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-18009/UKB-b-18009_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18009/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18009/UKB-b-18009_data.vcf.gz ...
Read summary statistics for 8033326 SNPs.
Dropped 6187 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, 1282670 SNPs remain.
After merging with regression SNP LD, 1282670 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1004 (0.0053)
Lambda GC: 1.3658
Mean Chi^2: 1.5445
Intercept: 1.044 (0.0106)
Ratio: 0.0808 (0.0194)
Analysis finished at Thu Oct 17 14:41:50 2019
Total time elapsed: 1.0m:31.6s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9432,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -3.4645e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 96,
    "n_p_sig": 5765,
    "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": 75025,
    "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": 1282670,
    "ldsc_nsnp_merge_regression_ld": 1282670,
    "ldsc_observed_scale_h2_beta": 0.1004,
    "ldsc_observed_scale_h2_se": 0.0053,
    "ldsc_intercept_beta": 1.044,
    "ldsc_intercept_se": 0.0106,
    "ldsc_lambda_gc": 1.3658,
    "ldsc_mean_chisq": 1.5445,
    "ldsc_ratio": 0.0808
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 8027166 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 8033326 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 8.660403e+00 5.763568e+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 7.870827e+07 5.640971e+07 828.0000000 3.227396e+07 6.917815e+07 1.145419e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.500000e-06 2.909300e-03 -0.0443361 -1.412500e-03 -4.300000e-06 1.396500e-03 5.589740e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.273700e-03 1.378300e-03 0.0010253 1.190000e-03 1.662300e-03 2.995700e-03 1.274070e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.580258e-01 3.006759e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.580277e-01 3.006511e-01 0.0000000 1.869206e-01 4.438558e-01 7.187215e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.446209e-01 2.606947e-01 0.0080940 3.475700e-02 1.352370e-01 3.876108e-01 9.919060e-01 ▇▂▂▁▁
numeric AF_reference 75025 0.9906608 NA NA NA NA NA NA NA 2.439191e-01 2.525364e-01 0.0000000 3.634190e-02 1.507590e-01 3.827880e-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 -0.0000409 0.0018888 0.9800000 0.9827124 0.623403 0.7821490 NA
1 54676 rs2462492 C T 0.0010660 0.0018673 0.5700002 0.5680794 0.400976 NA NA
1 86028 rs114608975 T C 0.0059936 0.0029969 0.0460002 0.0455039 0.103437 0.0277556 NA
1 91536 rs6702460 G T -0.0004701 0.0018398 0.8000000 0.7983049 0.457088 0.4207270 NA
1 234313 rs8179466 C T -0.0007453 0.0036335 0.8400000 0.8374851 0.074451 NA NA
1 534192 rs6680723 C T -0.0013028 0.0021029 0.5400003 0.5355683 0.241186 NA NA
1 546697 rs12025928 A G -0.0019686 0.0026236 0.4500005 0.4530481 0.913577 NA NA
1 693731 rs12238997 A G -0.0000430 0.0017597 0.9800000 0.9805039 0.116703 0.1417730 NA
1 705882 rs72631875 G A -0.0031803 0.0025838 0.2200002 0.2183732 0.067069 0.0315495 NA
1 706368 rs55727773 A G -0.0020509 0.0013049 0.1199999 0.1160313 0.515134 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0007626 0.0015794 0.6300007 0.6292317 0.137913 0.2052720 NA
22 51219387 rs9616832 T C -0.0004689 0.0020495 0.8200001 0.8190275 0.073612 0.0654952 NA
22 51219704 rs147475742 G A -0.0010173 0.0027465 0.7099994 0.7110827 0.041843 0.0473243 NA
22 51221190 rs369304721 G A 0.0000439 0.0027443 0.9900000 0.9872239 0.049574 NA NA
22 51221731 rs115055839 T C -0.0004426 0.0020503 0.8300000 0.8290988 0.073145 0.0625000 NA
22 51222100 rs114553188 G T -0.0013815 0.0024092 0.5700002 0.5663436 0.054643 0.0880591 NA
22 51223637 rs375798137 G A -0.0014606 0.0024206 0.5500004 0.5462482 0.054278 0.0788738 NA
22 51229805 rs9616985 T C -0.0004443 0.0020576 0.8300000 0.8290596 0.073012 0.0730831 NA
22 51232488 rs376461333 A G -0.0030235 0.0048414 0.5300002 0.5322910 0.020061 NA NA
22 51237063 rs3896457 T C 0.0029130 0.0012567 0.0200000 0.0204521 0.297860 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623403 ES:SE:LP:AF:ID  -4.09267e-05:0.00188877:0.00877392:0.623403:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400976 ES:SE:LP:AF:ID  0.00106602:0.00186732:0.244125:0.400976:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103437 ES:SE:LP:AF:ID  0.00599364:0.00299687:1.33724:0.103437:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457088 ES:SE:LP:AF:ID  -0.000470135:0.00183976:0.09691:0.457088:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074451 ES:SE:LP:AF:ID  -0.000745264:0.00363346:0.0757207:0.074451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241186 ES:SE:LP:AF:ID  -0.0013028:0.00210289:0.267606:0.241186:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913577 ES:SE:LP:AF:ID  -0.00196863:0.00262364:0.346787:0.913577:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116703 