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-7773/UKB-b-7773_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7773/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7773/UKB-b-7773_data.vcf.gz ...
Read summary statistics for 7554529 SNPs.
Dropped 5270 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, 1276846 SNPs remain.
After merging with regression SNP LD, 1276846 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0082 (0.0013)
Lambda GC: 1.0984
Mean Chi^2: 1.1185
Intercept: 1.0552 (0.0071)
Ratio: 0.466 (0.0596)
Analysis finished at Thu Oct 17 14:42:22 2019
Total time elapsed: 1.0m:27.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9401,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 13,
    "n_p_sig": 545,
    "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": 70141,
    "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": 1276846,
    "ldsc_nsnp_merge_regression_ld": 1276846,
    "ldsc_observed_scale_h2_beta": 0.0082,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0552,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.0984,
    "ldsc_mean_chisq": 1.1185,
    "ldsc_ratio": 0.4658
}

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 7549282 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 7554529 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 8.663083e+00 5.764393e+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 7.866042e+07 5.644081e+07 828.0000000 3.219227e+07 6.909323e+07 1.145482e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.220000e-05 1.365500e-03 -0.0123759 -6.905000e-04 -1.250000e-05 6.672000e-04 1.777330e-02 ▁▅▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.157600e-03 6.275000e-04 0.0005765 6.601000e-04 8.866000e-04 1.493400e-03 6.911500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.856554e-01 2.929407e-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 4.856558e-01 2.929142e-01 0.0000000 2.285400e-01 4.815334e-01 7.393773e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.584031e-01 2.608333e-01 0.0113110 4.490100e-02 1.548600e-01 4.079200e-01 9.886890e-01 ▇▂▂▁▁
numeric AF_reference 70141 0.9907154 NA NA NA NA NA NA NA 2.572886e-01 2.526767e-01 0.0000000 4.972040e-02 1.689300e-01 4.021570e-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 0.0000985 0.0010614 0.9299999 0.9260517 0.623691 0.7821490 NA
1 54676 rs2462492 C T 0.0000038 0.0010512 1.0000000 0.9970779 0.400480 NA NA
1 86028 rs114608975 T C -0.0014031 0.0016814 0.4000000 0.4040194 0.103509 0.0277556 NA
1 91536 rs6702460 G T 0.0005201 0.0010359 0.6200004 0.6156171 0.457052 0.4207270 NA
1 234313 rs8179466 C T -0.0009977 0.0020447 0.6300007 0.6255924 0.074428 NA NA
1 534192 rs6680723 C T 0.0004422 0.0011828 0.7099994 0.7085100 0.241043 NA NA
1 546697 rs12025928 A G 0.0004944 0.0014751 0.7400005 0.7375089 0.913458 NA NA
1 693731 rs12238997 A G 0.0011588 0.0009906 0.2399999 0.2420497 0.116271 0.1417730 NA
1 705882 rs72631875 G A -0.0005864 0.0014508 0.6899999 0.6860984 0.067416 0.0315495 NA
1 706368 rs55727773 A G -0.0001431 0.0007340 0.8499999 0.8454245 0.515712 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0001576 0.0008861 0.8600001 0.8588591 0.137852 0.2052720 NA
22 51219387 rs9616832 T C -0.0006412 0.0011500 0.5800000 0.5771717 0.073752 0.0654952 NA
22 51219704 rs147475742 G A -0.0011257 0.0015421 0.4700002 0.4654278 0.041910 0.0473243 NA
22 51221190 rs369304721 G A -0.0006218 0.0015381 0.6899999 0.6860264 0.049711 NA NA
22 51221731 rs115055839 T C -0.0006488 0.0011506 0.5700002 0.5728361 0.073239 0.0625000 NA
22 51222100 rs114553188 G T 0.0001865 0.0013552 0.8900000 0.8905443 0.054372 0.0880591 NA
22 51223637 rs375798137 G A 0.0001329 0.0013617 0.9199999 0.9222721 0.054006 0.0788738 NA
22 51229805 rs9616985 T C -0.0006185 0.0011548 0.5900000 0.5922317 0.073076 0.0730831 NA
22 51232488 rs376461333 A G -0.0035553 0.0027231 0.1900002 0.1916839 0.019984 NA NA
22 51237063 rs3896457 T C 0.0002802 0.0007060 0.6899999 0.6915034 0.297921 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623691 ES:SE:LP:AF:ID  9.85169e-05:0.00106145:0.0315171:0.623691:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40048  ES:SE:LP:AF:ID  3.84981e-06:0.00105121:-0:0.40048:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103509 ES:SE:LP:AF:ID  -0.00140306:0.00168139:0.39794:0.103509:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457052 ES:SE:LP:AF:ID  0.000520081:0.00103587:0.207608:0.457052:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074428 ES:SE:LP:AF:ID  -0.000997676:0.00204467:0.200659:0.074428:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241043 ES:SE:LP:AF:ID  0.000442203:0.00118281:0.148742:0.241043:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913458 ES:SE:LP:AF:ID  0.000494369:0.00147505:0.130768:0.913458:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116271 ES:SE:LP:AF:ID  