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-4849_1/ukb-d-4849_1.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-4849_1/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 17:12:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4849_1/ukb-d-4849_1.vcf.gz ...
Read summary statistics for 13568108 SNPs.
Dropped 12692 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0017 (0.0037)
Lambda GC: 1.0042
Mean Chi^2: 1.0044
Intercept: 1.0003 (0.0059)
Ratio: 0.0785 (1.336)
Analysis finished at Mon Nov 25 17:14:15 2019
Total time elapsed: 2.0m:6.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0061,
    "mean_EFFECT": 3.4594e-07,
    "n": 119880,
    "n_snps": 13568108,
    "n_clumped_hits": 0,
    "n_p_sig": 6,
    "n_mono": 0,
    "n_ns": 1251235,
    "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": 563347,
    "n_est": 120351.2596,
    "ratio_se_n": 1.002,
    "mean_diff": 1.4511e-06,
    "ratio_diff": 2.7078,
    "sd_y_est1": 0.148,
    "sd_y_est2": 0.1483,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0017,
    "ldsc_observed_scale_h2_se": 0.0037,
    "ldsc_intercept_beta": 1.0003,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0042,
    "ldsc_mean_chisq": 1.0044,
    "ldsc_ratio": 0.0682
}

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 13556080 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57058 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33327 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051379e+00 6.184942e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902541e+07 5.591660e+07 3.0200e+02 3.292895e+07 7.013918e+07 1.148577e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.000000e-07 3.515800e-03 -5.4959e-02 -9.015000e-04 1.650000e-05 9.597000e-04 3.835950e-02 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.530200e-03 2.438300e-03 4.9640e-04 7.227000e-04 1.329300e-03 3.633100e-03 1.241470e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.992654e-01 2.886266e-01 0.0000e+00 2.492350e-01 4.986915e-01 7.491417e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.992641e-01 2.886274e-01 0.0000e+00 2.492323e-01 4.986912e-01 7.491414e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910555e-01 2.544611e-01 1.0000e-03 7.505200e-03 6.030340e-02 2.958180e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563347 0.9584801 NA NA NA NA NA 1.965083e-01 2.471416e-01 0.0000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.198800e+05 0.000000e+00 1.1988e+05 1.198800e+05 1.198800e+05 1.198800e+05 1.198800e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0020142 0.0010573 0.0567806 0.0567793 0.1114330 0.1894970 119880
1 693731 rs12238997 A G 0.0013315 0.0010002 0.1831332 0.1831307 0.1166860 0.1417730 119880
1 707522 rs371890604 G C 0.0014564 0.0011225 0.1945020 0.1945008 0.0981079 0.1293930 119880
1 717587 rs144155419 G A 0.0037061 0.0026956 0.1691741 0.1691724 0.0156650 0.0045926 119880
1 723329 rs189787166 A T 0.0005799 0.0080377 0.9424849 0.9424853 0.0016747 0.0003994 119880
1 730087 rs148120343 T C 0.0010093 0.0013951 0.4694086 0.4694089 0.0567674 0.0127796 119880
1 731718 rs142557973 T C 0.0012662 0.0009495 0.1823862 0.1823819 0.1225130 0.1543530 119880
1 732032 rs61770163 A C 0.0016110 0.0010119 0.1113779 0.1113751 0.1220470 0.1555510 119880
1 734349 rs141242758 T C 0.0012609 0.0009502 0.1844901 0.1844870 0.1217290 0.1525560 119880
1 740284 rs61770167 C T 0.0046618 0.0042460 0.2722300 0.2722287 0.0060140 0.0023962 119880
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0000623 0.0011072 0.9551520 0.9551518 0.0549631 0.0309934 119880
23 154923374 rs111332691 T A -0.0001145 0.0012077 0.9244670 0.9244670 0.0442568 0.0116556 119880
23 154925045 rs509981 C T 0.0010290 0.0005806 0.0763467 0.0763453 0.2438930 0.3634440 119880
23 154925895 rs538470 C T 0.0008518 0.0005936 0.1512910 0.1512879 0.2403940 0.3634440 119880
23 154927581 rs644138 G A 0.0009056 0.0005461 0.0972434 0.0972412 0.2992620 0.4635760 119880
23 154929412 rs557132 C T 0.0010163 0.0005808 0.0801512 0.0801470 0.2437180 0.3568210 119880
23 154929637 rs35185538 CT C 0.0010429 0.0006058 0.0851707 0.0851683 0.2277460 0.3011920 119880
23 154929952 rs4012982 CAA C 0.0010818 0.0006112 0.0767255 0.0767237 0.2377740 0.3165560 119880
23 154930230 rs781880 A G 0.0010296 0.0005807 0.0762044 0.0762016 0.2442010 0.3618540 119880
23 154930487 rs781879 T A -0.0031657 0.0020195 0.1169879 0.1169849 0.0190232 0.1263580 119880

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111433 ES:SE:LP:AF:SS:ID   0.00201422:0.00105733:1.2458:0.111433:119880:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116686 ES:SE:LP:AF:SS:ID   0.00133151:0.00100025:0.737233:0.116686:119880:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981079    ES:SE:LP:AF:SS:ID   0.00145636:0.00112254:0.711076:0.0981079:119880:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015665 ES:SE:LP:AF:SS:ID   0.00370608:0.00269559:0.771666:0.015665:119880:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00167473   ES:SE:LP:AF:SS:ID   0.000579889:0.00803766:0.0257256:0.00167473:119880:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0567674    ES:SE:LP:AF:SS:ID   0.00100928:0.00139511:0.328449:0.0567674:119880:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122513 ES:SE:LP:AF:SS:ID   0.00126616:0.000949532:0.739008:0.122513:119880:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122047 ES:SE:LP:AF:SS:ID   