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-15251/UKB-b-15251_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15251/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15251/UKB-b-15251_data.vcf.gz ...
Read summary statistics for 7312492 SNPs.
Dropped 4815 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, 1271983 SNPs remain.
After merging with regression SNP LD, 1271983 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0374 (0.0108)
Lambda GC: 1.0434
Mean Chi^2: 1.035
Intercept: 1.0024 (0.0067)
Ratio: 0.0686 (0.1914)
Analysis finished at Thu Oct 17 14:45:31 2019
Total time elapsed: 1.0m:25.06s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9383,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -2.2984e-06,
    "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": 67586,
    "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": 1271983,
    "ldsc_nsnp_merge_regression_ld": 1271983,
    "ldsc_observed_scale_h2_beta": 0.0374,
    "ldsc_observed_scale_h2_se": 0.0108,
    "ldsc_intercept_beta": 1.0024,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0434,
    "ldsc_mean_chisq": 1.035,
    "ldsc_ratio": 0.0686
}

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 7307699 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 7312492 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 8.663998e+00 5.763931e+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 7.863930e+07 5.644982e+07 828.0000000 3.216959e+07 6.905726e+07 1.145225e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.300000e-06 6.688700e-03 -0.0719021 -3.461300e-03 -2.100000e-05 3.432700e-03 7.753720e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.904200e-03 3.004500e-03 0.0030776 3.510000e-03 4.623700e-03 7.527800e-03 3.219910e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.938435e-01 2.898586e-01 0.0000005 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.938416e-01 2.898319e-01 0.0000005 2.417462e-01 4.910717e-01 7.449498e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.658146e-01 2.605457e-01 0.0133970 5.096300e-02 1.652640e-01 4.185040e-01 9.866030e-01 ▇▂▂▁▁
numeric AF_reference 67586 0.9907575 NA NA NA NA NA NA NA 2.644516e-01 2.524229e-01 0.0000000 5.710860e-02 1.783150e-01 4.121410e-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 0.0011742 0.0056831 0.8400000 0.8363188 0.624486 0.7821490 NA
1 54676 rs2462492 C T -0.0014572 0.0056245 0.8000000 0.7955728 0.400211 NA NA
1 86028 rs114608975 T C -0.0156841 0.0090148 0.0819993 0.0818902 0.103396 0.0277556 NA
1 91536 rs6702460 G T 0.0018966 0.0055241 0.7300002 0.7313419 0.457244 0.4207270 NA
1 234313 rs8179466 C T 0.0027076 0.0108561 0.8000000 0.8030444 0.074689 NA NA
1 534192 rs6680723 C T 0.0023522 0.0063038 0.7099994 0.7090441 0.241777 NA NA
1 546697 rs12025928 A G 0.0070337 0.0079346 0.3800004 0.3753690 0.913507 NA NA
1 693731 rs12238997 A G 0.0024221 0.0053067 0.6499995 0.6480874 0.116186 0.1417730 NA
1 705882 rs72631875 G A 0.0091318 0.0078447 0.2399999 0.2443962 0.066874 0.0315495 NA
1 706368 rs55727773 A G -0.0015212 0.0039244 0.6999999 0.6982905 0.515455 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0065881 0.0047337 0.1600000 0.1639968 0.139339 0.2052720 NA
22 51219387 rs9616832 T C -0.0056762 0.0061127 0.3500000 0.3530983 0.074585 0.0654952 NA
22 51219704 rs147475742 G A 0.0000406 0.0082132 1.0000000 0.9960599 0.042158 0.0473243 NA
22 51221190 rs369304721 G A -0.0047012 0.0081840 0.5700002 0.5656735 0.050188 NA NA
22 51221731 rs115055839 T C -0.0058700 0.0061226 0.3400001 0.3376818 0.074017 0.0625000 NA
22 51222100 rs114553188 G T -0.0081792 0.0072346 0.2599998 0.2582387 0.054757 0.0880591 NA
22 51223637 rs375798137 G A -0.0082731 0.0072680 0.2599998 0.2550006 0.054395 0.0788738 NA
22 51229805 rs9616985 T C -0.0055538 0.0061446 0.3700002 0.3660752 0.073852 0.0730831 NA
22 51232488 rs376461333 A G -0.0218767 0.0146740 0.1400000 0.1360015 0.019782 NA NA
22 51237063 rs3896457 T C 0.0020811 0.0037747 0.5800000 0.5814159 0.300646 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624486 ES:SE:LP:AF:ID  0.00117416:0.00568313:0.0757207:0.624486:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400211 ES:SE:LP:AF:ID  -0.00145719:0.00562446:0.09691:0.400211:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103396 ES:SE:LP:AF:ID  -0.0156841:0.00901477:1.08619:0.103396:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457244 ES:SE:LP:AF:ID  0.00189665:0.0055241:0.136677:0.457244:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074689 ES:SE:LP:AF:ID  0.00270761:0.0108561:0.09691:0.074689:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241777 ES:SE:LP:AF:ID  0.00235222:0.00630385:0.148742:0.241777:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913507 ES:SE:LP:AF:ID  0.00703368:0.00793456:0.420216:0.913507:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116186 