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-16855/UKB-b-16855_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16855/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16855/UKB-b-16855_data.vcf.gz ...
Read summary statistics for 7778822 SNPs.
Dropped 5701 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, 1280099 SNPs remain.
After merging with regression SNP LD, 1280099 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0084 (0.0013)
Lambda GC: 1.0692
Mean Chi^2: 1.0905
Intercept: 1.0145 (0.0068)
Ratio: 0.1606 (0.0753)
Analysis finished at Thu Oct 17 14:46:40 2019
Total time elapsed: 1.0m:21.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9416,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -4.889e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 12,
    "n_p_sig": 226,
    "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": 72483,
    "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": 1280099,
    "ldsc_nsnp_merge_regression_ld": 1280099,
    "ldsc_observed_scale_h2_beta": 0.0084,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0145,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0692,
    "ldsc_mean_chisq": 1.0905,
    "ldsc_ratio": 0.1602
}

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 1.000000 3 58 0 7773147 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 7778822 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.661935e+00 5.764234e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.869323e+07 5.643151e+07 828.0000000 3.222119e+07 6.915560e+07 1.145660e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -4.900000e-06 1.325000e-03 -0.0126264 -6.438000e-04 -2.300000e-06 6.356000e-04 1.546570e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.133000e-03 6.485000e-04 0.0005393 6.210000e-04 8.489000e-04 1.477300e-03 6.477200e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.911621e-01 2.916757e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.911629e-01 2.916496e-01 0.0000000 2.364317e-01 4.884266e-01 7.437348e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.517585e-01 2.608264e-01 0.0096780 3.981000e-02 1.454580e-01 3.982690e-01 9.903220e-01 ▇▂▂▁▁
numeric AF_reference 72483 0.990682 NA NA NA NA NA NA NA 2.508539e-01 2.526712e-01 0.0000000 4.313100e-02 1.601440e-01 3.929710e-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 -0.0000632 0.0009925 0.9500000 0.9492445 0.623781 0.7821490 NA
1 54676 rs2462492 C T 0.0012771 0.0009832 0.1900002 0.1939899 0.400411 NA NA
1 86028 rs114608975 T C 0.0009583 0.0015723 0.5400003 0.5422226 0.103544 0.0277556 NA
1 91536 rs6702460 G T 0.0003850 0.0009682 0.6899999 0.6908607 0.456868 0.4207270 NA
1 234313 rs8179466 C T 0.0019173 0.0019090 0.3200000 0.3152186 0.074509 NA NA
1 534192 rs6680723 C T -0.0013547 0.0011059 0.2200002 0.2206005 0.240954 NA NA
1 546697 rs12025928 A G -0.0009929 0.0013797 0.4700002 0.4717623 0.913476 NA NA
1 693731 rs12238997 A G 0.0008563 0.0009268 0.3599996 0.3554902 0.116321 0.1417730 NA
1 705882 rs72631875 G A 0.0000522 0.0013580 0.9699999 0.9693438 0.067293 0.0315495 NA
1 706368 rs55727773 A G -0.0003887 0.0006865 0.5700002 0.5712106 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0012261 0.0008281 0.1400000 0.1387098 0.137981 0.2052720 NA
22 51219387 rs9616832 T C -0.0005294 0.0010749 0.6200004 0.6223380 0.073764 0.0654952 NA
22 51219704 rs147475742 G A -0.0009499 0.0014402 0.5099998 0.5095349 0.041976 0.0473243 NA
22 51221190 rs369304721 G A -0.0007293 0.0014380 0.6100002 0.6120540 0.049742 NA NA
22 51221731 rs115055839 T C -0.0004431 0.0010755 0.6800001 0.6803274 0.073256 0.0625000 NA
22 51222100 rs114553188 G T -0.0011159 0.0012662 0.3800004 0.3781666 0.054469 0.0880591 NA
22 51223637 rs375798137 G A -0.0011321 0.0012724 0.3700002 0.3736082 0.054098 0.0788738 NA
22 51229805 rs9616985 T C -0.0003894 0.0010794 0.7199992 0.7183198 0.073090 0.0730831 NA
22 51232488 rs376461333 A G -0.0035442 0.0025441 0.1600000 0.1635786 0.020038 NA NA
22 51237063 rs3896457 T C -0.0000842 0.0006603 0.9000000 0.8985608 0.297979 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623781 ES:SE:LP:AF:ID  -6.31813e-05:0.000992549:0.0222764:0.623781:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400411 ES:SE:LP:AF:ID  0.00127711:0.00098325:0.721246:0.400411:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103544 ES:SE:LP:AF:ID  0.000958253:0.00157231:0.267606:0.103544:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456868 ES:SE:LP:AF:ID  0.00038504:0.000968198:0.161151:0.456868:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  0.00191729:0.00190902:0.49485:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240954 ES:SE:LP:AF:ID  -0.00135469:0.00110593:0.657577:0.240954:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.000992874:0.00137973:0.327902:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116321 ES:SE:LP:AF:ID  