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/dev/ukb-d-import/processed/ukb-d-20493/ukb-d-20493.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20493/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 17:15:37 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20493/ukb-d-20493.vcf.gz ...
Read summary statistics for 12871266 SNPs.
Dropped 11667 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283348 SNPs remain.
After merging with regression SNP LD, 1283348 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0596 (0.0157)
Lambda GC: 1.0155
Mean Chi^2: 1.0226
Intercept: 0.9917 (0.0054)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:17:43 2019
Total time elapsed: 2.0m:5.62s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9509,
    "inflation_factor": 1.0142,
    "mean_EFFECT": -6.5579e-06,
    "n": 26655,
    "n_snps": 12871266,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1223439,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 407119,
    "n_est": 26773.4327,
    "ratio_se_n": 1.0022,
    "mean_diff": -0,
    "ratio_diff": 2.1275,
    "sd_y_est1": 0.4582,
    "sd_y_est2": 0.4592,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283348,
    "ldsc_nsnp_merge_regression_ld": 1283348,
    "ldsc_observed_scale_h2_beta": 0.0596,
    "ldsc_observed_scale_h2_se": 0.0157,
    "ldsc_intercept_beta": 0.9917,
    "ldsc_intercept_se": 0.0054,
    "ldsc_lambda_gc": 1.0155,
    "ldsc_mean_chisq": 1.0226,
    "ldsc_ratio": -0.3673
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 12860245 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 55535 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32856 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.059713e+00 6.185658e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.896703e+07 5.594265e+07 3.02000e+02 3.282492e+07 7.003854e+07 1.148055e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -6.600000e-06 1.940390e-02 -2.14765e-01 -5.812000e-03 -5.000000e-05 5.703200e-03 2.325510e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.434940e-02 1.300070e-02 3.28470e-03 4.661000e-03 8.012100e-03 2.029200e-02 7.430770e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.974402e-01 2.890547e-01 1.00000e-07 2.464830e-01 4.969675e-01 7.471796e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.974342e-01 2.890582e-01 1.00000e-07 2.464729e-01 4.969621e-01 7.471765e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.008433e-01 2.567364e-01 1.56490e-03 1.029620e-02 7.317610e-02 3.152520e-01 9.984350e-01 ▇▂▁▁▁
numeric AF_reference 407119 0.9683699 NA NA NA NA NA 2.041392e-01 2.487759e-01 0.00000e+00 7.587900e-03 9.524760e-02 3.226840e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.665500e+04 0.000000e+00 2.66550e+04 2.665500e+04 2.665500e+04 2.665500e+04 2.665500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0063303 0.0069367 0.3614698 0.3614610 0.1122330 0.1894970 26655
1 693731 rs12238997 A G 0.0055324 0.0065516 0.3984318 0.3984253 0.1175190 0.1417730 26655
1 707522 rs371890604 G C 0.0038908 0.0073481 0.5964637 0.5964586 0.0992288 0.1293930 26655
1 717587 rs144155419 G A 0.0253841 0.0175498 0.1480751 0.1480639 0.0158361 0.0045926 26655
1 723329 rs189787166 A T -0.0231205 0.0478029 0.6286284 0.6286250 0.0020169 0.0003994 26655
1 730087 rs148120343 T C -0.0000846 0.0091015 0.9925850 0.9925852 0.0573653 0.0127796 26655
1 731718 rs142557973 T C 0.0030169 0.0062180 0.6275524 0.6275485 0.1236290 0.1543530 26655
1 732032 rs61770163 A C 0.0055451 0.0066136 0.4017927 0.4017855 0.1233120 0.1555510 26655
1 734349 rs141242758 T C 0.0028185 0.0062182 0.6503558 0.6503533 0.1230010 0.1525560 26655
1 740284 rs61770167 C T 0.0222906 0.0289574 0.4414424 0.4414351 0.0056189 0.0023962 26655
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0024244 0.0071992 0.7363054 0.7363026 0.0566278 0.0309934 26655
23 154923374 rs111332691 T A -0.0075762 0.0080000 0.3436347 0.3436266 0.0451135 0.0116556 26655
23 154925045 rs509981 C T 0.0030553 0.0038143 0.4231360 0.4231296 0.2483730 0.3634440 26655
23 154925895 rs538470 C T 0.0022054 0.0038987 0.5716300 0.5716252 0.2445920 0.3634440 26655
23 154927581 rs644138 G A 0.0023622 0.0035909 0.5106508 0.5106453 0.3053180 0.4635760 26655
23 154929412 rs557132 C T 0.0029166 0.0038151 0.4445903 0.4445833 0.2482530 0.3568210 26655
23 154929637 rs35185538 CT C 0.0077854 0.0039801 0.0504661 0.0504550 0.2326830 0.3011920 26655
23 154929952 rs4012982 CAA C 0.0040191 0.0040103 0.3162533 0.3162449 0.2425520 0.3165560 26655
23 154930230 rs781880 A G 0.0029757 0.0038142 0.4352903 0.4352836 0.2486750 0.3618540 26655
23 154930487 rs781879 T A 0.0394262 0.0131099 0.0026377 0.0026353 0.0194572 0.1263580 26655

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112233 ES:SE:LP:AF:SS:ID   0.00633029:0.00693666:0.441928:0.112233:26655:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117519 ES:SE:LP:AF:SS:ID   0.00553243:0.00655162:0.399646:0.117519:26655:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0992288    ES:SE:LP:AF:SS:ID   0.00389083:0.00734812:0.224416:0.0992288:26655:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158361    ES:SE:LP:AF:SS:ID   0.0253841:0.0175498:0.829518:0.0158361:26655:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00201691   ES:SE:LP:AF:SS:ID   -0.0231205:0.0478029:0.201606:0.00201691:26655:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0573653    ES:SE:LP:AF:SS:ID   -8.4583e-05:0.00910154:0.00323229:0.0573653:26655:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123629 