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-9543/UKB-b-9543_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9543/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:52 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9543/UKB-b-9543_data.vcf.gz ...
Read summary statistics for 6625197 SNPs.
Dropped 3733 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, 1249631 SNPs remain.
After merging with regression SNP LD, 1249631 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0502 (0.0039)
Lambda GC: 1.1566
Mean Chi^2: 1.1644
Intercept: 1.014 (0.0071)
Ratio: 0.085 (0.0431)
Analysis finished at Thu Oct 17 14:44:28 2019
Total time elapsed: 1.0m:36.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9323,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 60841,
    "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": 1249631,
    "ldsc_nsnp_merge_regression_ld": 1249631,
    "ldsc_observed_scale_h2_beta": 0.0502,
    "ldsc_observed_scale_h2_se": 0.0039,
    "ldsc_intercept_beta": 1.014,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.1566,
    "ldsc_mean_chisq": 1.1644,
    "ldsc_ratio": 0.0852
}

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 6621486 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 6625197 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 8.664817e+00 5.763722e+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 7.858973e+07 5.647824e+07 828.0000000 3.205774e+07 6.903646e+07 1.144848e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.300000e-05 2.094400e-03 -0.0175586 -1.175100e-03 5.800000e-06 1.192200e-03 1.975710e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.829600e-03 7.603000e-04 0.0010845 1.213700e-03 1.518700e-03 2.258500e-03 9.275100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.781104e-01 2.941804e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.781103e-01 2.941564e-01 0.0000000 2.176235e-01 4.705609e-01 7.328517e-01 9.999998e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.886857e-01 2.581111e-01 0.0217630 7.209900e-02 1.975950e-01 4.492560e-01 9.782370e-01 ▇▃▂▂▁
numeric AF_reference 60841 0.9908167 NA NA NA NA NA NA NA 2.864332e-01 2.503920e-01 0.0000000 8.127000e-02 2.078670e-01 4.412940e-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 0.0015714 0.0019983 0.4299995 0.4316680 0.623742 0.7821490 NA
1 54676 rs2462492 C T 0.0013000 0.0019855 0.5099998 0.5126341 0.399346 NA NA
1 86028 rs114608975 T C -0.0001045 0.0031603 0.9699999 0.9736323 0.103849 0.0277556 NA
1 91536 rs6702460 G T 0.0007054 0.0019552 0.7199992 0.7182749 0.456234 0.4207270 NA
1 234313 rs8179466 C T 0.0021956 0.0038614 0.5700002 0.5696292 0.074497 NA NA
1 534192 rs6680723 C T -0.0018591 0.0022354 0.4100001 0.4055986 0.241217 NA NA
1 546697 rs12025928 A G -0.0018580 0.0027742 0.5000000 0.5030257 0.913083 NA NA
1 693731 rs12238997 A G 0.0007541 0.0018632 0.6899999 0.6856724 0.117049 0.1417730 NA
1 705882 rs72631875 G A 0.0013002 0.0027234 0.6300007 0.6330540 0.067723 0.0315495 NA
1 706368 rs55727773 A G -0.0000139 0.0013801 0.9900000 0.9919536 0.514968 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0050758 0.0021685 0.0189998 0.0192491 0.072670 0.0826677 NA
22 51219006 rs28729663 G A 0.0038846 0.0016712 0.0200000 0.0201074 0.137112 0.2052720 NA
22 51219387 rs9616832 T C 0.0049790 0.0021739 0.0219999 0.0220001 0.072740 0.0654952 NA
22 51219704 rs147475742 G A 0.0058326 0.0029010 0.0439997 0.0443754 0.041680 0.0473243 NA
22 51221190 rs369304721 G A 0.0056756 0.0029076 0.0510000 0.0509397 0.049151 NA NA
22 51221731 rs115055839 T C 0.0051410 0.0021752 0.0179999 0.0181052 0.072229 0.0625000 NA
22 51222100 rs114553188 G T 0.0012529 0.0025471 0.6200004 0.6228035 0.054448 0.0880591 NA
22 51223637 rs375798137 G A 0.0012025 0.0025601 0.6400000 0.6385730 0.054059 0.0788738 NA
22 51229805 rs9616985 T C 0.0055178 0.0021833 0.0109999 0.0114943 0.072078 0.0730831 NA
22 51237063 rs3896457 T C -0.0009217 0.0013279 0.4899999 0.4876136 0.297538 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623742 ES:SE:LP:AF:ID  0.00157136:0.00199832:0.366532:0.623742:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399346 ES:SE:LP:AF:ID  0.00129997:0.00198547:0.29243:0.399346:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103849 ES:SE:LP:AF:ID  -0.000104459:0.00316034:0.0132283:0.103849:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456234 ES:SE:LP:AF:ID  0.000705361:0.00195518:0.142668:0.456234:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074497 ES:SE:LP:AF:ID  0.0021956:0.00386143:0.244125:0.074497:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241217 ES:SE:LP:AF:ID  -0.00185911:0.00223541:0.387216:0.241217:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913083 ES:SE:LP:AF:ID  -0.00185799:0.00277421:0.30103:0.913083:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117049 ES:SE:LP:AF:ID  