0.000856348:0.000926791:0.443698:0.116321:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067293 ES:SE:LP:AF:ID  5.21909e-05:0.00135803:0.0132283:0.067293:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000388748:0.000686507:0.244125:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033009 ES:SE:LP:AF:ID  -0.00282562:0.00173071:1:0.033009:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036628 ES:SE:LP:AF:ID  -0.00231801:0.00157201:0.853872:0.036628:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036743 ES:SE:LP:AF:ID  -0.00222906:0.0015661:0.823909:0.036743:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036443 ES:SE:LP:AF:ID  -0.00227463:0.00157737:0.823909:0.036443:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016405 ES:SE:LP:AF:ID  -0.000612684:0.00242905:0.09691:0.016405:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036983 ES:SE:LP:AF:ID  -0.00237013:0.00155987:0.886057:0.036983:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03708  ES:SE:LP:AF:ID  -0.00234873:0.00155451:0.886057:0.03708:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101226 ES:SE:LP:AF:ID  -0.00108458:0.00113247:0.468521:0.101226:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959091 ES:SE:LP:AF:ID  0.00190091:0.00149939:0.69897:0.959091:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031447 ES:SE:LP:AF:ID  -0.00180284:0.00272246:0.29243:0.031447:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053252 ES:SE:LP:AF:ID  0.00110117:0.00216518:0.21467:0.053252:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036596 ES:SE:LP:AF:ID  -0.00226913:0.00156461:0.823909:0.036596:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036914 ES:SE:LP:AF:ID  -0.00203761:0.00155033:0.721246:0.036914:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843223 ES:SE:LP:AF:ID  -1.68275e-05:0.000803197:0.00877392:0.843223:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055895 ES:SE:LP:AF:ID  -0.00016412:0.00130063:0.0457575:0.055895:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122296 ES:SE:LP:AF:ID  0.000727345:0.000879162:0.387216:0.122296:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025709 ES:SE:LP:AF:ID  -0.00212161:0.00216268:0.481486:0.025709:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121538 ES:SE:LP:AF:ID  0.000713052:0.000879536:0.376751:0.121538:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132326 ES:SE:LP:AF:ID  0.0001165:0.000866841:0.05061:0.132326:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  0.00393259:0.00315118:0.677781:0.011135:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036829 ES:SE:LP:AF:ID  -0.00223155:0.00153465:0.823909:0.036829:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838955 ES:SE:LP:AF:ID  -2.73945e-05:0.000777819:0.0132283:0.838955:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838585 ES:SE:LP:AF:ID  -3.26568e-05:0.000776993:0.0132283:0.838585:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869786 ES:SE:LP:AF:ID  -0.000664665:0.000833748:0.366532:0.869786:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129862 ES:SE:LP:AF:ID  0.000719693:0.000835456:0.408935:0.129862:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037342 ES:SE:LP:AF:ID  -0.00231375:0.00150858:0.886057:0.037342:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037585 ES:SE:LP:AF:ID  -0.00233267:0.00149907:0.920819:0.037585:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869131 ES:SE:LP:AF:ID  -0.000711456:0.000832119:0.408935:0.869131:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86923  ES:SE:LP:AF:ID  -0.00070653:0.000832451:0.39794:0.86923:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037544 ES:SE:LP:AF:ID  -0.00237425:0.00150555:0.958607:0.037544:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869134 ES:SE:LP:AF:ID  -0.000705524:0.000832102:0.39794:0.869134:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838038 ES:SE:LP:AF:ID  -4.69925e-06:0.000774834:-0:0.838038:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037555 ES:SE:LP:AF:ID  -0.00233896:0.0015077:0.920819:0.037555:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838669 ES:SE:LP:AF:ID  -2.62878e-05:0.000777012:0.0132283:0.838669:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013779 ES:SE:LP:AF:ID  -0.00358893:0.00271174:0.721246:0.013779:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839781 ES:SE:LP:AF:ID  -5.75513e-05:0.000787531:0.0268721:0.839781:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869411 ES:SE:LP:AF:ID  -0.000657248:0.000831132:0.366532:0.869411:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868957 ES:SE:LP:AF:ID  -0.000616168:0.000829043:0.337242:0.868957:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867914 ES:SE:LP:AF:ID  -0.00074261:0.000827459:0.431798:0.867914:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000674522:0.000829718:0.376751:0.869101:rs4951929