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-20548_3/ukb-d-20548_3.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-20548_3/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 16:39:44 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20548_3/ukb-d-20548_3.vcf.gz ...
Read summary statistics for 13364554 SNPs.
Dropped 12419 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, 1283469 SNPs remain.
After merging with regression SNP LD, 1283469 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0278 (0.0049)
Lambda GC: 1.0642
Mean Chi^2: 1.0694
Intercept: 1.0056 (0.0073)
Ratio: 0.0811 (0.1046)
Analysis finished at Mon Nov 25 16:41:45 2019
Total time elapsed: 2.0m:0.63s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9517,
    "inflation_factor": 1.0426,
    "mean_EFFECT": 0,
    "n": 114422,
    "n_snps": 13364554,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1244240,
    "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": 511011,
    "n_est": 114848.1596,
    "ratio_se_n": 1.0019,
    "mean_diff": 0,
    "ratio_diff": 15.0396,
    "sd_y_est1": 0.2884,
    "sd_y_est2": 0.289,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283469,
    "ldsc_nsnp_merge_regression_ld": 1283469,
    "ldsc_observed_scale_h2_beta": 0.0278,
    "ldsc_observed_scale_h2_se": 0.0049,
    "ldsc_intercept_beta": 1.0056,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0642,
    "ldsc_mean_chisq": 1.0694,
    "ldsc_ratio": 0.0807
}

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 13352796 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56659 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33226 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.054486e+00 6.185705e+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 7.900396e+07 5.592276e+07 3.02000e+02 3.289100e+07 7.010559e+07 1.148376e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.330000e-05 6.687900e-03 -7.80911e-02 -1.876200e-03 -1.190000e-05 1.849300e-03 9.678970e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.835600e-03 4.579500e-03 9.98000e-04 1.434600e-03 2.584800e-03 6.917900e-03 2.358800e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.934598e-01 2.908332e-01 2.00000e-07 2.397397e-01 4.910130e-01 7.458990e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.934584e-01 2.908340e-01 2.00000e-07 2.397372e-01 4.910119e-01 7.458981e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.937892e-01 2.551248e-01 1.18150e-03 8.220700e-03 6.376850e-02 3.012408e-01 9.988180e-01 ▇▂▁▁▁
numeric AF_reference 511011 0.9617637 NA NA NA NA NA 1.985594e-01 2.475866e-01 0.00000e+00 6.190100e-03 8.726040e-02 3.125000e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.144220e+05 0.000000e+00 1.14422e+05 1.144220e+05 1.144220e+05 1.144220e+05 1.144220e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0002284 0.0021002 0.9133901 0.9133895 0.1117110 0.1894970 114422
1 693731 rs12238997 A G 0.0014986 0.0019898 0.4513599 0.4513592 0.1166780 0.1417730 114422
1 707522 rs371890604 G C -0.0004191 0.0022322 0.8510859 0.8510861 0.0983298 0.1293930 114422
1 717587 rs144155419 G A -0.0016548 0.0053485 0.7570211 0.7570200 0.0157526 0.0045926 114422
1 723329 rs189787166 A T 0.0019466 0.0155303 0.9002530 0.9002522 0.0017896 0.0003994 114422
1 730087 rs148120343 T C 0.0018480 0.0027682 0.5043941 0.5043921 0.0568713 0.0127796 114422
1 731718 rs142557973 T C 0.0010425 0.0018880 0.5808473 0.5808461 0.1226010 0.1543530 114422
1 732032 rs61770163 A C -0.0008737 0.0020122 0.6641191 0.6641190 0.1222220 0.1555510 114422
1 734349 rs141242758 T C 0.0012467 0.0018890 0.5092804 0.5092798 0.1218520 0.1525560 114422
1 740284 rs61770167 C T -0.0130800 0.0086146 0.1289279 0.1289255 0.0058609 0.0023962 114422
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0010398 0.0022199 0.6394977 0.6394976 0.0553623 0.0309934 114422
23 154923374 rs111332691 T A 0.0013418 0.0024164 0.5786754 0.5786767 0.0448384 0.0116556 114422
23 154925045 rs509981 C T 0.0007457 0.0011645 0.5219369 0.5219352 0.2446210 0.3634440 114422
23 154925895 rs538470 C T 0.0011139 0.0011909 0.3496109 0.3496067 0.2409890 0.3634440 114422
23 154927581 rs644138 G A 0.0003799 0.0010957 0.7287776 0.7287760 0.3003390 0.4635760 114422
23 154929412 rs557132 C T 0.0007305 0.0011648 0.5305716 0.5305689 0.2444980 0.3568210 114422
23 154929637 rs35185538 CT C 0.0009158 0.0012166 0.4516115 0.4516101 0.2287980 0.3011920 114422
23 154929952 rs4012982 CAA C 0.0009354 0.0012260 0.4454521 0.4454495 0.2385330 0.3165560 114422
23 154930230 rs781880 A G 0.0007635 0.0011645 0.5120166 0.5120168 0.2449060 0.3618540 114422
23 154930487 rs781879 T A 0.0027876 0.0039518 0.4805626 0.4805610 0.0197245 0.1263580 114422

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111711 ES:SE:LP:AF:SS:ID   -0.000228432:0.00210025:0.0393437:0.111711:114422:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116678 ES:SE:LP:AF:SS:ID   0.00149865:0.00198984:0.345477:0.116678:114422:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983298    ES:SE:LP:AF:SS:ID   -0.000419059:0.00223221:0.0700266:0.0983298:114422:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157526    ES:SE:LP:AF:SS:ID   -0.00165481:0.00534851:0.120892:0.0157526:114422:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00178963   ES:SE:LP:AF:SS:ID   0.00194661:0.0155303:0.0456354:0.00178963:114422:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568713    ES:SE:LP:AF:SS:ID   0.00184805:0.00276822:0.29723:0.0568713:114422:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122601 ES:SE:LP:AF:SS:ID   