ES:SE:LP:AF:SS:ID   0.00301687:0.00621804:0.20235:0.123629:26655:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123312 ES:SE:LP:AF:SS:ID   0.00554506:0.00661357:0.395998:0.123312:26655:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123001 ES:SE:LP:AF:SS:ID   0.00281851:0.00621815:0.186849:0.123001:26655:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00561893   ES:SE:LP:AF:SS:ID   0.0222906:0.0289574:0.355126:0.00561893:26655:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00199712   ES:SE:LP:AF:SS:ID   0.0534297:0.0519862:0.517028:0.00199712:26655:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867687 ES:SE:LP:AF:SS:ID   -0.00371482:0.00612431:0.264289:0.867687:26655:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.124946 ES:SE:LP:AF:SS:ID   0.00492274:0.00606934:0.379525:0.124946:26655:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144586 ES:SE:LP:AF:SS:ID   0.00365853:0.00598981:0.266527:0.144586:26655:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125072 ES:SE:LP:AF:SS:ID   0.00505825:0.00606067:0.393673:0.125072:26655:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868342 ES:SE:LP:AF:SS:ID   -0.005469:0.00590261:0.450783:0.868342:26655:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873089 ES:SE:LP:AF:SS:ID   -0.00637266:0.00599503:0.540915:0.873089:26655:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131063 ES:SE:LP:AF:SS:ID   0.00471345:0.00591968:0.370689:0.131063:26655:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363159    ES:SE:LP:AF:SS:ID   0.0146914:0.0107758:0.762514:0.0363159:26655:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867898 ES:SE:LP:AF:SS:ID   -0.00591783:0.0058953:0.501036:0.867898:26655:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868011 ES:SE:LP:AF:SS:ID   -0.00592158:0.00589908:0.501031:0.868011:26655:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867892 ES:SE:LP:AF:SS:ID   -0.0059408:0.005895:0.503659:0.867892:26655:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00529754   ES:SE:LP:AF:SS:ID   0.0133546:0.0296934:0.185157:0.00529754:26655:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00526466   ES:SE:LP:AF:SS:ID   0.013572:0.0297694:0.188116:0.00526466:26655:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00593613   ES:SE:LP:AF:SS:ID   0.00601637:0.0285327:0.0793555:0.00593613:26655:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868019 ES:SE:LP:AF:SS:ID   -0.00577479:0.00588622:0.486028:0.868019:26655:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128193 ES:SE:LP:AF:SS:ID   0.00490125:0.00600784:0.382353:0.128193:26655:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867511 ES:SE:LP:AF:SS:ID   -0.00568018:0.0058689:0.477385:0.867511:26655:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8669   ES:SE:LP:AF:SS:ID   -0.00547874:0.00586837:0.455292:0.8669:26655:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867704 ES:SE:LP:AF:SS:ID   -0.0054056:0.00587673:0.446519:0.867704:26655:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867712 ES:SE:LP:AF:SS:ID   -0.00540551:0.00587721:0.446462:0.867712:26655:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867716 ES:SE:LP:AF:SS:ID   -0.00540072:0.00587723:0.445941:0.867716:26655:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868148 ES:SE:LP:AF:SS:ID   -0.00573303:0.00589228:0.48073:0.868148:26655:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100515 ES:SE:LP:AF:SS:ID   0.00217551:0.00685802:0.124315:0.100515:26655:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00690964   ES:SE:LP:AF:SS:ID   0.000425162:0.0256817:0.00577438:0.00690964:26655:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872215 ES:SE:LP:AF:SS:ID   -0.00667866:0.005979:0.578403:0.872215:26655:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.861536 ES:SE:LP:AF:SS:ID   -0.00721211:0.00586759:0.659498:0.861536:26655:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867022 ES:SE:LP:AF:SS:ID   -0.00650525:0.0059254:0.564991:0.867022:26655:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864136 ES:SE:LP:AF:SS:ID   -0.00413329:0.00592605:0.313803:0.864136:26655:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.101599 ES:SE:LP:AF:SS:ID   0.00962761:0.00704499:0.765063:0.101599:26655:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869319 ES:SE:LP:AF:SS:ID   -0.0045142:0.00599355:0.345486:0.869319:26655:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869319 ES:SE:LP:AF:SS:ID   -0.00451464:0.00599355:0.345528:0.869319:26655:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869315 ES:SE:LP:AF:SS:ID   -0.00451674:0.00599357:0.345729:0.869315:26655:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869639 ES:SE:LP:AF:SS:ID   -0.00426822:0.00599605:0.321872:0.869639:26655:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127676 ES:SE:LP:AF:SS:ID   0.00493841:0.006006:0.386217:0.127676:26655:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107267 ES:SE:LP:AF:SS:ID   -0.000360846:0.00652667:0.0195834:0.107267:26655:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852697 ES:SE:LP:AF:SS:ID   -0.0028581:0.00586282:0.203487:0.852697:26655:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00191694   ES:SE:LP:AF:SS:ID   -0.0321267:0.048059:0.297716:0.00191694:26655:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837135 ES:SE:LP:AF:SS:ID   -0.00716031:0.00576298:0.669434:0.837135:26655:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.760724 ES:SE:LP:AF:SS:ID   -0.00573211:0.00462894:0.666335:0.760724:26655:rs2977608