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-20447/ukb-d-20447.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-20447/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 17:17:15 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20447/ukb-d-20447.vcf.gz ...
Read summary statistics for 13560804 SNPs.
Dropped 12684 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0218 (0.007)
Lambda GC: 1.0403
Mean Chi^2: 1.0342
Intercept: 1.0057 (0.0064)
Ratio: 0.1665 (0.1876)
Analysis finished at Mon Nov 25 17:19:31 2019
Total time elapsed: 2.0m:15.26s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0254,
    "mean_EFFECT": 0,
    "n": 66334,
    "n_snps": 13560804,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250948,
    "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": 561839,
    "n_est": 66501.3227,
    "ratio_se_n": 1.0013,
    "mean_diff": 0.0001,
    "ratio_diff": 25.4885,
    "sd_y_est1": 0.4391,
    "sd_y_est2": 0.4396,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0218,
    "ldsc_observed_scale_h2_se": 0.007,
    "ldsc_intercept_beta": 1.0057,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0403,
    "ldsc_mean_chisq": 1.0342,
    "ldsc_ratio": 0.1667
}

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 13548784 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57032 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33325 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051406e+00 6.184973e+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 7.902373e+07 5.591577e+07 3.02000e+02 3.292686e+07 7.013629e+07 1.148567e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.540000e-05 1.404930e-02 -1.93637e-01 -3.695300e-03 4.200000e-05 3.805600e-03 1.767990e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.007990e-02 9.709300e-03 2.04780e-03 2.881700e-03 5.297400e-03 1.447050e-02 4.896290e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.960717e-01 2.895265e-01 0.00000e+00 2.448612e-01 4.946113e-01 7.466207e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.960692e-01 2.895279e-01 0.00000e+00 2.448564e-01 4.946084e-01 7.466205e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911414e-01 2.544835e-01 1.00000e-03 7.522500e-03 6.044820e-02 2.960020e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561839 0.9585689 NA NA NA NA NA 1.965755e-01 2.471496e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.633400e+04 0.000000e+00 6.63340e+04 6.633400e+04 6.633400e+04 6.633400e+04 6.633400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0002866 0.0041909 0.9454799 0.9454795 0.1122000 0.1894970 66334
1 693731 rs12238997 A G 0.0004140 0.0039642 0.9168289 0.9168286 0.1172310 0.1417730 66334
1 707522 rs371890604 G C -0.0005686 0.0044402 0.8981050 0.8981044 0.0990009 0.1293930 66334
1 717587 rs144155419 G A -0.0118934 0.0107206 0.2672619 0.2672590 0.0156232 0.0045926 66334
1 723329 rs189787166 A T 0.0418422 0.0303049 0.1673728 0.1673689 0.0018653 0.0003994 66334
1 730087 rs148120343 T C 0.0008822 0.0055141 0.8728829 0.8728828 0.0572577 0.0127796 66334
1 731718 rs142557973 T C -0.0011238 0.0037605 0.7650609 0.7650593 0.1232250 0.1543530 66334
1 732032 rs61770163 A C -0.0018330 0.0040048 0.6471754 0.6471745 0.1228090 0.1555510 66334
1 734349 rs141242758 T C -0.0011757 0.0037618 0.7546281 0.7546282 0.1225150 0.1525560 66334
1 740284 rs61770167 C T 0.0328607 0.0171887 0.0559101 0.0559068 0.0058658 0.0023962 66334
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0046054 0.0045559 0.3120887 0.3120863 0.0555968 0.0309934 66334
23 154923374 rs111332691 T A 0.0071785 0.0050448 0.1547530 0.1547486 0.0434845 0.0116556 66334
23 154925045 rs509981 C T 0.0002266 0.0023878 0.9244021 0.9244017 0.2455250 0.3634440 66334
23 154925895 rs538470 C T 0.0001343 0.0024417 0.9561321 0.9561313 0.2418220 0.3634440 66334
23 154927581 rs644138 G A 0.0014573 0.0022478 0.5167756 0.5167750 0.3015410 0.4635760 66334
23 154929412 rs557132 C T 0.0001731 0.0023883 0.9422050 0.9422053 0.2454160 0.3568210 66334
23 154929637 rs35185538 CT C 0.0003507 0.0024949 0.8882271 0.8882267 0.2289950 0.3011920 66334
23 154929952 rs4012982 CAA C -0.0005885 0.0025161 0.8150559 0.8150558 0.2390850 0.3165560 66334
23 154930230 rs781880 A G 0.0001083 0.0023880 0.9638150 0.9638146 0.2457110 0.3618540 66334
23 154930487 rs781879 T A 0.0136311 0.0081192 0.0931816 0.0931785 0.0195324 0.1263580 66334

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.1122   ES:SE:LP:AF:SS:ID   0.000286595:0.00419093:0.0243477:0.1122:66334:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117231 ES:SE:LP:AF:SS:ID   0.000413984:0.00396425:0.0377117:0.117231:66334:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0990009    ES:SE:LP:AF:SS:ID   -0.000568593:0.00444018:0.0466729:0.0990009:66334:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156232    ES:SE:LP:AF:SS:ID   -0.0118934:0.0107206:0.573063:0.0156232:66334:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00186528   ES:SE:LP:AF:SS:ID   0.0418422:0.0303049:0.776315:0.00186528:66334:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572577    ES:SE:LP:AF:SS:ID   0.000882236:0.00551405:0.059044:0.0572577:66334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123225 ES:SE:LP:AF:SS:ID   -0.00112379:0.00376046:0.116304:0.123225:66334:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122809 ES:SE:LP:AF:SS:ID   -0.00183297:0.00400482:0.188978:0.122809:66334:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122515 ES:SE:LP:AF:SS:ID   -0.00117571:0.00376176:0.122267:0.122515:66334:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0058658    ES:SE:LP:AF:SS:ID   0.0328607:0.0171887:1.25251:0.0058658:66334:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00189694   ES:SE:LP:AF:SS:ID   0.0353937:0.0323266:0.562925:0.00189694:66334:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868326 ES:SE:LP:AF:SS:ID   0.00207603:0.00370453:0.240176:0.868326:66334:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00154353   ES:SE:LP:AF:SS:ID   -0.0329821:0.0335647:0.487066:0.00154353:66334:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124562 ES:SE:LP:AF:SS:ID   -0.00179784:0.00366757:0.20482:0.124562:66334:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143962 ES:SE:LP:AF:SS:ID   -0.00165772:0.00363082:0.188437:0.143962:66334:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124662 ES:SE:LP:AF:SS:ID   -0.00184121:0.00366267:0.210998:0.124662:66334:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869086 ES:SE:LP:AF:SS:ID   0.00148685:0.00356995:0.169378:0.869086:66334:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.8737   ES:SE:LP:AF:SS:ID   0.00131082:0.00362753:0.143975:0.8737:66334:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130298 ES:SE:LP:AF:SS:ID   -0.00190974:0.00358031:0.226391:0.130298:66334:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0364971    ES:SE:LP:AF:SS:ID   0.00501443:0.00652374:0.354472:0.0364971:66334:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868698 ES:SE:LP:AF:SS:ID   0.00127742:0.00356636:0.142544:0.868698:66334:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86878  ES:SE:LP:AF:SS:ID   0.00114307:0.00356774:0.125707:0.86878:66334:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8687   ES:SE:LP:AF:SS:ID   0.00127859:0.00356625:0.142697:0.8687:66334:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00500551   ES:SE:LP:AF:SS:ID   -0.000638768:0.0185521:0.0120952:0.00500551:66334:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00497355   ES:SE:LP:AF:SS:ID   -0.00125729:0.0185937:0.024068:0.00497355:66334:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00576527   ES:SE:LP:AF:SS:ID   0.0111418:0.0175135:0.280122:0.00576527:66334:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86873  ES:SE:LP:AF:SS:ID   0.00135406:0.00355977:0.152633:0.86873:66334:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127657 ES:SE:LP:AF:SS:ID   -0.00240572:0.00363355:0.294206:0.127657:66334:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86825  ES:SE:LP:AF:SS:ID   0.00144548:0.00355031:0.165004:0.86825:66334:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867725 ES:SE:LP:AF:SS:ID   0.0014738:0.00354901:0.168806:0.867725:66334:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868452 ES:SE:LP:AF:SS:ID   0.00148307:0.0035539:0.169762:0.868452:66334:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868459 ES:SE:LP:AF:SS:ID   0.00147883:0.00355415:0.169188:0.868459:66334:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868462 ES:SE:LP:AF:SS:ID   0.00148625:0.00355417:0.170166:0.868462:66334:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868857 ES:SE:LP:AF:SS:ID   0.00128586:0.00356298:0.143767:0.868857:66334:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100526 ES:SE:LP:AF:SS:ID   -0.00114782:0.00413223:0.107245:0.100526:66334:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0066401    ES:SE:LP:AF:SS:ID   0.0108214:0.015895:0.304523:0.0066401:66334:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872865 ES:SE:LP:AF:SS:ID   0.0012931:0.0036172:0.142227:0.872865:66334:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86233  ES:SE:LP:AF:SS:ID   0.00171382:0.00354764:0.201325:0.86233:66334:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867587 ES:SE:LP:AF:SS:ID   0.000618216:0.00358296:0.0639837:0.867587:66334:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864768 ES:SE:LP:AF:SS:ID   0.00102353:0.00358609:0.110516:0.864768:66334:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100635 ES:SE:LP:AF:SS:ID   0.00094554:0.0042769:0.0835303:0.100635:66334:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869812 ES:SE:LP:AF:SS:ID   0.00155287:0.00362522:0.174967:0.869812:66334:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869812 ES:SE:LP:AF:SS:ID   0.0015529:0.00362521:0.174971:0.869812:66334:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869809 ES:SE:LP:AF:SS:ID   0.00155166:0.00362522:0.174808:0.869809:66334:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870142 ES:SE:LP:AF:SS:ID   0.00149894:0.00362659:0.167892:0.870142:66334:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127282 ES:SE:LP:AF:SS:ID   -0.0017068:0.00362949:0.195063:0.127282:66334:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10708  ES:SE:LP:AF:SS:ID   -0.00109207:0.0039433:0.10689:0.10708:66334:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853597 ES:SE:LP:AF:SS:ID   0.00112761:0.00354729:0.124604:0.853597:66334:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00177332   ES:SE:LP:AF:SS:ID   0.0425905:0.0305153:0.788327:0.00177332:66334:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838087 ES:SE:LP:AF:SS:ID   -0.000916985:0.0035218:0.0998646:0.838087:66334:rs376645387