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-5361/UKB-b-5361_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5361/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5361/UKB-b-5361_data.vcf.gz ...
Read summary statistics for 6462515 SNPs.
Dropped 3468 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, 1241756 SNPs remain.
After merging with regression SNP LD, 1241756 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0036 (0.0011)
Lambda GC: 1.0445
Mean Chi^2: 1.0472
Intercept: 1.0142 (0.0065)
Ratio: 0.302 (0.1384)
Analysis finished at Thu Oct 17 14:46:24 2019
Total time elapsed: 1.0m:8.04s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9304,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -2.2171e-07,
    "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": 59275,
    "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": 1241756,
    "ldsc_nsnp_merge_regression_ld": 1241756,
    "ldsc_observed_scale_h2_beta": 0.0036,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0142,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0445,
    "ldsc_mean_chisq": 1.0472,
    "ldsc_ratio": 0.3008
}

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 6459068 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 6462515 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 8.667479e+00 5.763750e+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 7.856912e+07 5.648270e+07 828.0000000 3.203377e+07 6.899992e+07 1.144740e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.000000e-07 6.240000e-04 -0.0053904 -3.559000e-04 -2.100000e-06 3.539000e-04 5.955600e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.703000e-04 2.248000e-04 0.0003473 3.875000e-04 4.794000e-04 6.983000e-04 3.010100e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.931186e-01 2.904949e-01 0.0000002 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 4.931175e-01 2.904684e-01 0.0000002 2.400082e-01 4.907409e-01 7.444536e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.944798e-01 2.571604e-01 0.0244380 7.802000e-02 2.056530e-01 4.563960e-01 9.755620e-01 ▇▃▂▂▁
numeric AF_reference 59275 0.9908279 NA NA NA NA NA NA NA 2.919362e-01 2.496012e-01 0.0000000 8.726040e-02 2.152560e-01 4.482830e-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 0.0007381 0.0006391 0.2500000 0.2481523 0.623765 0.7821490 NA
1 54676 rs2462492 C T 0.0004702 0.0006331 0.4600002 0.4576533 0.400401 NA NA
1 86028 rs114608975 T C -0.0012952 0.0010123 0.2000000 0.2007069 0.103556 0.0277556 NA
1 91536 rs6702460 G T 0.0005718 0.0006234 0.3599996 0.3590008 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0003257 0.0012292 0.7899998 0.7910468 0.074506 NA NA
1 534192 rs6680723 C T -0.0006169 0.0007121 0.3900004 0.3863476 0.240959 NA NA
1 546697 rs12025928 A G -0.0014119 0.0008884 0.1100001 0.1119823 0.913475 NA NA
1 693731 rs12238997 A G 0.0001444 0.0005968 0.8100000 0.8087784 0.116329 0.1417730 NA
1 705882 rs72631875 G A 0.0003200 0.0008745 0.7099994 0.7144132 0.067288 0.0315495 NA
1 706368 rs55727773 A G 0.0009235 0.0004421 0.0369999 0.0366969 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0004710 0.0006908 0.5000000 0.4953638 0.073622 0.0826677 NA
22 51219006 rs28729663 G A 0.0001486 0.0005333 0.7800007 0.7805110 0.137950 0.2052720 NA
22 51219387 rs9616832 T C 0.0005371 0.0006922 0.4400003 0.4377501 0.073744 0.0654952 NA
22 51219704 rs147475742 G A 0.0005777 0.0009276 0.5300002 0.5334409 0.041954 0.0473243 NA
22 51221190 rs369304721 G A 0.0007374 0.0009260 0.4299995 0.4258965 0.049731 NA NA
22 51221731 rs115055839 T C 0.0004538 0.0006926 0.5099998 0.5123639 0.073235 0.0625000 NA
22 51222100 rs114553188 G T 0.0000528 0.0008154 0.9500000 0.9483343 0.054460 0.0880591 NA
22 51223637 rs375798137 G A 0.0000960 0.0008194 0.9100000 0.9067304 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 0.0004766 0.0006951 0.4899999 0.4929738 0.073071 0.0730831 NA
