953 0.0473243 NA
22 51221190 rs369304721 G A 0.0012388 0.0014790 0.4000000 0.4022410 0.049726 NA NA
22 51221731 rs115055839 T C 0.0002216 0.0011062 0.8400000 0.8412593 0.073226 0.0625000 NA
22 51222100 rs114553188 G T -0.0000393 0.0013022 0.9800000 0.9759338 0.054462 0.0880591 NA
22 51223637 rs375798137 G A -0.0000133 0.0013085 0.9900000 0.9919129 0.054091 0.0788738 NA
22 51229805 rs9616985 T C -0.0000502 0.0011102 0.9599999 0.9639362 0.073062 0.0730831 NA
22 51232488 rs376461333 A G 0.0002931 0.0026153 0.9100000 0.9107555 0.020042 NA NA
22 51237063 rs3896457 T C -0.0004017 0.0006790 0.5500004 0.5540918 0.297984 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.000512375:0.00102043:0.207608:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40041  ES:SE:LP:AF:ID  -0.000473452:0.00101088:0.19382:0.40041:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103551 ES:SE:LP:AF:ID  -0.000255913:0.00161631:0.0604807:0.103551:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456857 ES:SE:LP:AF:ID  -0.000960581:0.000995374:0.481486:0.456857:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07451  ES:SE:LP:AF:ID  0.000790712:0.00196252:0.161151:0.07451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240954 ES:SE:LP:AF:ID  -0.00113853:0.00113704:0.49485:0.240954:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91347  ES:SE:LP:AF:ID  0.00254427:0.00141835:1.13668:0.91347:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116333 ES:SE:LP:AF:ID  -0.00130298:0.000952801:0.769551:0.116333:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067286 ES:SE:LP:AF:ID  0.000361071:0.00139624:0.09691:0.067286:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515637 ES:SE:LP:AF:ID  0.000105802:0.000705813:0.0555173:0.515637:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033003 ES:SE:LP:AF:ID  -7.89723e-05:0.00177942:0.0177288:0.033003:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03662  ES:SE:LP:AF:ID  -0.000455242:0.0016163:0.107905:0.03662:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036736 ES:SE:LP:AF:ID  -0.00064191:0.00161018:0.161151:0.036736:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036435 ES:SE:LP:AF:ID  -0.000434882:0.0016218:0.102373:0.036435:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016406 ES:SE:LP:AF:ID  0.000887713:0.00249719:0.142668:0.016406:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036975 ES:SE:LP:AF:ID  -0.000607409:0.00160382:0.154902:0.036975:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037071 ES:SE:LP:AF:ID  -0.000581597:0.00159832:0.142668:0.037071:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101209 ES:SE:LP:AF:ID  0.000692737:0.00116444:0.259637:0.101209:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959098 ES:SE:LP:AF:ID  0.000208606:0.0015416:0.05061:0.959098:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031447 ES:SE:LP:AF:ID  0.00058453:0.0027988:0.0809219:0.031447:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  -0.00278796:0.0022259:0.677781:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  -0.000501538:0.00160866:0.119186:0.03659:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036906 ES:SE:LP:AF:ID  -0.000346594:0.00159401:0.0809219:0.036906:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84321  ES:SE:LP:AF:ID  0.00133549:0.000825759:0.958607:0.84321:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055918 ES:SE:LP:AF:ID  -0.00167278:0.00133693:0.677781:0.055918:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  -0.00150576:0.000903846:1.01773:0.122312:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025712 ES:SE:LP:AF:ID  0.000848518:0.00222329:0.154902:0.025712:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  -0.00145403:0.000904227:0.958607:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132334 ES:SE:LP:AF:ID  -0.00170318:0.000891208:1.25181:0.132334:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011134 ES:SE:LP:AF:ID  0.00283126:0.00324037:0.420216:0.011134:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.03682  ES:SE:LP:AF:ID  -0.00030124:0.00157791:0.0705811:0.03682:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838949 ES:SE:LP:AF:ID  0.000946928:0.000799696:0.619789:0.838949:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838578 ES:SE:LP:AF:ID  0.00102862:0.000798835:0.69897:0.838578:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  0.000969152:0.000857184:0.585027:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129874 ES:SE:LP:AF:ID  -0.00127268:0.000858932:0.853872:0.129874:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037331 ES:SE:LP:AF:ID  -0.000405587:0.00155116:0.102373:0.037331:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037575 ES:SE:LP:AF:ID  -0.000385285:0.00154136:0.09691:0.037575:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  0.0010612:0.000855505:0.677781:0.869119:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869217 ES:SE:LP:AF:ID  0.00104821:0.000855845:0.657577:0.869217:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037533 ES:SE:LP:AF:ID  -0.000371356:0.00154803:0.091515:0.037533:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  0.00105499:0.000855488:0.657577:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838031 ES:SE:LP:AF:ID  0.00102913:0.000796617:0.69897:0.838031:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.000301277:0.00155021:0.0705811:0.037545:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838662 ES:SE:LP:AF:ID  0.00105958:0.000798857:0.744727:0.838662:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  -0.00344775:0.00278826:0.657577:0.013775:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839775 ES:SE:LP:AF:ID  0.000990694:0.00080966:0.657577:0.839775:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  0.00101661:0.000854498:0.638272:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868947 ES:SE:LP:AF:ID  0.00103505:0.000852347:0.657577:0.868947:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867899 ES:SE:LP:AF:ID  0.0010924:0.000850713:0.69897:0.867899:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86909  ES:SE:LP:AF:ID  0.000990087:0.000853045:0.60206:0.86909:rs4951929