ES:SE:LP:AF:ID  0.00242207:0.00530666:0.187087:0.116186:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066874 ES:SE:LP:AF:ID  0.00913177:0.0078447:0.619789:0.066874:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515455 ES:SE:LP:AF:ID  -0.0015212:0.00392437:0.154902:0.515455:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033238 ES:SE:LP:AF:ID  0.00689173:0.00986002:0.318759:0.033238:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036648 ES:SE:LP:AF:ID  0.00588847:0.00898627:0.29243:0.036648:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  0.00646628:0.00895472:0.327902:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036468 ES:SE:LP:AF:ID  0.00689641:0.00901739:0.356547:0.036468:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016629 ES:SE:LP:AF:ID  -0.0079256:0.0137963:0.244125:0.016629:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037067 ES:SE:LP:AF:ID  0.00649315:0.00890625:0.327902:0.037067:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037165 ES:SE:LP:AF:ID  0.0072898:0.00887675:0.387216:0.037165:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101684 ES:SE:LP:AF:ID  -0.00205405:0.00645879:0.124939:0.101684:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959252 ES:SE:LP:AF:ID  -0.000932306:0.00859541:0.0409586:0.959252:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03138  ES:SE:LP:AF:ID  0.0018969:0.0156673:0.0457575:0.03138:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053315 ES:SE:LP:AF:ID  0.00207349:0.0123263:0.0604807:0.053315:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036642 ES:SE:LP:AF:ID  0.00424287:0.00893853:0.19382:0.036642:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036937 ES:SE:LP:AF:ID  0.0060979:0.00886114:0.309804:0.036937:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843727 ES:SE:LP:AF:ID  -0.00111415:0.00460736:0.091515:0.843727:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05488  ES:SE:LP:AF:ID  0.00171539:0.00752286:0.0861861:0.05488:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121988 ES:SE:LP:AF:ID  0.00285591:0.00503343:0.244125:0.121988:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025707 ES:SE:LP:AF:ID  0.00953039:0.0123012:0.356547:0.025707:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12121  ES:SE:LP:AF:ID  0.0025495:0.00503456:0.21467:0.12121:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.131909 ES:SE:LP:AF:ID  0.0030889:0.00497001:0.275724:0.131909:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036847 ES:SE:LP:AF:ID  0.00662006:0.00877531:0.346787:0.036847:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839891 ES:SE:LP:AF:ID  -0.000783408:0.00446629:0.0655015:0.839891:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.839516 ES:SE:LP:AF:ID  -0.000455634:0.004462:0.0362122:0.839516:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.870553 ES:SE:LP:AF:ID  -0.00130377:0.00478546:0.102373:0.870553:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129161 ES:SE:LP:AF:ID  0.00158515:0.00479164:0.130768:0.129161:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037326 ES:SE:LP:AF:ID  0.0055109:0.00863069:0.283997:0.037326:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037589 ES:SE:LP:AF:ID  0.00493029:0.00857345:0.244125:0.037589:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869945 ES:SE:LP:AF:ID  -0.000809685:0.00477687:0.0604807:0.869945:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870044 ES:SE:LP:AF:ID  -0.000678246:0.00477867:0.05061:0.870044:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.00477492:0.00861106:0.236572:0.03753:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869923 ES:SE:LP:AF:ID  -0.00080018:0.00477634:0.0604807:0.869923:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.839037 ES:SE:LP:AF:ID  -0.00031183:0.0044517:0.0268721:0.839037:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.00534315:0.00862624:0.267606:0.03753:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839704 ES:SE:LP:AF:ID  -0.000590555:0.00446481:0.05061:0.839704:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.840848 ES:SE:LP:AF:ID  -0.00128212:0.00452779:0.107905:0.840848:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.870254 ES:SE:LP:AF:ID  -0.00127972:0.00477007:0.102373:0.870254:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869756 ES:SE:LP:AF:ID  -0.00108468:0.00475866:0.0861861:0.869756:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868835 ES:SE:LP:AF:ID  -0.00114306:0.00475074:0.091515:0.868835:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869959 ES:SE:LP:AF:ID  -0.00119917:0.00476285:0.09691:0.869959:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869959 ES:SE:LP:AF:ID  -0.00123932:0.00476318:0.102373:0.869959:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86997  ES:SE:LP:AF:ID  -0.0011994:0.00476327:0.09691:0.86997:rs3131956