22 51237063 rs3896457 T C -0.0001469 0.0004252 0.7300002 0.7296661 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  0.000738057:0.000639094:0.60206:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000470248:0.000633146:0.337242:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  -0.00129524:0.00101227:0.69897:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  0.000571833:0.000623407:0.443698:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074506 ES:SE:LP:AF:ID  0.000325681:0.00122921:0.102373:0.074506:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  -0.000616862:0.000712098:0.408935:0.240959:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  -0.00141194:0.000888378:0.958607:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116329 ES:SE:LP:AF:ID  0.000144417:0.000596759:0.091515:0.116329:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  0.000320004:0.000874482:0.148742:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  0.000923506:0.000442055:1.4318:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033009 ES:SE:LP:AF:ID  -0.00134785:0.00111438:0.638272:0.033009:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036624 ES:SE:LP:AF:ID  -0.00143048:0.00101225:0.79588:0.036624:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036741 ES:SE:LP:AF:ID  -0.00135099:0.00100842:0.744727:0.036741:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036439 ES:SE:LP:AF:ID  -0.00141424:0.00101569:0.79588:0.036439:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.03698  ES:SE:LP:AF:ID  -0.00142868:0.00100442:0.823909:0.03698:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037077 ES:SE:LP:AF:ID  -0.00153248:0.00100098:0.886057:0.037077:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.1012   ES:SE:LP:AF:ID  -0.00166138:0.000729365:1.63827:0.1012:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959091 ES:SE:LP:AF:ID  0.0016945:0.000965421:1.10237:0.959091:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03145  ES:SE:LP:AF:ID  0.00217311:0.00175272:0.657577:0.03145:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  -0.00171876:0.00139425:0.657577:0.053255:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  -0.00141444:0.00100747:0.79588:0.036594:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03691  ES:SE:LP:AF:ID  -0.00136024:0.000998301:0.769551:0.03691:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  0.000305723:0.000517169:0.259637:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055912 ES:SE:LP:AF:ID  0.000194668:0.00083738:0.0861861:0.055912:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  1.82371e-05:0.000566085:0.0132283:0.122312:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025711 ES:SE:LP:AF:ID  0.00123545:0.00139252:0.431798:0.025711:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  4.77204e-07:0.000566323:-0:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  -0.000336112:0.000558168:0.259637:0.132335:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  -0.00139502:0.000988202:0.79588:0.036825:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  0.000138639:0.000500843:0.107905:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838573 ES:SE:LP:AF:ID  9.58535e-05:0.000500304:0.0705811:0.838573:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  -0.00016403:0.000536844:0.119186:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  0.000271452:0.000537943:0.21467:0.129876:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  -0.00141956:0.000971446:0.853872:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03758  ES:SE:LP:AF:ID  -0.00134385:0.000965308:0.79588:0.03758:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000180025:0.000535792:0.130768:0.869117:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.000157006:0.000536005:0.113509:0.869215:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  -0.00133755:0.000969484:0.769551:0.037538:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  -0.000182588:0.000535782:0.136677:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  0.000133255:0.000498916:0.102373:0.838026:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -0.00133411:0.000970853:0.769551:0.03755:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838657 ES:SE:LP:AF:ID  0.000112683:0.000500318:0.0861861:0.838657:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83977  ES:SE:LP:AF:ID  0.000149702:0.000507084:0.113509:0.83977:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  -0.000185371:0.000535162:0.136677:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868947 ES:SE:LP:AF:ID  -0.000222905:0.000533816:0.167491:0.868947:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867898 ES:SE:LP:AF:ID  -0.00028093:0.000532792:0.221849:0.867898:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86909  ES:SE:LP:AF:ID  -0.000210581:0.000534253:0.161151:0.86909:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869098 ES:SE:LP:AF:ID  -0.000209605:0.000534294:0.161151:0.869098:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  -0.000203538:0.000534306:0.154902:0.869106:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869584 ES:SE:LP:AF:ID  -0.00018007:0.000535773:0.130768:0.869584:rs3131954