0.00161102:0.00101192:0.953201:0.122047:119880:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121729 ES:SE:LP:AF:SS:ID   0.00126093:0.000950164:0.734027:0.121729:119880:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00601396   ES:SE:LP:AF:SS:ID   0.00466184:0.00424597:0.565064:0.00601396:119880:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00177539   ES:SE:LP:AF:SS:ID   0.00260128:0.00854254:0.118763:0.00177539:119880:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868961 ES:SE:LP:AF:SS:ID   -0.00189883:0.000936593:1.37033:0.868961:119880:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158963   ES:SE:LP:AF:SS:ID   -0.0161569:0.00828331:1.29146:0.00158963:119880:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123621 ES:SE:LP:AF:SS:ID   0.00169812:0.000927869:1.17242:0.123621:119880:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143235 ES:SE:LP:AF:SS:ID   0.00184943:0.000918839:1.35518:0.143235:119880:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12374  ES:SE:LP:AF:SS:ID   0.00171258:0.000926524:1.19012:0.12374:119880:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   -0.0015709:0.000902451:1.08758:0.87014:119880:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874828 ES:SE:LP:AF:SS:ID   -0.00178469:0.000917641:1.28572:0.874828:119880:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129435 ES:SE:LP:AF:SS:ID   0.001556:0.000904413:1.06878:0.129435:119880:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0367284    ES:SE:LP:AF:SS:ID   0.00120579:0.00163218:0.337193:0.0367284:119880:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869751 ES:SE:LP:AF:SS:ID   -0.00157823:0.00090154:1.0968:0.869751:119880:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869872 ES:SE:LP:AF:SS:ID   -0.00159658:0.000902034:1.11502:0.869872:119880:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869742 ES:SE:LP:AF:SS:ID   -0.00157913:0.000901485:1.09784:0.869742:119880:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00507954   ES:SE:LP:AF:SS:ID   0.0104283:0.00462502:1.61706:0.00507954:119880:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00504675   ES:SE:LP:AF:SS:ID   0.0104993:0.00463715:1.62772:0.00504675:119880:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00552489   ES:SE:LP:AF:SS:ID   0.00356151:0.00449562:0.368318:0.00552489:119880:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869867 ES:SE:LP:AF:SS:ID   -0.00155158:0.000900021:1.07201:0.869867:119880:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126721 ES:SE:LP:AF:SS:ID   0.0016405:0.000918369:1.13047:0.126721:119880:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869453 ES:SE:LP:AF:SS:ID   -0.00147539:0.000897956:0.998374:0.869453:119880:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86866  ES:SE:LP:AF:SS:ID   -0.00148402:0.00089686:1.00882:0.86866:119880:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869599 ES:SE:LP:AF:SS:ID   -0.00151568:0.000898669:1.03769:0.869599:119880:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869606 ES:SE:LP:AF:SS:ID   -0.00151566:0.000898733:1.03756:0.869606:119880:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869614 ES:SE:LP:AF:SS:ID   -0.00151526:0.000898761:1.03712:0.869614:119880:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870038 ES:SE:LP:AF:SS:ID   -0.0015866:0.000901048:1.10642:0.870038:119880:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996424    ES:SE:LP:AF:SS:ID   0.00130641:0.00104497:0.675246:0.0996424:119880:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00632799   ES:SE:LP:AF:SS:ID   0.00173269:0.00408183:0.173141:0.00632799:119880:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873975 ES:SE:LP:AF:SS:ID   -0.00183553:0.000914779:1.3487:0.873975:119880:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863333 ES:SE:LP:AF:SS:ID   -0.00139907:0.000896993:0.925089:0.863333:119880:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868756 ES:SE:LP:AF:SS:ID   -0.00168158:0.000905609:1.19836:0.868756:119880:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86552  ES:SE:LP:AF:SS:ID   -0.00162128:0.000905528:1.13438:0.86552:119880:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0992499    ES:SE:LP:AF:SS:ID   0.00179938:0.001086:1.0108:0.0992499:119880:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870772 ES:SE:LP:AF:SS:ID   -0.00183657:0.000915977:1.34717:0.870772:119880:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870772 ES:SE:LP:AF:SS:ID   -0.00183659:0.000915977:1.34719:0.870772:119880:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870774 ES:SE:LP:AF:SS:ID   -0.00183844:0.000916025:1.34917:0.870774:119880:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871164 ES:SE:LP:AF:SS:ID   -0.00185378:0.000916584:1.36524:0.871164:119880:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126297 ES:SE:LP:AF:SS:ID   0.00171772:0.000917189:1.21398:0.126297:119880:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106113 ES:SE:LP:AF:SS:ID   0.000813607:0.000997496:0.382264:0.106113:119880:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854694 ES:SE:LP:AF:SS:ID   -0.00145646:0.00089695:0.981204:0.854694:119880:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00157509   ES:SE:LP:AF:SS:ID   -0.00176418:0.00809832:0.0822058:0.00157509:119880:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838005 ES:SE:LP:AF:SS:ID   0.00117488:0.000881925:0.738014:0.838005:119880:rs376645387