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-20427/ukb-d-20427.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-20427/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 17:13:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20427/ukb-d-20427.vcf.gz ...
Read summary statistics for 13542828 SNPs.
Dropped 12661 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, 1283494 SNPs remain.
After merging with regression SNP LD, 1283494 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0537 (0.0137)
Lambda GC: 1.0163
Mean Chi^2: 1.0239
Intercept: 0.9865 (0.0056)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:16:04 2019
Total time elapsed: 2.0m:10.86s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0112,
    "mean_EFFECT": -0,
    "n": 35584,
    "n_snps": 13542828,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250267,
    "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": 557808,
    "n_est": 35698.0836,
    "ratio_se_n": 1.0016,
    "mean_diff": -0,
    "ratio_diff": 59.5227,
    "sd_y_est1": 0.3832,
    "sd_y_est2": 0.3838,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283494,
    "ldsc_nsnp_merge_regression_ld": 1283494,
    "ldsc_observed_scale_h2_beta": 0.0537,
    "ldsc_observed_scale_h2_se": 0.0137,
    "ldsc_intercept_beta": 0.9865,
    "ldsc_intercept_se": 0.0056,
    "ldsc_lambda_gc": 1.0163,
    "ldsc_mean_chisq": 1.0239,
    "ldsc_ratio": -0.5649
}

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 13530831 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57010 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33313 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051560e+00 6.185072e+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 7.902331e+07 5.591456e+07 3.02000e+02 3.292580e+07 7.014008e+07 1.148558e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.900000e-05 1.666590e-02 -2.25401e-01 -4.384300e-03 2.220000e-05 4.476900e-03 1.905420e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.197030e-02 1.152300e-02 2.44090e-03 3.431700e-03 6.296100e-03 1.717140e-02 6.378190e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.980891e-01 2.889686e-01 0.00000e+00 2.477411e-01 4.976064e-01 7.477648e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.980847e-01 2.889713e-01 0.00000e+00 2.477340e-01 4.976027e-01 7.477623e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913834e-01 2.545459e-01 1.00000e-03 7.582000e-03 6.070520e-02 2.965260e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557808 0.9588116 NA NA NA NA NA 1.967571e-01 2.471946e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.558400e+04 0.000000e+00 3.55840e+04 3.558400e+04 3.558400e+04 3.558400e+04 3.558400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0037853 0.0050053 0.4494962 0.4494910 0.1120450 0.1894970 35584
1 693731 rs12238997 A G 0.0056169 0.0047256 0.2346011 0.2345932 0.1171420 0.1417730 35584
1 707522 rs371890604 G C 0.0073978 0.0053062 0.1632770 0.1632682 0.0989450 0.1293930 35584
1 717587 rs144155419 G A -0.0046202 0.0124436 0.7104213 0.7104194 0.0163751 0.0045926 35584
1 723329 rs189787166 A T -0.0516195 0.0365429 0.1577909 0.1577814 0.0018368 0.0003994 35584
1 730087 rs148120343 T C 0.0013735 0.0065622 0.8342150 0.8342138 0.0570957 0.0127796 35584
1 731718 rs142557973 T C 0.0028069 0.0044788 0.5308539 0.5308499 0.1237100 0.1543530 35584
1 732032 rs61770163 A C 0.0056600 0.0047742 0.2358159 0.2358077 0.1232440 0.1555510 35584
1 734349 rs141242758 T C 0.0033080 0.0044824 0.4605184 0.4605130 0.1228920 0.1525560 35584
1 740284 rs61770167 C T 0.0005349 0.0209780 0.9796580 0.9796576 0.0056266 0.0023962 35584
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0016943 0.0053787 0.7527625 0.7527593 0.0564587 0.0309934 35584
23 154923374 rs111332691 T A -0.0036150 0.0059958 0.5465652 0.5465614 0.0438961 0.0116556 35584
23 154925045 rs509981 C T -0.0055930 0.0028596 0.0504847 0.0504775 0.2434400 0.3634440 35584
23 154925895 rs538470 C T -0.0063331 0.0029247 0.0303648 0.0303580 0.2397680 0.3634440 35584
23 154927581 rs644138 G A -0.0054881 0.0026836 0.0408583 0.0408513 0.3003680 0.4635760 35584
23 154929412 rs557132 C T -0.0056994 0.0028602 0.0463116 0.0463035 0.2432950 0.3568210 35584
23 154929637 rs35185538 CT C -0.0048328 0.0029863 0.1056061 0.1055969 0.2277120 0.3011920 35584
23 154929952 rs4012982 CAA C -0.0057133 0.0030128 0.0579269 0.0579194 0.2376350 0.3165560 35584
23 154930230 rs781880 A G -0.0057752 0.0028598 0.0434510 0.0434439 0.2435920 0.3618540 35584
23 154930487 rs781879 T A 0.0036777 0.0094651 0.6976105 0.6976082 0.0203455 0.1263580 35584

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112045 ES:SE:LP:AF:SS:ID   0.00378532:0.00500529:0.347274:0.112045:35584:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117142 ES:SE:LP:AF:SS:ID   0.00561686:0.00472557:0.62967:0.117142:35584:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098945 ES:SE:LP:AF:SS:ID   0.00739778:0.00530625:0.787075:0.098945:35584:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0163751    ES:SE:LP:AF:SS:ID   -0.00462022:0.0124436:0.148484:0.0163751:35584:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00183675   ES:SE:LP:AF:SS:ID   -0.0516195:0.0365429:0.801918:0.00183675:35584:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570957    ES:SE:LP:AF:SS:ID   0.00137346:0.00656215:0.078722:0.0570957:35584:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12371  ES:SE:LP:AF:SS:ID   