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-12841/UKB-b-12841_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12841/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12841/UKB-b-12841_data.vcf.gz ...
Read summary statistics for 5902304 SNPs.
Dropped 2612 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, 1207709 SNPs remain.
After merging with regression SNP LD, 1207709 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0273 (0.0048)
Lambda GC: 1.0733
Mean Chi^2: 1.0768
Intercept: 1.013 (0.0075)
Ratio: 0.169 (0.0973)
Analysis finished at Thu Oct 17 14:43:16 2019
Total time elapsed: 1.0m:9.35s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9231,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 5.6898e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 159,
    "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": 53085,
    "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": 1207709,
    "ldsc_nsnp_merge_regression_ld": 1207709,
    "ldsc_observed_scale_h2_beta": 0.0273,
    "ldsc_observed_scale_h2_se": 0.0048,
    "ldsc_intercept_beta": 1.013,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.0733,
    "ldsc_mean_chisq": 1.0768,
    "ldsc_ratio": 0.1693
}

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 5899709 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 5902304 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 8.672099e+00 5.763133e+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 7.859464e+07 5.653249e+07 828.0000000 3.199692e+07 6.905093e+07 1.145285e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.700000e-06 1.854500e-03 -0.0173306 -1.114400e-03 7.100000e-06 1.117900e-03 1.376340e-02 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.709400e-03 5.533000e-04 0.0011359 1.252800e-03 1.495500e-03 2.034800e-03 5.860400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.884908e-01 2.923885e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.884917e-01 2.923626e-01 0.0000000 2.322088e-01 4.844452e-01 7.425824e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.154600e-01 2.523150e-01 0.0361690 1.011870e-01 2.349320e-01 4.810810e-01 9.638300e-01 ▇▃▂▂▁
numeric AF_reference 53085 0.9910061 NA NA NA NA NA NA NA 3.117209e-01 2.456743e-01 0.0000000 1.098240e-01 2.420130e-01 4.714460e-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 0.0009361 0.0020881 0.6499995 0.6539370 0.624290 0.7821490 NA
1 54676 rs2462492 C T -0.0018692 0.0020698 0.3700002 0.3664855 0.400055 NA NA
1 86028 rs114608975 T C 0.0070969 0.0033118 0.0320000 0.0321182 0.103422 0.0277556 NA
1 91536 rs6702460 G T -0.0021281 0.0020386 0.2999998 0.2965350 0.456878 0.4207270 NA
1 234313 rs8179466 C T 0.0019567 0.0040233 0.6300007 0.6267246 0.074494 NA NA
1 534192 rs6680723 C T 0.0037062 0.0023302 0.1100001 0.1117265 0.240639 NA NA
1 546697 rs12025928 A G 0.0007116 0.0028981 0.8100000 0.8060351 0.913377 NA NA
1 693731 rs12238997 A G 0.0011981 0.0019515 0.5400003 0.5392672 0.116942 0.1417730 NA
1 705882 rs72631875 G A 0.0026646 0.0028459 0.3500000 0.3491095 0.067453 0.0315495 NA
1 706368 rs55727773 A G -0.0009106 0.0014452 0.5300002 0.5286248 0.515771 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0008860 0.0022705 0.6999999 0.6963623 0.072944 0.0826677 NA
22 51219006 rs28729663 G A 0.0023106 0.0017514 0.1900002 0.1870629 0.136400 0.2052720 NA
22 51219387 rs9616832 T C 0.0006634 0.0022741 0.7700005 0.7704904 0.073116 0.0654952 NA
22 51219704 rs147475742 G A 0.0009546 0.0030586 0.7499995 0.7549580 0.041354 0.0473243 NA
22 51221190 rs369304721 G A -0.0000412 0.0030467 0.9900000 0.9892173 0.049198 NA NA
22 51221731 rs115055839 T C 0.0011049 0.0022767 0.6300007 0.6274627 0.072556 0.0625000 NA
22 51222100 rs114553188 G T 0.0052810 0.0026864 0.0490004 0.0493181 0.053686 0.0880591 NA
22 51223637 rs375798137 G A 0.0053827 0.0026998 0.0460002 0.0461784 0.053335 0.0788738 NA
22 51229805 rs9616985 T C 0.0010978 0.0022852 0.6300007 0.6309536 0.072363 0.0730831 NA
22 51237063 rs3896457 T C 0.0013365 0.0013880 0.3400001 0.3356244 0.297871 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62429  ES:SE:LP:AF:ID  0.000936081:0.00208807:0.187087:0.62429:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400055 ES:SE:LP:AF:ID  -0.00186916:0.00206977:0.431798:0.400055:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103422 ES:SE:LP:AF:ID  0.00709689:0.00331176:1.49485:0.103422:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456878 ES:SE:LP:AF:ID  -0.00212808:0.0020386:0.522879:0.456878:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074494 ES:SE:LP:AF:ID  0.00195671:0.00402332:0.200659:0.074494:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240639 ES:SE:LP:AF:ID  0.00370617:0.00233022:0.958607:0.240639:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913377 ES:SE:LP:AF:ID  0.000711619:0.00289813:0.091515:0.913377:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116942 ES:SE:LP:AF:ID  0.00119808:0.00195152:0.267606:0.116942:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067453 ES:SE:LP:AF:ID  0.00266463:0.00284586:0.455932:0.067453:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515771 ES:SE:LP:AF:ID  -0.000910605:0.00144516:0.275724:0.515771:rs12029736