ES:SE:LP:AF:ID  -4.30016e-05:0.00175968:0.00877392:0.116703:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067069 ES:SE:LP:AF:ID  -0.00318031:0.0025838:0.657577:0.067069:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515134 ES:SE:LP:AF:ID  -0.00205088:0.00130492:0.920819:0.515134:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03287  ES:SE:LP:AF:ID  0.00209564:0.00329701:0.275724:0.03287:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03645  ES:SE:LP:AF:ID  0.000649006:0.00299685:0.0809219:0.03645:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036557 ES:SE:LP:AF:ID  0.000528514:0.00298616:0.0655015:0.036557:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036249 ES:SE:LP:AF:ID  0.000586084:0.00300818:0.0705811:0.036249:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016355 ES:SE:LP:AF:ID  0.00493587:0.00462387:0.537602:0.016355:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036782 ES:SE:LP:AF:ID  0.000846152:0.00297499:0.107905:0.036782:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036873 ES:SE:LP:AF:ID  0.00070666:0.00296507:0.091515:0.036873:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101076 ES:SE:LP:AF:ID  0.000561305:0.00215436:0.102373:0.101076:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959309 ES:SE:LP:AF:ID  -8.82274e-05:0.00285926:0.00877392:0.959309:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031432 ES:SE:LP:AF:ID  0.0053285:0.00515752:0.522879:0.031432:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053418 ES:SE:LP:AF:ID  0.00333169:0.00410462:0.376751:0.053418:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036416 ES:SE:LP:AF:ID  0.001145:0.00298242:0.154902:0.036416:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036745 ES:SE:LP:AF:ID  0.00116693:0.00295531:0.161151:0.036745:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843032 ES:SE:LP:AF:ID  0.000402452:0.00152715:0.102373:0.843032:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056041 ES:SE:LP:AF:ID  -0.00119491:0.00247076:0.200659:0.056041:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122705 ES:SE:LP:AF:ID  0.000439204:0.00166898:0.102373:0.122705:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025586 ES:SE:LP:AF:ID  -0.000465093:0.00412051:0.0409586:0.025586:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121928 ES:SE:LP:AF:ID  0.000356076:0.00166973:0.0809219:0.121928:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132582 ES:SE:LP:AF:ID  -0.00055056:0.0016469:0.130768:0.132582:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  -0.00531142:0.00599444:0.420216:0.011132:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036653 ES:SE:LP:AF:ID  0.00124332:0.00292584:0.173925:0.036653:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838725 ES:SE:LP:AF:ID  0.000130113:0.0014782:0.0315171:0.838725:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838352 ES:SE:LP:AF:ID  0.000255482:0.00147674:0.0655015:0.838352:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869399 ES:SE:LP:AF:ID  -0.000179974:0.00158307:0.0409586:0.869399:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130253 ES:SE:LP:AF:ID  -9.54746e-05:0.00158658:0.0222764:0.130253:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037121 ES:SE:LP:AF:ID  0.00143004:0.0028775:0.207608:0.037121:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037384 ES:SE:LP:AF:ID  0.00155468:0.0028583:0.229148:0.037384:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868732 ES:SE:LP:AF:ID  7.74388e-06:0.00158015:-0:0.868732:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868802 ES:SE:LP:AF:ID  2.64234e-06:0.0015807:-0:0.868802:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037334 ES:SE:LP:AF:ID  0.00140672:0.00287099:0.207608:0.037334:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868732 ES:SE:LP:AF:ID  3.12059e-05:0.0015801:0.00877392:0.868732:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8378   ES:SE:LP:AF:ID  0.000259692:0.00147258:0.0655015:0.8378:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037347 ES:SE:LP:AF:ID  0.00144332:0.00287529:0.207608:0.037347:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838436 ES:SE:LP:AF:ID  0.000269874:0.00147672:0.0705811:0.838436:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013889 ES:SE:LP:AF:ID  -0.00928074:0.00513315:1.14874:0.013889:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839574 ES:SE:LP:AF:ID  0.000192233:0.00149652:0.0457575:0.839574:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869019 ES:SE:LP:AF:ID  -0.000259849:0.00157805:0.0604807:0.869019:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868559 ES:SE:LP:AF:ID  -0.0002511:0.00157408:0.0604807:0.868559:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867537 ES:SE:LP:AF:ID  -0.000200247:0.0015715:0.0457575:0.867537:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868706 ES:SE:LP:AF:ID  -0.000291822:0.0015754:0.0705811:0.868706:rs4951929