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-133/UKB-b-133_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-133/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-133/UKB-b-133_data.vcf.gz ...
Read summary statistics for 7926692 SNPs.
Dropped 5985 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, 1281567 SNPs remain.
After merging with regression SNP LD, 1281567 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0098 (0.0091)
Lambda GC: 1.0297
Mean Chi^2: 1.026
Intercept: 1.016 (0.006)
Ratio: 0.6153 (0.2322)
Analysis finished at Thu Oct 17 14:43:43 2019
Total time elapsed: 1.0m:25.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9424,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "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": 73945,
    "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": 1281567,
    "ldsc_nsnp_merge_regression_ld": 1281567,
    "ldsc_observed_scale_h2_beta": 0.0098,
    "ldsc_observed_scale_h2_se": 0.0091,
    "ldsc_intercept_beta": 1.016,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0297,
    "ldsc_mean_chisq": 1.026,
    "ldsc_ratio": 0.6154
}

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 TRUE
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 7920734 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 7926692 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 8.661053e+00 5.763565e+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 7.870147e+07 5.641955e+07 828.0000000 3.225183e+07 6.916413e+07 1.145484e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.610000e-05 6.323500e-03 -0.0645670 -2.959500e-03 -2.140000e-05 2.936000e-03 5.821090e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.392700e-03 3.193300e-03 0.0024840 2.877600e-03 3.983300e-03 7.070400e-03 3.129490e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.961478e-01 2.895880e-01 0.0000008 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.961477e-01 2.895638e-01 0.0000008 2.444499e-01 4.944547e-01 7.467118e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.475604e-01 2.607898e-01 0.0087170 3.676200e-02 1.393610e-01 3.918662e-01 9.912830e-01 ▇▂▂▁▁
numeric AF_reference 73945 0.9906714 NA NA NA NA NA NA NA 2.467562e-01 2.526101e-01 0.0000000 3.913740e-02 1.545530e-01 3.869810e-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 -0.0041275 0.0045645 0.3700002 0.3658536 0.622983 0.7821490 NA
1 54676 rs2462492 C T 0.0054148 0.0045456 0.2300001 0.2335614 0.400511 NA NA
1 86028 rs114608975 T C -0.0015196 0.0072316 0.8300000 0.8335657 0.103660 0.0277556 NA
1 91536 rs6702460 G T 0.0035001 0.0044636 0.4299995 0.4329576 0.457420 0.4207270 NA
1 234313 rs8179466 C T -0.0113531 0.0088063 0.2000000 0.1973299 0.074598 NA NA
1 534192 rs6680723 C T -0.0053818 0.0051034 0.2900000 0.2916322 0.241739 NA NA
1 546697 rs12025928 A G -0.0028544 0.0064449 0.6600001 0.6578471 0.914735 NA NA
1 693731 rs12238997 A G -0.0028946 0.0042751 0.5000000 0.4983634 0.116306 0.1417730 NA
1 705882 rs72631875 G A -0.0031058 0.0062864 0.6200004 0.6212642 0.066989 0.0315495 NA
1 706368 rs55727773 A G 0.0018633 0.0031722 0.5600000 0.5569357 0.514103 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0067992 0.0037927 0.0729995 0.0730216 0.140032 0.2052720 NA
22 51219387 rs9616832 T C 0.0092853 0.0049132 0.0589997 0.0587767 0.075174 0.0654952 NA
22 51219704 rs147475742 G A 0.0081154 0.0065488 0.2200002 0.2152619 0.042894 0.0473243 NA
22 51221190 rs369304721 G A 0.0108604 0.0065834 0.0990011 0.0990096 0.050737 NA NA
22 51221731 rs115055839 T C 0.0091240 0.0049170 0.0640000 0.0635115 0.074670 0.0625000 NA
22 51222100 rs114553188 G T -0.0001651 0.0058230 0.9800000 0.9773760 0.054894 0.0880591 NA
22 51223637 rs375798137 G A -0.0002247 0.0058551 0.9699999 0.9693822 0.054481 0.0788738 NA
22 51229805 rs9616985 T C 0.0097404 0.0049305 0.0479999 0.0482085 0.074546 0.0730831 NA
22 51232488 rs376461333 A G -0.0032171 0.0115732 0.7800007 0.7810283 0.020419 NA NA
22 51237063 rs3896457 T C 0.0030304 0.0030557 0.3200000 0.3213387 0.296294 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.622983 ES:SE:LP:AF:ID  -0.00412752:0.00456449:0.431798:0.622983:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400511 ES:SE:LP:AF:ID  0.00541483:0.00454556:0.638272:0.400511:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10366  ES:SE:LP:AF:ID  -0.00151957:0.00723155:0.0809219:0.10366:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45742  ES:SE:LP:AF:ID  0.00350009:0.0044636:0.366532:0.45742:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074598 ES:SE:LP:AF:ID  -0.0113531:0.00880634:0.69897:0.074598:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241739 ES:SE:LP:AF:ID  -0.0053818:0.00510342:0.537602:0.241739:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.914735 ES:SE:LP:AF:ID  -0.00285437:0.00644491:0.180456:0.914735:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116306 ES:SE:LP:AF:ID  -0.00289455:0.00427513:0.30103:0.116306:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066989 ES:SE:LP:AF:ID  -0.00310585:0.00628639:0.207608:0.066989:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514103 ES:SE:LP:AF:ID  0.00186333:0.00317217:0.251812:0.514103:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032661 ES:SE:LP:AF:ID  -0.00626923:0.00802905:0.366532:0.032661:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036174 ES:SE:LP:AF:ID  -0.00493605:0.00730193:0.30103:0.036174:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036289 ES:SE:LP:AF:ID  -0.00445376:0.00727676:0.267606:0.036289:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035981 ES:SE:LP:AF:ID  -0.00504818:0.007329:0.309804:0.035981:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016642 ES:SE:LP:AF:ID  -0.0108816:0.0110796:0.481486:0.016642:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03652  ES:SE:LP:AF:ID  -0.00483303:0.0072458:0.30103:0.03652:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036597 ES:SE:LP:AF:ID  -0.00492288:0.00722348:0.30103:0.036597:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101417 ES:SE:LP:AF:ID  0.00255825:0.00520366:0.207608:0.101417:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959584 ES:SE:LP:AF:ID  0.00553247:0.00695216:0.366532:0.959584:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031676 ES:SE:LP:AF:ID  -0.0116289:0.0124384:0.455932:0.031676:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053984 ES:SE:LP:AF:ID  -0.00147418:0.00989698:0.0555173:0.053984:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.0362   ES:SE:LP:AF:ID  -0.00362248:0.00726057:0.207608:0.0362:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03645  ES:SE:LP:AF:ID  -0.00249196:0.00720169:0.136677:0.03645:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843662 ES:SE:LP:AF:ID  0.00357553:0.00371224:0.468521:0.843662:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055745 ES:SE:LP:AF:ID  0.00222425:0.00601081:0.148742:0.055745:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122203 ES:SE:LP:AF:ID  -0.00191957:0.00405689:0.19382:0.122203:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.026057 ES:SE:LP:AF:ID  -0.00442538:0.00992701:0.180456:0.026057:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121465 ES:SE:LP:AF:ID  -0.00197746:0.00405843:0.200659:0.121465:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132038 ES:SE:LP:AF:ID  -0.00210958:0.00400864:0.221849:0.132038:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010954 ES:SE:LP:AF:ID  -0.0152416:0.0146171:0.522879:0.010954:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036338 ES:SE:LP:AF:ID  -0.00352222:0.00712537:0.207608:0.036338:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839415 ES:SE:LP:AF:ID  0.0028584:0.00359556:0.366532:0.839415:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.839079 ES:SE:LP:AF:ID  0.00297841:0.00359196:0.387216:0.839079:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.87003  ES:SE:LP:AF:ID  0.00302567:0.00385186:0.366532:0.87003:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129636 ES:SE:LP:AF:ID  -0.00304504:0.00385811:0.366532:0.129636:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036816 ES:SE:LP:AF:ID  -0.00501522:0.00701007:0.327902:0.036816:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037086 ES:SE:LP:AF:ID  -0.00463535:0.006962:0.29243:0.037086:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869449 ES:SE:LP:AF:ID  0.00313186:0.0038458:0.376751:0.869449:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869537 ES:SE:LP:AF:ID  0.00314907:0.00384671:0.387216:0.869537:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037077 ES:SE:LP:AF:ID  -0.00474534:0.00698996:0.30103:0.037077:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869441 ES:SE:LP:AF:ID  0.00305323:0.00384589:0.366532:0.869441:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838616 ES:SE:LP:AF:ID  0.00324274:0.0035857:0.431798:0.838616:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037079 ES:SE:LP:AF:ID  -0.00448603:0.00700013:0.283997:0.037079:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839293 ES:SE:LP:AF:ID  0.00320604:0.00359652:0.431798:0.839293:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01394  ES:SE:LP:AF:ID  -0.000700031:0.0124773:0.0177288:0.01394:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.840467 ES:SE:LP:AF:ID  0.0034443:0.0036454:0.468521:0.840467:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869744 ES:SE:LP:AF:ID  0.00300111:0.00384012:0.366532:0.869744:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869312 ES:SE:LP:AF:ID  0.00337076:0.00382994:0.420216:0.869312:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868191 ES:SE:LP:AF:ID  0.00295057:0.00382466:0.356547:0.868191:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869466 ES:SE:LP:AF:ID  0.00289:0.00383377:0.346787:0.869466:rs4951929