0.00115884:0.000990564:0.619789:0.116271:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067416 ES:SE:LP:AF:ID  -0.000586369:0.00145085:0.161151:0.067416:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515712 ES:SE:LP:AF:ID  -0.000143094:0.000733967:0.0705811:0.515712:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033075 ES:SE:LP:AF:ID  -0.000842828:0.00184869:0.187087:0.033075:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036705 ES:SE:LP:AF:ID  -0.000324698:0.00167907:0.0705811:0.036705:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036819 ES:SE:LP:AF:ID  -0.000425032:0.0016728:0.09691:0.036819:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036517 ES:SE:LP:AF:ID  -0.000451086:0.00168486:0.102373:0.036517:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016432 ES:SE:LP:AF:ID  -0.00253347:0.00259388:0.481486:0.016432:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037059 ES:SE:LP:AF:ID  -9.62154e-05:0.00166618:0.0222764:0.037059:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037154 ES:SE:LP:AF:ID  -0.000191627:0.00166052:0.0409586:0.037154:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101375 ES:SE:LP:AF:ID  -0.000548884:0.0012095:0.187087:0.101375:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959093 ES:SE:LP:AF:ID  0.000296341:0.00160308:0.0705811:0.959093:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031509 ES:SE:LP:AF:ID  -0.000385562:0.00290237:0.05061:0.031509:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053269 ES:SE:LP:AF:ID  0.00148983:0.00231447:0.283997:0.053269:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036662 ES:SE:LP:AF:ID  -0.000166715:0.00167131:0.0362122:0.036662:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036986 ES:SE:LP:AF:ID  -0.000101652:0.00165602:0.0222764:0.036986:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843256 ES:SE:LP:AF:ID  -0.000807895:0.000858401:0.455932:0.843256:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055896 ES:SE:LP:AF:ID  0.00235338:0.00139014:1.04576:0.055896:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122298 ES:SE:LP:AF:ID  0.000856022:0.000939336:0.443698:0.122298:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025691 ES:SE:LP:AF:ID  0.00229396:0.00231287:0.49485:0.025691:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121532 ES:SE:LP:AF:ID  0.000812379:0.000939751:0.408935:0.121532:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132377 ES:SE:LP:AF:ID  0.00112887:0.000926232:0.657577:0.132377:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036903 ES:SE:LP:AF:ID  -5.19311e-05:0.00163916:0.0132283:0.036903:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838891 ES:SE:LP:AF:ID  -0.000746922:0.000831166:0.431798:0.838891:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838545 ES:SE:LP:AF:ID  -0.000718787:0.000830311:0.408935:0.838545:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869783 ES:SE:LP:AF:ID  -0.000670952:0.000891063:0.346787:0.869783:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129844 ES:SE:LP:AF:ID  0.000642297:0.000892921:0.327902:0.129844:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037427 ES:SE:LP:AF:ID  -6.66332e-07:0.00161108:-0:0.037427:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037663 ES:SE:LP:AF:ID  5.826e-05:0.00160117:0.0132283:0.037663:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869153 ES:SE:LP:AF:ID  -0.000634158:0.000889382:0.318759:0.869153:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869257 ES:SE:LP:AF:ID  -0.000649904:0.000889734:0.327902:0.869257:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037626 ES:SE:LP:AF:ID  -0.000207423:0.00160792:0.0457575:0.037626:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  -0.000625038:0.000889365:0.318759:0.869154:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837992 ES:SE:LP:AF:ID  -0.000688621:0.00082798:0.387216:0.837992:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037639 ES:SE:LP:AF:ID  -0.000312482:0.00161024:0.0705811:0.037639:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838624 ES:SE:LP:AF:ID  -0.000694287:0.0008303:0.39794:0.838624:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013795 ES:SE:LP:AF:ID  0.00107511:0.00289931:0.148742:0.013795:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.83971  ES:SE:LP:AF:ID  -0.000629187:0.000841434:0.346787:0.83971:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  -0.000765953:0.00088826:0.408935:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86895  ES:SE:LP:AF:ID  -0.000785766:0.000886001:0.420216:0.86895:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86793  ES:SE:LP:AF:ID  -0.000785234:0.000884358:0.431798:0.86793:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -0.000758974:0.000886721:0.408935:0.869089:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869097 ES:SE:LP:AF:ID  -0.000755792:0.000886787:0.408935:0.869097:rs4951862