0.00280688:0.00447876:0.275025:0.12371:35584:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123244 ES:SE:LP:AF:SS:ID   0.00566002:0.00477425:0.627427:0.123244:35584:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122892 ES:SE:LP:AF:SS:ID   0.003308:0.00448237:0.336753:0.122892:35584:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00562662   ES:SE:LP:AF:SS:ID   0.0005349:0.020978:0.00892551:0.00562662:35584:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00203418   ES:SE:LP:AF:SS:ID   0.00751564:0.0368334:0.0765902:0.00203418:35584:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867658 ES:SE:LP:AF:SS:ID   -0.00432856:0.00440666:0.486822:0.867658:35584:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00147737   ES:SE:LP:AF:SS:ID   -0.0348856:0.0409571:0.404114:0.00147737:35584:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124943 ES:SE:LP:AF:SS:ID   0.00450795:0.00436896:0.519754:0.124943:35584:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144887 ES:SE:LP:AF:SS:ID   0.00332095:0.00432134:0.354386:0.144887:35584:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12502  ES:SE:LP:AF:SS:ID   0.00457491:0.00436334:0.531031:0.12502:35584:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868353 ES:SE:LP:AF:SS:ID   -0.00337244:0.00425432:0.368604:0.868353:35584:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873368 ES:SE:LP:AF:SS:ID   -0.00465487:0.00432342:0.550309:0.873368:35584:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131084 ES:SE:LP:AF:SS:ID   0.00292655:0.00426447:0.307548:0.131084:35584:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365333    ES:SE:LP:AF:SS:ID   -0.0101443:0.00777048:0.717305:0.0365333:35584:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867916 ES:SE:LP:AF:SS:ID   -0.00331934:0.00424912:0.36181:0.867916:35584:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867989 ES:SE:LP:AF:SS:ID   -0.00359128:0.00425003:0.399991:0.867989:35584:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86791  ES:SE:LP:AF:SS:ID   -0.00332904:0.00424891:0.363175:0.86791:35584:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00538373   ES:SE:LP:AF:SS:ID   0.00256799:0.0212125:0.0440026:0.00538373:35584:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00535816   ES:SE:LP:AF:SS:ID   0.0025616:0.0212559:0.0437941:0.00535816:35584:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00593013   ES:SE:LP:AF:SS:ID   0.0178676:0.0204831:0.416751:0.00593013:35584:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868027 ES:SE:LP:AF:SS:ID   -0.00370377:0.00424261:0.417173:0.868027:35584:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128364 ES:SE:LP:AF:SS:ID   0.00363672:0.00432537:0.397427:0.128364:35584:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867511 ES:SE:LP:AF:SS:ID   -0.0039319:0.00423119:0.452523:0.867511:35584:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866949 ES:SE:LP:AF:SS:ID   -0.00353831:0.00422792:0.395063:0.866949:35584:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867704 ES:SE:LP:AF:SS:ID   -0.00381602:0.00423547:0.43461:0.867704:35584:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867711 ES:SE:LP:AF:SS:ID   -0.00380764:0.00423574:0.433332:0.867711:35584:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867713 ES:SE:LP:AF:SS:ID   -0.00380955:0.00423575:0.433613:0.867713:35584:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868164 ES:SE:LP:AF:SS:ID   -0.00364123:0.00424652:0.407606:0.868164:35584:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100352 ES:SE:LP:AF:SS:ID   0.00528073:0.00493379:0.545944:0.100352:35584:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00688176   ES:SE:LP:AF:SS:ID   0.0184324:0.0185646:0.493798:0.00688176:35584:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872459 ES:SE:LP:AF:SS:ID   -0.00444667:0.00431186:0.519385:0.872459:35584:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.861258 ES:SE:LP:AF:SS:ID   -0.00329629:0.00422237:0.36151:0.861258:35584:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867089 ES:SE:LP:AF:SS:ID   -0.00396486:0.00427212:0.451767:0.867089:35584:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864049 ES:SE:LP:AF:SS:ID   -0.00348439:0.00426976:0.382507:0.864049:35584:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100653 ES:SE:LP:AF:SS:ID   0.00479604:0.00509847:0.459828:0.100653:35584:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869286 ES:SE:LP:AF:SS:ID   -0.00347226:0.00431634:0.375568:0.869286:35584:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869285 ES:SE:LP:AF:SS:ID   -0.00347291:0.00431634:0.375658:0.869285:35584:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869282 ES:SE:LP:AF:SS:ID   -0.00347355:0.00431634:0.375746:0.869282:35584:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869684 ES:SE:LP:AF:SS:ID   -0.00380814:0.00431906:0.422575:0.869684:35584:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127775 ES:SE:LP:AF:SS:ID   0.00369699:0.00432499:0.405973:0.127775:35584:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106705 ES:SE:LP:AF:SS:ID   0.00389137:0.00471543:0.388022:0.106705:35584:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853115 ES:SE:LP:AF:SS:ID   -0.00381228:0.00422264:0.435774:0.853115:35584:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00174682   ES:SE:LP:AF:SS:ID   -0.0438366:0.0367298:0.633232:0.00174682:35584:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837848 ES:SE:LP:AF:SS:ID   -0.00383936:0.0041972:0.443296:0.837848:35584:rs376645387