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-4106/UKB-b-4106_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4106/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:02 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4106/UKB-b-4106_data.vcf.gz ...
Read summary statistics for 6566230 SNPs.
Dropped 3626 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, 1246913 SNPs remain.
After merging with regression SNP LD, 1246913 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0422 (0.0081)
Lambda GC: 1.0677
Mean Chi^2: 1.066
Intercept: 1.0178 (0.0068)
Ratio: 0.27 (0.1033)
Analysis finished at Thu Oct 17 14:45:22 2019
Total time elapsed: 1.0m:19.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9316,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 8.5766e-06,
    "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": 60247,
    "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": 1246913,
    "ldsc_nsnp_merge_regression_ld": 1246913,
    "ldsc_observed_scale_h2_beta": 0.0422,
    "ldsc_observed_scale_h2_se": 0.0081,
    "ldsc_intercept_beta": 1.0178,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0677,
    "ldsc_mean_chisq": 1.066,
    "ldsc_ratio": 0.2697
}

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 6562626 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 6566230 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 8.665892e+00 5.763987e+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 7.858517e+07 5.648500e+07 828.0000000 3.204973e+07 6.902144e+07 1.144938e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.600000e-06 4.597100e-03 -0.0426476 -2.589900e-03 6.600000e-06 2.615200e-03 3.870630e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.157400e-03 1.695300e-03 0.0024865 2.782200e-03 3.467200e-03 5.116900e-03 2.152440e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.898406e-01 2.910382e-01 0.0000012 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.898409e-01 2.910123e-01 0.0000012 2.352671e-01 4.857632e-01 7.417977e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.907761e-01 2.577967e-01 0.0226950 7.420400e-02 2.004740e-01 4.517260e-01 9.773050e-01 ▇▃▂▂▁
numeric AF_reference 60247 0.9908247 NA NA NA NA NA NA NA 2.884169e-01 2.501195e-01 0.0000000 8.346650e-02 2.104630e-01 4.438900e-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 0.0003708 0.0045536 0.9400001 0.9350988 0.623509 0.7821490 NA
1 54676 rs2462492 C T 0.0052818 0.0045342 0.2399999 0.2440679 0.399954 NA NA
1 86028 rs114608975 T C 0.0080937 0.0071874 0.2599998 0.2601256 0.103790 0.0277556 NA
1 91536 rs6702460 G T 0.0096448 0.0044657 0.0309999 0.0307916 0.455534 0.4207270 NA
1 234313 rs8179466 C T 0.0012474 0.0087227 0.8900000 0.8862900 0.074874 NA NA
1 534192 rs6680723 C T -0.0033171 0.0050875 0.5099998 0.5143944 0.241426 NA NA
1 546697 rs12025928 A G 0.0000088 0.0063457 1.0000000 0.9988887 0.913453 NA NA
1 693731 rs12238997 A G -0.0011002 0.0042733 0.8000000 0.7968212 0.115841 0.1417730 NA
1 705882 rs72631875 G A 0.0017489 0.0063031 0.7800007 0.7814265 0.066819 0.0315495 NA
1 706368 rs55727773 A G 0.0047353 0.0031610 0.1299999 0.1341253 0.514763 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0002323 0.0049556 0.9599999 0.9626175 0.073596 0.0826677 NA
22 51219006 rs28729663 G A -0.0007805 0.0038247 0.8400000 0.8382991 0.137452 0.2052720 NA
22 51219387 rs9616832 T C -0.0000210 0.0049668 1.0000000 0.9966323 0.073673 0.0654952 NA
22 51219704 rs147475742 G A -0.0024132 0.0067077 0.7199992 0.7190202 0.041209 0.0473243 NA
22 51221190 rs369304721 G A -0.0036883 0.0066292 0.5800000 0.5779555 0.049905 NA NA
22 51221731 rs115055839 T C -0.0000726 0.0049672 0.9900000 0.9883332 0.073255 0.0625000 NA
22 51222100 rs114553188 G T -0.0020488 0.0058636 0.7300002 0.7267867 0.054113 0.0880591 NA
22 51223637 rs375798137 G A -0.0021645 0.0058931 0.7099994 0.7134000 0.053713 0.0788738 NA
22 51229805 rs9616985 T C 0.0002007 0.0049841 0.9699999 0.9678790 0.073130 0.0730831 NA
22 51237063 rs3896457 T C 0.0011179 0.0030471 0.7099994 0.7137268 0.299891 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623509 ES:SE:LP:AF:ID  0.000370805:0.00455358:0.0268721:0.623509:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399954 ES:SE:LP:AF:ID  0.00528183:0.00453423:0.619789:0.399954:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10379  ES:SE:LP:AF:ID  0.00809369:0.0071874:0.585027:0.10379:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455534 ES:SE:LP:AF:ID  0.0096448:0.00446569:1.50864:0.455534:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074874 ES:SE:LP:AF:ID  0.00124735:0.00872271:0.05061:0.074874:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241426 ES:SE:LP:AF:ID  -0.00331709:0.00508748:0.29243:0.241426:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913453 ES:SE:LP:AF:ID  8.83799e-06:0.00634567:-0:0.913453:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115841 ES:SE:LP:AF:ID  -0.00110022:0.00427331:0.09691:0.115841:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066819 ES:SE:LP:AF:ID  0.00174887:0.00630313:0.107905:0.066819:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514763 ES:SE:LP:AF:ID  0.00473526:0.00316099:0.886057:0.514763:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033079 ES:SE:LP:AF:ID  -0.00271541:0.00798702:0.136677:0.033079:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036865 ES:SE:LP:AF:ID  -0.0023031:0.00723086:0.124939:0.036865:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  -0.00181753:0.00720459:0.09691:0.036987:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036666 ES:SE:LP:AF:ID  -0.00180703:0.00726238:0.09691:0.036666:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037187 ES:SE:LP:AF:ID  -0.000185862:0.00718104:0.00877392:0.037187:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037333 ES:SE:LP:AF:ID  -0.000419784:0.00714925:0.0222764:0.037333:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100532 ES:SE:LP:AF:ID  0.00102661:0.00521931:0.0757207:0.100532:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958808 ES:SE:LP:AF:ID  0.00262469:0.00690712:0.154902:0.958808:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031554 ES:SE:LP:AF:ID  0.0139026:0.0124479:0.585027:0.031554:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052815 ES:SE:LP:AF:ID  0.00397855:0.0100626:0.161151:0.052815:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  -0.00153379:0.00719469:0.0809219:0.036825:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037143 ES:SE:LP:AF:ID  -0.000628472:0.00713065:0.0315171:0.037143:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843553 ES:SE:LP:AF:ID  0.00248452:0.0037086:0.30103:0.843553:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055516 ES:SE:LP:AF:ID  -0.00121069:0.00600984:0.0757207:0.055516:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121634 ES:SE:LP:AF:ID  -0.00124735:0.00405823:0.119186:0.121634:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025561 ES:SE:LP:AF:ID  -0.00242904:0.00997964:0.091515:0.025561:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.120916 ES:SE:LP:AF:ID  -0.00146354:0.00405974:0.142668:0.120916:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.131366 ES:SE:LP:AF:ID  -0.00245465:0.00401225:0.267606:0.131366:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036924 ES:SE:LP:AF:ID  -0.00103916:0.00707163:0.0555173:0.036924:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838934 ES:SE:LP:AF:ID  0.0015129:0.00358514:0.173925:0.838934:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838528 ES:SE:LP:AF:ID  0.00179887:0.00358048:0.207608:0.838528:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869949 ES:SE:LP:AF:ID  0.00104901:0.00384344:0.107905:0.869949:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129615 ES:SE:LP:AF:ID  -0.00117984:0.00385181:0.119186:0.129615:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037466 ES:SE:LP:AF:ID  -0.000217002:0.00694821:0.00877392:0.037466:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037701 ES:SE:LP:AF:ID  -0.000349666:0.00690618:0.0177288:0.037701:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869316 ES:SE:LP:AF:ID  0.00129858:0.00383564:0.136677:0.869316:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869406 ES:SE:LP:AF:ID  0.00124533:0.00383681:0.124939:0.869406:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037697 ES:SE:LP:AF:ID  4.60032e-05:0.00693208:0.00436481:0.037697:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869317 ES:SE:LP:AF:ID  0.00128293:0.00383569:0.130768:0.869317:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837997 ES:SE:LP:AF:ID  0.0020208:0.00357242:0.244125:0.837997:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037715 ES:SE:LP:AF:ID  9.35273e-05:0.00693935:0.00436481:0.037715:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838598 ES:SE:LP:AF:ID  0.00184728:0.00358278:0.21467:0.838598:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839804 ES:SE:LP:AF:ID  0.00147231:0.0036317:0.161151:0.839804:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869638 ES:SE:LP:AF:ID  0.000916607:0.00383174:0.091515:0.869638:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869136 ES:SE:LP:AF:ID  0.000737604:0.00382108:0.0705811:0.869136:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868132 ES:SE:LP:AF:ID  0.000800098:0.00381428:0.0809219:0.868132:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869302 ES:SE:LP:AF:ID  0.000650152:0.00382457:0.0604807:0.869302:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869307 ES:SE:LP:AF:ID  0.000654533:0.00382485:0.0655015:0.869307:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869315 ES:SE:LP:AF:ID  0.000647916:0.00382491:0.0604807:0.869315:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869803 ES:SE:LP:AF:ID  0.00101954:0.00383574:0.102373:0.869803:rs3131954