0.00075409:0.00186317:0.161151:0.117049:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067723 ES:SE:LP:AF:ID  0.00130025:0.00272342:0.200659:0.067723:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514968 ES:SE:LP:AF:ID  -1.3918e-05:0.0013801:0.00436481:0.514968:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033495 ES:SE:LP:AF:ID  0.00655686:0.00345232:1.23657:0.033495:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037207 ES:SE:LP:AF:ID  0.00497472:0.0031342:0.958607:0.037207:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  0.00486599:0.00312183:0.920819:0.037336:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  0.00498552:0.00314575:0.958607:0.036987:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037576 ES:SE:LP:AF:ID  0.00529518:0.0031093:1.05061:0.037576:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037665 ES:SE:LP:AF:ID  0.00548304:0.00309952:1.11351:0.037665:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101517 ES:SE:LP:AF:ID  -0.000357103:0.00227378:0.0555173:0.101517:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958432 ES:SE:LP:AF:ID  -0.0032618:0.00299238:0.552842:0.958432:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031711 ES:SE:LP:AF:ID  -0.00337995:0.00545855:0.267606:0.031711:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052626 ES:SE:LP:AF:ID  -0.00436445:0.00441028:0.49485:0.052626:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037142 ES:SE:LP:AF:ID  0.00485366:0.00312082:0.920819:0.037142:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03747  ES:SE:LP:AF:ID  0.00486299:0.00309307:0.920819:0.03747:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841961 ES:SE:LP:AF:ID  -0.00119084:0.00161303:0.337242:0.841961:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056102 ES:SE:LP:AF:ID  -0.00187818:0.00262051:0.327902:0.056102:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122973 ES:SE:LP:AF:ID  0.000237438:0.00176825:0.05061:0.122973:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025812 ES:SE:LP:AF:ID  0.00884935:0.00434355:1.37675:0.025812:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12219  ES:SE:LP:AF:ID  0.000116506:0.00176918:0.0222764:0.12219:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133423 ES:SE:LP:AF:ID  0.00067056:0.00174038:0.154902:0.133423:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.037413 ES:SE:LP:AF:ID  0.00503922:0.00306135:1:0.037413:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837669 ES:SE:LP:AF:ID  -0.000786896:0.00156208:0.21467:0.837669:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837283 ES:SE:LP:AF:ID  -0.000786021:0.00156035:0.21467:0.837283:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868941 ES:SE:LP:AF:ID  0.000355362:0.00167492:0.0809219:0.868941:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130759 ES:SE:LP:AF:ID  -0.000260008:0.00167827:0.0555173:0.130759:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037906 ES:SE:LP:AF:ID  0.00474758:0.00301117:0.958607:0.037906:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038159 ES:SE:LP:AF:ID  0.00484285:0.00299203:0.958607:0.038159:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868264 ES:SE:LP:AF:ID  0.000354574:0.00167156:0.0809219:0.868264:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868369 ES:SE:LP:AF:ID  0.000357483:0.00167231:0.0809219:0.868369:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038093 ES:SE:LP:AF:ID  0.00505593:0.00300488:1.03621:0.038093:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86826  ES:SE:LP:AF:ID  0.000326792:0.00167146:0.0757207:0.86826:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836771 ES:SE:LP:AF:ID  -0.000835727:0.00155627:0.229148:0.836771:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038104 ES:SE:LP:AF:ID  0.00506003:0.00300901:1.03152:0.038104:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837401 ES:SE:LP:AF:ID  -0.000864061:0.0015606:0.236572:0.837401:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83861  ES:SE:LP:AF:ID  -0.000998508:0.00158194:0.275724:0.83861:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868576 ES:SE:LP:AF:ID  0.000381891:0.00166977:0.0861861:0.868576:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86813  ES:SE:LP:AF:ID  0.000330071:0.00166563:0.0757207:0.86813:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866944 ES:SE:LP:AF:ID  0.000422289:0.00166171:0.09691:0.866944:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86827  ES:SE:LP:AF:ID  0.000279875:0.00166694:0.0604807:0.86827:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868281 ES:SE:LP:AF:ID  0.000281937:0.00166706:0.0604807:0.868281:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86829  ES:SE:LP:AF:ID  0.000276011:0.00166712:0.0604807:0.86829:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868762 ES:SE:LP:AF:ID  0.00038351:0.00167182:0.0861861:0.868762:rs3131954