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-17557/UKB-b-17557_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17557/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17557/UKB-b-17557_data.vcf.gz ...
Read summary statistics for 7654528 SNPs.
Dropped 5439 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, 1278461 SNPs remain.
After merging with regression SNP LD, 1278461 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.027 (0.0015)
Lambda GC: 1.2617
Mean Chi^2: 1.2967
Intercept: 1.0529 (0.0069)
Ratio: 0.1783 (0.0231)
Analysis finished at Thu Oct 17 14:41:50 2019
Total time elapsed: 1.0m:31.04s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9408,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -3.1028e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 9,
    "n_p_sig": 2808,
    "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": 71163,
    "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": 1278461,
    "ldsc_nsnp_merge_regression_ld": 1278461,
    "ldsc_observed_scale_h2_beta": 0.027,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0529,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.2617,
    "ldsc_mean_chisq": 1.2967,
    "ldsc_ratio": 0.1783
}

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 7649113 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 7654528 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 8.662084e+00 5.764358e+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 7.867568e+07 5.644265e+07 828.0000000 3.219672e+07 6.912073e+07 1.145673e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.100000e-06 1.299500e-03 -0.0120713 -6.597000e-04 -5.900000e-06 6.527000e-04 1.261170e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.058000e-03 5.879000e-04 0.0005166 5.928000e-04 8.024000e-04 1.371300e-03 6.203300e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.669742e-01 2.977620e-01 0.0000000 2.000000e-01 4.600002e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.669763e-01 2.977377e-01 0.0000000 2.003703e-01 4.552251e-01 7.248024e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.554127e-01 2.608526e-01 0.0105570 4.257200e-02 1.505610e-01 4.036502e-01 9.894430e-01 ▇▂▂▁▁
numeric AF_reference 71163 0.9907031 NA NA NA NA NA NA NA 2.543985e-01 2.526960e-01 0.0000000 4.672520e-02 1.649360e-01 3.981630e-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 0.0014426 0.0009505 0.1299999 0.1290979 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0009360 0.0009415 0.3200000 0.3201592 0.400406 NA NA
1 86028 rs114608975 T C -0.0036435 0.0015052 0.0150000 0.0154955 0.103563 0.0277556 NA
1 91536 rs6702460 G T 0.0019844 0.0009271 0.0320000 0.0323164 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0002429 0.0018280 0.8900000 0.8943079 0.074504 NA NA
1 534192 rs6680723 C T -0.0015700 0.0010591 0.1400000 0.1382315 0.240945 NA NA
1 546697 rs12025928 A G -0.0008130 0.0013214 0.5400003 0.5383667 0.913508 NA NA
1 693731 rs12238997 A G -0.0008726 0.0008874 0.3300000 0.3254586 0.116354 0.1417730 NA
1 705882 rs72631875 G A 0.0007574 0.0013006 0.5600000 0.5603211 0.067273 0.0315495 NA
1 706368 rs55727773 A G 0.0005458 0.0006574 0.4100001 0.4063694 0.515599 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0021505 0.0007934 0.0066999 0.0067183 0.137947 0.2052720 NA
22 51219387 rs9616832 T C -0.0019047 0.0010299 0.0640000 0.0643893 0.073727 0.0654952 NA
22 51219704 rs147475742 G A -0.0026554 0.0013801 0.0539995 0.0543546 0.041939 0.0473243 NA
22 51221190 rs369304721 G A -0.0030315 0.0013779 0.0280001 0.0277980 0.049719 NA NA
22 51221731 rs115055839 T C -0.0018472 0.0010305 0.0729995 0.0730590 0.073218 0.0625000 NA
22 51222100 rs114553188 G T -0.0023602 0.0012128 0.0519996 0.0516485 0.054475 0.0880591 NA
22 51223637 rs375798137 G A -0.0023051 0.0012187 0.0589997 0.0585674 0.054104 0.0788738 NA
22 51229805 rs9616985 T C -0.0019103 0.0010343 0.0649995 0.0647483 0.073051 0.0730831 NA
22 51232488 rs376461333 A G -0.0044976 0.0024351 0.0649995 0.0647506 0.020054 NA NA
22 51237063 rs3896457 T C -0.0002327 0.0006325 0.7099994 0.7129306 0.297950 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.00144257:0.000950517:0.886057:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.000936002:0.000941528:0.49485:0.400406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  -0.00364354:0.00150523:1.82391:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  0.0019844:0.000927084:1.49485:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074504 ES:SE:LP:AF:ID  0.000242854:0.00182796:0.05061:0.074504:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240945 ES:SE:LP:AF:ID  -0.00156996:0.00105906:0.853872:0.240945:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913508 ES:SE:LP:AF:ID  -0.000813031:0.00132139:0.267606:0.913508:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  -0.00087256:0.000887377:0.481486:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067273 ES:SE:LP:AF:ID  0.000757435:0.00130062:0.251812:0.067273:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515599 ES:SE:LP:AF:ID  0.000545839:0.0006574:0.387216:0.515599:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  0.00270716:0.00165807:1:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  0.00208467:0.00150601:0.769551:0.036594:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036711 ES:SE:LP:AF:ID  0.00217257:0.00150031:0.823909:0.036711:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036411 ES:SE:LP:AF:ID  0.00223016:0.0015111:0.853872:0.036411:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016396 ES:SE:LP:AF:ID  0.00258531:0.00232687:0.568636:0.016396:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03695  ES:SE:LP:AF:ID  0.00227768:0.00149436:0.886057:0.03695:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037046 ES:SE:LP:AF:ID  0.00230249:0.00148927:0.920819:0.037046:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  -0.000653032:0.0010844:0.259637:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959119 ES:SE:LP:AF:ID  -0.00234415:0.00143627:1:0.959119:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  -0.000629333:0.00260641:0.091515:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05328  ES:SE:LP:AF:ID  -0.00178325:0.00207256:0.408935:0.05328:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036565 ES:SE:LP:AF:ID  0.00235103:0.00149886:0.920819:0.036565:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036879 ES:SE:LP:AF:ID  0.00243881:0.00148526:1:0.036879:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843219 ES:SE:LP:AF:ID  -0.000133998:0.000769131:0.0655015:0.843219:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055932 ES:SE:LP:AF:ID  -0.00178837:0.00124508:0.823909:0.055932:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122326 ES:SE:LP:AF:ID  -0.000582302:0.000841782:0.309804:0.122326:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025683 ES:SE:LP:AF:ID  -0.00416915:0.00207181:1.35655:0.025683:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12157  ES:SE:LP:AF:ID  -0.000569889:0.000842132:0.30103:0.12157:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132331 ES:SE:LP:AF:ID  -0.000141836:0.000830099:0.0655015:0.132331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011145 ES:SE:LP:AF:ID  0.00396129:0.00301612:0.721246:0.011145:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036795 ES:SE:LP:AF:ID  0.00231596:0.00147023:0.920819:0.036795:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838954 ES:SE:LP:AF:ID  -0.000295322:0.00074483:0.161151:0.838954:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838582 ES:SE:LP:AF:ID  -0.000284969:0.00074403:0.154902:0.838582:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869756 ES:SE:LP:AF:ID  4.48877e-05:0.000798335:0.0177288:0.869756:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  -0.000125535:0.00079996:0.0555173:0.129892:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037306 ES:SE:LP:AF:ID  0.00233814:0.00144529:0.958607:0.037306:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  0.00229693:0.00143615:0.958607:0.03755:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869099 ES:SE:LP:AF:ID  1.91863e-05:0.000796775:0.00877392:0.869099:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869196 ES:SE:LP:AF:ID  3.20616e-05:0.00079709:0.0132283:0.869196:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037508 ES:SE:LP:AF:ID  0.00232657:0.00144237:0.958607:0.037508:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  2.55948e-05:0.000796759:0.0132283:0.869101:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838034 ES:SE:LP:AF:ID  -0.000367174:0.000741961:0.207608:0.838034:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037521 ES:SE:LP:AF:ID  0.00239275:0.00144439:1.00877:0.037521:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  -0.000316906:0.000744046:0.173925:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013784 ES:SE:LP:AF:ID  -0.00383963:0.00259589:0.853872:0.013784:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -0.000315471:0.000754109:0.167491:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869381 ES:SE:LP:AF:ID  3.62069e-05:0.000795831:0.0177288:0.869381:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868927 ES:SE:LP:AF:ID  6.14244e-05:0.000793825:0.0268721:0.868927:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86788  ES:SE:LP:AF:ID  9.54707e-05:0.00079231:0.0457575:0.86788:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869071 ES:SE:LP:AF:ID  -1.22707e-08:0.000794477:-0:0.869071:rs4951929