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-14395/UKB-b-14395_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14395/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14395/UKB-b-14395_data.vcf.gz ...
Read summary statistics for 8296230 SNPs.
Dropped 6697 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, 1284372 SNPs remain.
After merging with regression SNP LD, 1284372 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1028 (0.0049)
Lambda GC: 1.3373
Mean Chi^2: 1.4708
Intercept: 1.0408 (0.0107)
Ratio: 0.0866 (0.0227)
Analysis finished at Thu Oct 17 14:44:39 2019
Total time elapsed: 1.0m:14.43s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9446,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -6.2975e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 76,
    "n_p_sig": 4535,
    "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": 78021,
    "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": 1284372,
    "ldsc_nsnp_merge_regression_ld": 1284372,
    "ldsc_observed_scale_h2_beta": 0.1028,
    "ldsc_observed_scale_h2_se": 0.0049,
    "ldsc_intercept_beta": 1.0408,
    "ldsc_intercept_se": 0.0107,
    "ldsc_lambda_gc": 1.3373,
    "ldsc_mean_chisq": 1.4708,
    "ldsc_ratio": 0.0867
}

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 8289563 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 8296230 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 8.655224e+00 5.762352e+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 7.873728e+07 5.638700e+07 828.0000000 3.232778e+07 6.922757e+07 1.145508e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.000000e-07 3.810600e-03 -0.0400819 -1.789800e-03 -2.500000e-06 1.781700e-03 4.138950e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.997200e-03 1.920600e-03 0.0012787 1.493200e-03 2.135200e-03 3.993800e-03 2.007990e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.617199e-01 2.992092e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.617210e-01 2.991838e-01 0.0000000 1.930178e-01 4.485557e-01 7.204203e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.374970e-01 2.602588e-01 0.0067340 3.019300e-02 1.255330e-01 3.761318e-01 9.932660e-01 ▇▂▂▁▁
numeric AF_reference 78021 0.9905956 NA NA NA NA NA NA NA 2.369845e-01 2.521466e-01 0.0000000 2.995210e-02 1.413740e-01 3.724040e-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 0.0002489 0.0023500 0.9199999 0.9156366 0.624267 0.7821490 NA
1 54676 rs2462492 C T 0.0021331 0.0023335 0.3599996 0.3606543 0.399695 NA NA
1 86028 rs114608975 T C -0.0016320 0.0037144 0.6600001 0.6603849 0.103686 0.0277556 NA
1 91536 rs6702460 G T 0.0022015 0.0022958 0.3400001 0.3376096 0.456603 0.4207270 NA
1 234313 rs8179466 C T 0.0057546 0.0045147 0.2000000 0.2024301 0.074622 NA NA
1 534192 rs6680723 C T 0.0032476 0.0026210 0.2200002 0.2153298 0.240711 NA NA
1 546697 rs12025928 A G -0.0026322 0.0032702 0.4199997 0.4208629 0.913394 NA NA
1 693731 rs12238997 A G -0.0002608 0.0021990 0.9100000 0.9055768 0.115933 0.1417730 NA
1 705882 rs72631875 G A 0.0024277 0.0032161 0.4500005 0.4503396 0.067538 0.0315495 NA
1 706368 rs55727773 A G -0.0009547 0.0016276 0.5600000 0.5575140 0.516309 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0002507 0.0019624 0.9000000 0.8983468 0.137965 0.2052720 NA
22 51219387 rs9616832 T C 0.0001913 0.0025493 0.9400001 0.9401871 0.073841 0.0654952 NA
22 51219704 rs147475742 G A 0.0009196 0.0034157 0.7899998 0.7877639 0.042049 0.0473243 NA
22 51221190 rs369304721 G A 0.0006427 0.0034076 0.8499999 0.8503890 0.049860 NA NA
22 51221731 rs115055839 T C -0.0000060 0.0025516 1.0000000 0.9981116 0.073283 0.0625000 NA
22 51222100 rs114553188 G T -0.0014483 0.0030074 0.6300007 0.6301135 0.054302 0.0880591 NA
22 51223637 rs375798137 G A -0.0013986 0.0030222 0.6400000 0.6435304 0.053924 0.0788738 NA
22 51229805 rs9616985 T C 0.0000557 0.0025610 0.9800000 0.9826527 0.073082 0.0730831 NA
22 51232488 rs376461333 A G -0.0056638 0.0060320 0.3500000 0.3477536 0.020066 NA NA
22 51237063 rs3896457 T C 0.0006653 0.0015683 0.6700003 0.6714035 0.298014 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624267 ES:SE:LP:AF:ID  0.000248934:0.00234995:0.0362122:0.624267:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399695 ES:SE:LP:AF:ID  0.00213306:0.00233346:0.443698:0.399695:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103686 ES:SE:LP:AF:ID  -0.00163204:0.0037144:0.180456:0.103686:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456603 ES:SE:LP:AF:ID  0.00220145:0.00229581:0.468521:0.456603:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074622 ES:SE:LP:AF:ID  0.00575465:0.00451466:0.69897:0.074622:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240711 ES:SE:LP:AF:ID  0.00324758:0.00262104:0.657577:0.240711:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913394 ES:SE:LP:AF:ID  -0.00263225:0.00327018:0.376751:0.913394:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115933 