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-16369/UKB-b-16369_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16369/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16369/UKB-b-16369_data.vcf.gz ...
Read summary statistics for 8302467 SNPs.
Dropped 6720 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, 1284420 SNPs remain.
After merging with regression SNP LD, 1284420 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0076 (0.0013)
Lambda GC: 1.1348
Mean Chi^2: 1.1325
Intercept: 1.0639 (0.007)
Ratio: 0.4819 (0.053)
Analysis finished at Thu Oct 17 14:46:30 2019
Total time elapsed: 1.0m:29.32s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9446,
    "inflation_factor": 1.0966,
    "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": 78104,
    "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": 1284420,
    "ldsc_nsnp_merge_regression_ld": 1284420,
    "ldsc_observed_scale_h2_beta": 0.0076,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0639,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.1348,
    "ldsc_mean_chisq": 1.1325,
    "ldsc_ratio": 0.4823
}

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 8295777 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 8302467 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 8.655133e+00 5.762356e+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 7.873773e+07 5.638530e+07 828.0000000 3.233066e+07 6.923065e+07 1.145476e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.610000e-05 1.738800e-03 -0.0184747 -7.691000e-04 3.000000e-06 7.807000e-04 1.840160e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.410800e-03 9.051000e-04 0.0006011 7.020000e-04 1.004400e-03 1.880200e-03 9.393100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.829581e-01 2.929727e-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 4.829592e-01 2.929463e-01 0.0000000 2.255898e-01 4.754094e-01 7.370070e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.373348e-01 2.602459e-01 0.0067050 3.010500e-02 1.253300e-01 3.758910e-01 9.932940e-01 ▇▂▂▁▁
numeric AF_reference 78104 0.9905927 NA NA NA NA NA NA NA 2.368302e-01 2.521356e-01 0.0000000 2.995210e-02 1.411740e-01 3.720050e-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 0.0009700 0.0011059 0.3800004 0.3804364 0.623794 0.7821490 NA
1 54676 rs2462492 C T -0.0020008 0.0010959 0.0680002 0.0678833 0.400395 NA NA
1 86028 rs114608975 T C -0.0009998 0.0017520 0.5700002 0.5682087 0.103548 0.0277556 NA
1 91536 rs6702460 G T -0.0011535 0.0010789 0.2900000 0.2850076 0.456873 0.4207270 NA
1 234313 rs8179466 C T 0.0012804 0.0021272 0.5500004 0.5472118 0.074513 NA NA
1 534192 rs6680723 C T -0.0002140 0.0012324 0.8600001 0.8621300 0.240946 NA NA
1 546697 rs12025928 A G -0.0027633 0.0015376 0.0719996 0.0723077 0.913483 NA NA
1 693731 rs12238997 A G 0.0011673 0.0010328 0.2599998 0.2584106 0.116327 0.1417730 NA
1 705882 rs72631875 G A 0.0020817 0.0015133 0.1700000 0.1689505 0.067308 0.0315495 NA
1 706368 rs55727773 A G -0.0018314 0.0007651 0.0170000 0.0166819 0.515669 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0006607 0.0009231 0.4700002 0.4741084 0.137957 0.2052720 NA
22 51219387 rs9616832 T C 0.0000595 0.0011981 0.9599999 0.9604228 0.073739 0.0654952 NA
22 51219704 rs147475742 G A -0.0010548 0.0016053 0.5099998 0.5111550 0.041962 0.0473243 NA
22 51221190 rs369304721 G A -0.0000532 0.0016028 0.9699999 0.9735210 0.049729 NA NA
22 51221731 rs115055839 T C 0.0001316 0.0011988 0.9100000 0.9126082 0.073229 0.0625000 NA
22 51222100 rs114553188 G T 0.0015918 0.0014114 0.2599998 0.2594233 0.054466 0.0880591 NA
22 51223637 rs375798137 G A 0.0016582 0.0014183 0.2399999 0.2423499 0.054095 0.0788738 NA
22 51229805 rs9616985 T C 0.0001006 0.0012032 0.9299999 0.9333980 0.073066 0.0730831 NA
22 51232488 rs376461333 A G -0.0018839 0.0028349 0.5099998 0.5063458 0.020043 NA NA
22 51237063 rs3896457 T C 0.0002637 0.0007360 0.7199992 0.7201081 0.297963 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623794 ES:SE:LP:AF:ID  0.000970003:0.00110593:0.420216:0.623794:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400395 ES:SE:LP:AF:ID  -0.0020008:0.00109586:1.16749:0.400395:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103548 ES:SE:LP:AF:ID  -0.000999846:0.00175199:0.244125:0.103548:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456873 ES:SE:LP:AF:ID  -0.00115345:0.00107886:0.537602:0.456873:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.00128043:0.00212716:0.259637:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240946 ES:SE:LP:AF:ID  -0.000214021:0.00123239:0.0655015:0.240946:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913483 ES:SE:LP:AF:ID  -0.00276332:0.00153759:1.14267:0.913483:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116327 ES:SE:LP:AF:ID  0.00116727:0.00103284:0.585027:0.116327:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067308 ES:SE:LP:AF:ID  0.00208174:0.00151335:0.769551:0.067308:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515669 ES:SE:LP:AF:ID  -0.00183138:0.000765101:1.76955:0.515669:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033007 ES:SE:LP:AF:ID  0.000419732:0.00192865:0.0809219:0.033007:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036623 ES:SE:LP:AF:ID  0.000473007:0.00175188:0.102373:0.036623:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  0.000659192:0.00174523:0.148742:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036438 ES:SE:LP:AF:ID  0.000545236:0.00175784:0.119186:0.036438:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016418 ES:SE:LP:AF:ID  0.00132724:0.00270564:0.207608:0.016418:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036978 ES:SE:LP:AF:ID  0.000460839:0.00173837:0.102373:0.036978:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037075 ES:SE:LP:AF:ID  0.000540996:0.00173238:0.124939:0.037075:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101208 ES:SE:LP:AF:ID  0.000526053:0.00126231:0.167491:0.101208:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959092 ES:SE:LP:AF:ID  -0.00100775:0.00167082:0.259637:0.959092:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031437 ES:SE:LP:AF:ID  0.00180028:0.00303508:0.259637:0.031437:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053266 ES:SE:LP:AF:ID  -0.0014725:0.00241246:0.267606:0.053266:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  0.000630156:0.00174362:0.142668:0.036592:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036907 ES:SE:LP:AF:ID  0.000559565:0.00172776:0.124939:0.036907:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  -0.00136896:0.000895088:0.886057:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055911 ES:SE:LP:AF:ID  0.000509029:0.00144936:0.136677:0.055911:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  0.00116048:0.000979763:0.619789:0.122312:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025717 ES:SE:LP:AF:ID  -0.00471396:0.00240973:1.30103:0.025717:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  0.00113287:0.000980173:0.60206:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132328 ES:SE:LP:AF:ID  0.00129797:0.000966071:0.744727:0.132328:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  0.00246865:0.0035132:0.318759:0.01113:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036822 ES:SE:LP:AF:ID  0.000643411:0.0017103:0.148742:0.036822:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838947 ES:SE:LP:AF:ID  -0.00138184:0.000866832:0.958607:0.838947:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838576 ES:SE:LP:AF:ID  -0.00135202:0.000865898:0.920819:0.838576:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869778 ES:SE:LP:AF:ID  -0.00113735:0.000929151:0.657577:0.869778:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  0.00119684:0.000931033:0.69897:0.129876:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037333 ES:SE:LP:AF:ID  0.000472852:0.00168128:0.107905:0.037333:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037577 ES:SE:LP:AF:ID  0.000598987:0.00167067:0.142668:0.037577:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  -0.00115667:0.000927325:0.677781:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  -0.00118905:0.000927689:0.69897:0.869216:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037536 ES:SE:LP:AF:ID  0.000314107:0.00167788:0.0705811:0.037536:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.00114668:0.000927308:0.657577:0.869122:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838028 ES:SE:LP:AF:ID  -0.00131848:0.000863491:0.886057:0.838028:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037548 ES:SE:LP:AF:ID  0.000395471:0.00168026:0.091515:0.037548:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838658 ES:SE:LP:AF:ID  -0.00131601:0.000865916:0.886057:0.838658:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  -0.0030169:0.00302233:0.49485:0.013776:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839773 ES:SE:LP:AF:ID  -0.00140908:0.000877632:0.958607:0.839773:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869402 ES:SE:LP:AF:ID  -0.00114853:0.000926241:0.677781:0.869402:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.00111842:0.000923919:0.638272:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867902 ES:SE:LP:AF:ID  -0.00120275:0.000922138:0.721246:0.867902:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869094 ES:SE:LP:AF:ID  -0.00116092:0.000924671:0.677781:0.869094:rs4951929