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-9038/UKB-b-9038_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9038/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9038/UKB-b-9038_data.vcf.gz ...
Read summary statistics for 7088242 SNPs.
Dropped 4429 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, 1266313 SNPs remain.
After merging with regression SNP LD, 1266313 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0059 (0.001)
Lambda GC: 1.0952
Mean Chi^2: 1.0968
Intercept: 1.0433 (0.0068)
Ratio: 0.4474 (0.0707)
Analysis finished at Thu Oct 17 14:43:33 2019
Total time elapsed: 1.0m:22.99s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9366,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 2.4788e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 54,
    "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": 65266,
    "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": 1266313,
    "ldsc_nsnp_merge_regression_ld": 1266313,
    "ldsc_observed_scale_h2_beta": 0.0059,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0433,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0952,
    "ldsc_mean_chisq": 1.0968,
    "ldsc_ratio": 0.4473
}

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 7083835 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 7088242 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 8.663744e+00 5.764134e+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 7.864057e+07 5.646297e+07 828.0000000 3.214223e+07 6.906806e+07 1.145305e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.000000e-07 9.050000e-04 -0.0079440 -4.822000e-04 -1.800000e-06 4.782000e-04 7.600800e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.906000e-04 3.779000e-04 0.0004311 4.878000e-04 6.314000e-04 9.971000e-04 4.675000e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.866764e-01 2.925475e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.866781e-01 2.925216e-01 0.0000000 2.294708e-01 4.820222e-01 7.398144e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.729987e-01 2.600383e-01 0.0156910 5.723100e-02 1.754290e-01 4.288070e-01 9.843090e-01 ▇▃▂▁▁
numeric AF_reference 65266 0.9907924 NA NA NA NA NA NA NA 2.713904e-01 2.520061e-01 0.0000000 6.449680e-02 1.878990e-01 4.215260e-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 -0.0003540 0.0007932 0.6600001 0.6554121 0.623782 0.7821490 NA
1 54676 rs2462492 C T 0.0006334 0.0007860 0.4199997 0.4203693 0.400404 NA NA
1 86028 rs114608975 T C -0.0009358 0.0012567 0.4600002 0.4564959 0.103547 0.0277556 NA
1 91536 rs6702460 G T 0.0000316 0.0007738 0.9699999 0.9674043 0.456866 0.4207270 NA
1 234313 rs8179466 C T -0.0010537 0.0015256 0.4899999 0.4897812 0.074517 NA NA
1 534192 rs6680723 C T -0.0004667 0.0008840 0.5999997 0.5974919 0.240936 NA NA
1 546697 rs12025928 A G -0.0004356 0.0011027 0.6899999 0.6927850 0.913470 NA NA
1 693731 rs12238997 A G -0.0007073 0.0007408 0.3400001 0.3396841 0.116322 0.1417730 NA
1 705882 rs72631875 G A 0.0012149 0.0010854 0.2599998 0.2629983 0.067308 0.0315495 NA
1 706368 rs55727773 A G 0.0011139 0.0005488 0.0420001 0.0423678 0.515669 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0004742 0.0006619 0.4700002 0.4737321 0.137952 0.2052720 NA
22 51219387 rs9616832 T C -0.0003181 0.0008591 0.7099994 0.7111886 0.073740 0.0654952 NA
22 51219704 rs147475742 G A 0.0004439 0.0011512 0.6999999 0.6997759 0.041963 0.0473243 NA
22 51221190 rs369304721 G A -0.0001162 0.0011494 0.9199999 0.9195010 0.049733 NA NA
22 51221731 rs115055839 T C -0.0003033 0.0008597 0.7199992 0.7242495 0.073230 0.0625000 NA
22 51222100 rs114553188 G T 0.0010830 0.0010122 0.2800000 0.2846446 0.054460 0.0880591 NA
22 51223637 rs375798137 G A 0.0010979 0.0010172 0.2800000 0.2803971 0.054089 0.0788738 NA
22 51229805 rs9616985 T C -0.0003252 0.0008628 0.7099994 0.7062301 0.073067 0.0730831 NA
22 51232488 rs376461333 A G 0.0013140 0.0020329 0.5199996 0.5180563 0.020042 NA NA
22 51237063 rs3896457 T C 0.0004193 0.0005278 0.4299995 0.4269181 0.297976 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  -0.000353983:0.000793228:0.180456:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400404 ES:SE:LP:AF:ID  0.000633367:0.000786029:0.376751:0.400404:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103547 ES:SE:LP:AF:ID  -0.000935768:0.00125669:0.337242:0.103547:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456866 ES:SE:LP:AF:ID  3.1622e-05:0.000773834:0.0132283:0.456866:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  -0.00105368:0.00152562:0.309804:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240936 ES:SE:LP:AF:ID  -0.000466744:0.000883967:0.221849:0.240936:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91347  ES:SE:LP:AF:ID  -0.000435649:0.00110269:0.161151:0.91347:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116322 ES:SE:LP:AF:ID  -0.000707333:0.000740826:0.468521:0.116322:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067308 ES:SE:LP:AF:ID  0.00121489:0.00108537:0.585027:0.067308:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515669 ES:SE:LP:AF:ID  0.00111393:0.000548764:1.37675:0.515669:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033012 ES:SE:LP:AF:ID  -0.00200588:0.0013832:0.823909:0.033012:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036626 ES:SE:LP:AF:ID  -0.00148947:0.00125646:0.619789:0.036626:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036743 ES:SE:LP:AF:ID  -0.00152202:0.0012517:0.657577:0.036743:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036441 ES:SE:LP:AF:ID  -0.00146322:0.00126074:0.60206:0.036441:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016418 ES:SE:LP:AF:ID  0.00356206:0.00194061:1.18046:0.016418:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03698  ES:SE:LP:AF:ID  -0.00154394:0.00124679:0.657577:0.03698:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037077 ES:SE:LP:AF:ID  -0.00150135:0.00124249:0.638272:0.037077:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  -0.00107608:0.000905349:0.638272:0.10121:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959088 ES:SE:LP:AF:ID  0.0013172:0.00119832:0.568636:0.959088:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031438 ES:SE:LP:AF:ID  0.00201317:0.00217674:0.443698:0.031438:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053268 ES:SE:LP:AF:ID  -0.00144628:0.00173021:0.39794:0.053268:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036595 ES:SE:LP:AF:ID  -0.00148247:0.00125055:0.619789:0.036595:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036911 ES:SE:LP:AF:ID  -0.00150751:0.00123918:0.657577:0.036911:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843201 ES:SE:LP:AF:ID  0.00111732:0.000641984:1.08619:0.843201:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055917 ES:SE:LP:AF:ID  -0.0012262:0.00103948:0.619789:0.055917:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  -0.000857694:0.000702724:0.657577:0.122312:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025722 ES:SE:LP:AF:ID  0.00458636:0.00172809:2.09691:0.025722:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  -0.000900342:0.000703019:0.69897:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  -0.00166654:0.000692902:1.79588:0.13233:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  -0.00157906:0.00122664:0.69897:0.036825:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838942 ES:SE:LP:AF:ID  0.00122884:0.000621717:1.31876:0.838942:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838569 ES:SE:LP:AF:ID  0.00119999:0.000621045:1.27572:0.838569:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  0.00092353:0.000666421:0.769551:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  -0.000856617:0.000667773:0.69897:0.129876:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037338 ES:SE:LP:AF:ID  -0.00156263:0.00120582:0.69897:0.037338:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037582 ES:SE:LP:AF:ID  -0.00147916:0.0011982:0.657577:0.037582:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  0.000904738:0.000665111:0.769551:0.869117:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  0.000896594:0.000665372:0.744727:0.869215:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  -0.00139379:0.00120338:0.60206:0.03754:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86912  ES:SE:LP:AF:ID  0.000894689:0.000665099:0.744727:0.86912:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838022 ES:SE:LP:AF:ID  0.00125105:0.000619322:1.36653:0.838022:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037553 ES:SE:LP:AF:ID  -0.00139896:0.00120508:0.60206:0.037553:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838653 ES:SE:LP:AF:ID  0.00122688:0.000621061:1.31876:0.838653:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839768 ES:SE:LP:AF:ID  0.00124485:0.000629466:1.31876:0.839768:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869401 ES:SE:LP:AF:ID  0.000968395:0.000664334:0.853872:0.869401:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868951 ES:SE:LP:AF:ID  0.000890591:0.000662667:0.744727:0.868951:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8679   ES:SE:LP:AF:ID  0.000951517:0.000661389:0.823909:0.8679:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869093 ES:SE:LP:AF:ID  0.000947858:0.000663207:0.823909:0.869093:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  0.000948029:0.000663258:0.823909:0.869101:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869109 ES:SE:LP:AF:ID  0.000946549:0.000663273:0.823909:0.869109:rs3131956