ES:SE:LP:AF:ID  -0.000260848:0.00219903:0.0409586:0.115933:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067538 ES:SE:LP:AF:ID  0.00242767:0.0032161:0.346787:0.067538:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516309 ES:SE:LP:AF:ID  -0.000954661:0.00162762:0.251812:0.516309:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033135 ES:SE:LP:AF:ID  -0.00465787:0.00409488:0.585027:0.033135:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.0368   ES:SE:LP:AF:ID  -0.00433775:0.00371568:0.619789:0.0368:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036924 ES:SE:LP:AF:ID  -0.00440297:0.00370093:0.638272:0.036924:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036638 ES:SE:LP:AF:ID  -0.00438056:0.00372651:0.619789:0.036638:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016464 ES:SE:LP:AF:ID  0.00337295:0.00574932:0.251812:0.016464:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037184 ES:SE:LP:AF:ID  -0.00441084:0.00368507:0.638272:0.037184:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037284 ES:SE:LP:AF:ID  -0.00449177:0.00367221:0.657577:0.037284:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101305 ES:SE:LP:AF:ID  0.00061408:0.00268377:0.0861861:0.101305:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958869 ES:SE:LP:AF:ID  0.00455168:0.00354262:0.69897:0.958869:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031492 ES:SE:LP:AF:ID  0.00103163:0.00647063:0.0604807:0.031492:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053094 ES:SE:LP:AF:ID  0.00244472:0.00514474:0.200659:0.053094:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036774 ES:SE:LP:AF:ID  -0.00451455:0.00369857:0.657577:0.036774:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037076 ES:SE:LP:AF:ID  -0.0047434:0.0036647:0.69897:0.037076:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843414 ES:SE:LP:AF:ID  0.00146504:0.00190307:0.356547:0.843414:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055776 ES:SE:LP:AF:ID  -0.000137334:0.00308396:0.0177288:0.055776:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121895 ES:SE:LP:AF:ID  -0.000219476:0.00208643:0.0362122:0.121895:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025878 ES:SE:LP:AF:ID  0.00777086:0.00510877:0.886057:0.025878:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12116  ES:SE:LP:AF:ID  -0.000386924:0.00208727:0.0705811:0.12116:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132047 ES:SE:LP:AF:ID  -0.00151313:0.00205592:0.337242:0.132047:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011131 ES:SE:LP:AF:ID  0.0127202:0.00746939:1.05061:0.011131:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036993 ES:SE:LP:AF:ID  -0.00430641:0.00362743:0.619789:0.036993:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839209 ES:SE:LP:AF:ID  0.00153139:0.00184421:0.387216:0.839209:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838837 ES:SE:LP:AF:ID  0.00135403:0.001842:0.337242:0.838837:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.870174 ES:SE:LP:AF:ID  0.000869414:0.00197866:0.180456:0.870174:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129469 ES:SE:LP:AF:ID  -0.000569688:0.00198226:0.113509:0.129469:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  -0.00482734:0.00356396:0.744727:0.037556:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037778 ES:SE:LP:AF:ID  -0.00456453:0.00354284:0.69897:0.037778:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869527 ES:SE:LP:AF:ID  0.000686783:0.00197448:0.136677:0.869527:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869655 ES:SE:LP:AF:ID  0.000655876:0.00197537:0.130768:0.869655:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037747 ES:SE:LP:AF:ID  -0.00480241:0.0035577:0.744727:0.037747:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869532 ES:SE:LP:AF:ID  0.000678261:0.00197447:0.136677:0.869532:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838292 ES:SE:LP:AF:ID  0.00140173:0.00183693:0.346787:0.838292:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037758 ES:SE:LP:AF:ID  -0.00464198:0.00356248:0.721246:0.037758:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838917 ES:SE:LP:AF:ID  0.00143337:0.00184209:0.356547:0.838917:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013685 ES:SE:LP:AF:ID  0.000103721:0.00644942:0.00436481:0.013685:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839989 ES:SE:LP:AF:ID  0.00167226:0.00186728:0.431798:0.839989:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869803 ES:SE:LP:AF:ID  0.000812836:0.00197252:0.167491:0.869803:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869356 ES:SE:LP:AF:ID  0.000778726:0.00196753:0.161151:0.869356:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868288 ES:SE:LP:AF:ID  0.000491282:0.00196313:0.09691:0.868288:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869497 ES:SE:LP:AF:ID  0.000763891:0.00196911:0.154902:0.869497:rs4951929