0.00104248:0.00188804:0.235938:0.122601:114422:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122222 ES:SE:LP:AF:SS:ID   -0.000873747:0.00201216:0.177754:0.122222:114422:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121852 ES:SE:LP:AF:SS:ID   0.00124669:0.00188904:0.293043:0.121852:114422:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0058609    ES:SE:LP:AF:SS:ID   -0.01308:0.0086146:0.889653:0.0058609:114422:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0017873    ES:SE:LP:AF:SS:ID   0.0133701:0.0168351:0.369478:0.0017873:114422:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869045 ES:SE:LP:AF:SS:ID   -0.000745353:0.00186091:0.161928:0.869045:114422:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00160053   ES:SE:LP:AF:SS:ID   0.0101064:0.0164598:0.26824:0.00160053:114422:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123663 ES:SE:LP:AF:SS:ID   0.000716755:0.00184388:0.156466:0.123663:114422:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143266 ES:SE:LP:AF:SS:ID   -0.00012376:0.00182377:0.0241557:0.143266:114422:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123787 ES:SE:LP:AF:SS:ID   0.000743853:0.00184132:0.16353:0.123787:114422:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.86984  ES:SE:LP:AF:SS:ID   -0.00081436:0.00179356:0.187224:0.86984:114422:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874607 ES:SE:LP:AF:SS:ID   -0.0010233:0.00182342:0.240588:0.874607:114422:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129637 ES:SE:LP:AF:SS:ID   0.000707557:0.00179843:0.158639:0.129637:114422:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366494    ES:SE:LP:AF:SS:ID   -0.00539327:0.00325964:1.0087:0.0366494:114422:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869441 ES:SE:LP:AF:SS:ID   -0.000801426:0.00179185:0.183967:0.869441:114422:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869515 ES:SE:LP:AF:SS:ID   -0.000783618:0.00179253:0.179143:0.869515:114422:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86944  ES:SE:LP:AF:SS:ID   -0.000817419:0.0017918:0.188259:0.86944:114422:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00515222   ES:SE:LP:AF:SS:ID   0.00294263:0.00912378:0.126646:0.00515222:114422:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00512096   ES:SE:LP:AF:SS:ID   0.00322407:0.00914389:0.140025:0.00512096:114422:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00569216   ES:SE:LP:AF:SS:ID   0.00650925:0.00882605:0.336471:0.00569216:114422:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869508 ES:SE:LP:AF:SS:ID   -0.000774079:0.00178853:0.177075:0.869508:114422:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126917 ES:SE:LP:AF:SS:ID   0.000643471:0.00182548:0.139981:0.126917:114422:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869029 ES:SE:LP:AF:SS:ID   -0.000699856:0.00178382:0.158133:0.869029:114422:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868436 ES:SE:LP:AF:SS:ID   -0.000684129:0.00178323:0.154133:0.868436:114422:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869215 ES:SE:LP:AF:SS:ID   -0.000731914:0.00178559:0.166293:0.869215:114422:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869222 ES:SE:LP:AF:SS:ID   -0.000731952:0.00178572:0.166289:0.869222:114422:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869224 ES:SE:LP:AF:SS:ID   -0.000726326:0.00178572:0.164818:0.869224:114422:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869663 ES:SE:LP:AF:SS:ID   -0.00081088:0.00179032:0.186683:0.869663:114422:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099489 ES:SE:LP:AF:SS:ID   0.000716336:0.00208127:0.136255:0.099489:114422:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00655187   ES:SE:LP:AF:SS:ID   0.00181615:0.0080102:0.0858505:0.00655187:114422:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873708 ES:SE:LP:AF:SS:ID   -0.000997296:0.00181749:0.234184:0.873708:114422:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863017 ES:SE:LP:AF:SS:ID   -0.000760846:0.00178285:0.174213:0.863017:114422:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868401 ES:SE:LP:AF:SS:ID   -0.000744823:0.00179974:0.16814:0.868401:114422:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865415 ES:SE:LP:AF:SS:ID   -0.000504708:0.00179993:0.108369:0.865415:114422:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997473    ES:SE:LP:AF:SS:ID   0.00213787:0.00215053:0.494618:0.0997473:114422:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870695 ES:SE:LP:AF:SS:ID   -0.000740161:0.00182108:0.164677:0.870695:114422:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870695 ES:SE:LP:AF:SS:ID   -0.00074029:0.00182108:0.16471:0.870695:114422:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870693 ES:SE:LP:AF:SS:ID   -0.000742943:0.00182109:0.16539:0.870693:114422:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871018 ES:SE:LP:AF:SS:ID   -0.000769323:0.00182189:0.172094:0.871018:114422:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126512 ES:SE:LP:AF:SS:ID   0.000633561:0.00182342:0.137721:0.126512:114422:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106279 ES:SE:LP:AF:SS:ID   0.000700128:0.00198145:0.140362:0.106279:114422:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854464 ES:SE:LP:AF:SS:ID   -0.00138151:0.00178229:0.358263:0.854464:114422:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00170509   ES:SE:LP:AF:SS:ID   0.00176832:0.0155775:0.04114:0.00170509:114422:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839076 ES:SE:LP:AF:SS:ID   -0.001657:0.00176457:0.458778:0.839076:114422:rs376645387