1   715265  rs12184267  C   T   .   PASS    AF=0.036179 ES:SE:LP:AF:ID  0.00482472:0.00333347:0.823909:0.036179:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036289 ES:SE:LP:AF:ID  0.00485103:0.00332044:0.853872:0.036289:rs12184277
1   720381  rs116801199 G   T   .   PASS    AF=0.036544 ES:SE:LP:AF:ID  0.00501902:0.00330608:0.886057:0.036544:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03665  ES:SE:LP:AF:ID  0.00507526:0.00329389:0.920819:0.03665:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101881 ES:SE:LP:AF:ID  0.00095756:0.00237617:0.161151:0.101881:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959784 ES:SE:LP:AF:ID  -0.0057587:0.00318571:1.14874:0.959784:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053215 ES:SE:LP:AF:ID  -0.00804228:0.00455133:1.11351:0.053215:rs865924913
1   729632  rs116720794 C   T   .   PASS    AF=0.03643  ES:SE:LP:AF:ID  0.00550704:0.003287:1.02687:0.03643:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843316 ES:SE:LP:AF:ID  -0.00289273:0.00169557:1.05552:0.843316:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056231 ES:SE:LP:AF:ID  -0.000456048:0.00273036:0.0604807:0.056231:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122818 ES:SE:LP:AF:ID  0.00110405:0.00185221:0.259637:0.122818:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.122073 ES:SE:LP:AF:ID  0.00120907:0.00185343:0.29243:0.122073:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132198 ES:SE:LP:AF:ID  0.00290561:0.00182831:0.958607:0.132198:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.03633  ES:SE:LP:AF:ID  0.00517252:0.00325334:0.958607:0.03633:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838812 ES:SE:LP:AF:ID  -0.00266057:0.00164181:0.958607:0.838812:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838513 ES:SE:LP:AF:ID  -0.00277387:0.00164013:1.04096:0.838513:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869129 ES:SE:LP:AF:ID  -0.00125752:0.00175672:0.327902:0.869129:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130516 ES:SE:LP:AF:ID  0.00146923:0.00176028:0.39794:0.130516:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036859 ES:SE:LP:AF:ID  0.0051068:0.00319629:0.958607:0.036859:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037121 ES:SE:LP:AF:ID  0.00510314:0.00317424:0.958607:0.037121:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868532 ES:SE:LP:AF:ID  -0.00142566:0.0017534:0.376751:0.868532:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868621 ES:SE:LP:AF:ID  -0.00145398:0.00175412:0.387216:0.868621:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  0.00509502:0.00319041:0.958607:0.037058:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868535 ES:SE:LP:AF:ID  -0.00139036:0.00175341:0.366532:0.868535:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83787  ES:SE:LP:AF:ID  -0.00263957:0.00163524:0.958607:0.83787:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037085 ES:SE:LP:AF:ID  0.00506566:0.00319427:0.958607:0.037085:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838477 ES:SE:LP:AF:ID  -0.00264202:0.00163962:0.958607:0.838477:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839547 ES:SE:LP:AF:ID  -0.00228717:0.00166127:0.769551:0.839547:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868704 ES:SE:LP:AF:ID  -0.00112588:0.00175101:0.283997:0.868704:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868221 ES:SE:LP:AF:ID  -0.00107737:0.00174641:0.267606:0.868221:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867275 ES:SE:LP:AF:ID  -0.00127184:0.00174318:0.327902:0.867275:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868358 ES:SE:LP:AF:ID  -0.00111379:0.00174787:0.283997:0.868358:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868366 ES:SE:LP:AF:ID  -0.00111376:0.001748:0.283997:0.868366:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868368 ES:SE:LP:AF:ID  -0.00111607:0.001748:0.283997:0.868368:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868878 ES:SE:LP:AF:ID  -0.00119331:0.0017529:0.30103:0.868878:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037218 ES:SE:LP:AF:ID  0.00468016:0.00317123:0.853872:0.037218:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.838021 ES:SE:LP:AF:ID  -0.00250961:0.00163151:0.920819:0.838021:rs1048488
1   760998  rs148828841 C   A   .   PASS    AF=0.036597 ES:SE:LP:AF:ID  0.00453872:0.00323497:0.79588:0.036597:rs148828841
1   761147  rs3115850   T   C   .   PASS    AF=0.838129 ES:SE:LP:AF:ID  -0.00253238:0.00163254:0.920819:0.838129:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.861636 ES:SE:LP:AF:ID  -0.0016103:0.0017422:0.443698:0.861636:rs2286139