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-20550_3/ukb-d-20550_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-20550_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 16:45:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20550_3/ukb-d-20550_3.vcf.gz ...
Read summary statistics for 12282662 SNPs.
Dropped 10855 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, 1283183 SNPs remain.
After merging with regression SNP LD, 1283183 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0283 (0.0047)
Lambda GC: 1.0499
Mean Chi^2: 1.0517
Intercept: 0.9963 (0.0058)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:48:10 2019
Total time elapsed: 2.0m:19.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9497,
    "inflation_factor": 1.0297,
    "mean_EFFECT": 4.3711e-06,
    "n": 98990,
    "n_snps": 12282662,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1197017,
    "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": 314970,
    "n_est": 99286.715,
    "ratio_se_n": 1.0015,
    "mean_diff": 0,
    "ratio_diff": 10.0848,
    "sd_y_est1": 0.2324,
    "sd_y_est2": 0.2327,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283183,
    "ldsc_nsnp_merge_regression_ld": 1283183,
    "ldsc_observed_scale_h2_beta": 0.0283,
    "ldsc_observed_scale_h2_se": 0.0047,
    "ldsc_intercept_beta": 0.9963,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0499,
    "ldsc_mean_chisq": 1.0517,
    "ldsc_ratio": -0.0716
}

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 12272433 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 54058 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32370 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.064951e+00 6.184448e+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 7.892096e+07 5.596648e+07 3.02000e+02 3.274165e+07 6.995838e+07 1.147843e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.400000e-06 4.411600e-03 -4.53206e-02 -1.469700e-03 -5.400000e-06 1.431500e-03 5.889790e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.345900e-03 2.855500e-03 8.63300e-04 1.209300e-03 1.967900e-03 4.654500e-03 1.708240e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.954093e-01 2.898798e-01 0.00000e+00 2.436049e-01 4.936964e-01 7.466533e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.954077e-01 2.898807e-01 0.00000e+00 2.436022e-01 4.936955e-01 7.466524e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.099715e-01 2.585573e-01 2.17960e-03 1.349380e-02 8.574600e-02 3.325900e-01 9.978200e-01 ▇▂▁▁▁
numeric AF_reference 314970 0.9743565 NA NA NA NA NA 2.118647e-01 2.501946e-01 0.00000e+00 1.018370e-02 1.060300e-01 3.362620e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.899000e+04 0.000000e+00 9.89900e+04 9.899000e+04 9.899000e+04 9.899000e+04 9.899000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0014607 0.0018227 0.4229081 0.4229064 0.1115540 0.1894970 98990
1 693731 rs12238997 A G 0.0010951 0.0017259 0.5257642 0.5257607 0.1164250 0.1417730 98990
1 707522 rs371890604 G C 0.0004007 0.0019400 0.8363520 0.8363516 0.0981163 0.1293930 98990
1 717587 rs144155419 G A 0.0089621 0.0046185 0.0523239 0.0523211 0.0158461 0.0045926 98990
1 730087 rs148120343 T C -0.0006312 0.0024048 0.7929723 0.7929712 0.0566111 0.0127796 98990
1 731718 rs142557973 T C 0.0007773 0.0016382 0.6351554 0.6351551 0.1223630 0.1543530 98990
1 732032 rs61770163 A C 0.0011833 0.0017472 0.4982634 0.4982587 0.1219830 0.1555510 98990
1 734349 rs141242758 T C 0.0006985 0.0016392 0.6700142 0.6700143 0.1216130 0.1525560 98990
1 740284 rs61770167 C T -0.0092589 0.0074784 0.2156920 0.2156887 0.0058414 0.0023962 98990
1 749963 rs529266287 T TAA -0.0007837 0.0016145 0.6273704 0.6273699 0.8692740 0.7641770 98990
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0030390 0.0019079 0.1111960 0.1111927 0.0559291 0.0309934 98990
23 154923374 rs111332691 T A -0.0049453 0.0020889 0.0179122 0.0179101 0.0448985 0.0116556 98990
23 154925045 rs509981 C T -0.0005357 0.0010082 0.5951576 0.5951566 0.2441810 0.3634440 98990
23 154925895 rs538470 C T -0.0006829 0.0010310 0.5077489 0.5077472 0.2406180 0.3634440 98990
23 154927581 rs644138 G A -0.0012211 0.0009474 0.1974390 0.1974344 0.3004650 0.4635760 98990
23 154929412 rs557132 C T -0.0005550 0.0010084 0.5820818 0.5820803 0.2440640 0.3568210 98990
23 154929637 rs35185538 CT C -0.0006880 0.0010541 0.5139431 0.5139425 0.2281060 0.3011920 98990
23 154929952 rs4012982 CAA C -0.0002351 0.0010614 0.8247380 0.8247370 0.2381730 0.3165560 98990
23 154930230 rs781880 A G -0.0005948 0.0010081 0.5552096 0.5552066 0.2444650 0.3618540 98990
23 154930487 rs781879 T A -0.0053709 0.0034240 0.1167449 0.1167413 0.0196595 0.1263580 98990

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111554 ES:SE:LP:AF:SS:ID   -0.00146066:0.00182266:0.373754:0.111554:98990:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116425 ES:SE:LP:AF:SS:ID   0.00109508:0.00172592:0.279209:0.116425:98990:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981163    ES:SE:LP:AF:SS:ID   0.000400725:0.00193997:0.0776109:0.0981163:98990:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158461    ES:SE:LP:AF:SS:ID   0.00896206:0.00461847:1.2813:0.0158461:98990:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0566111    ES:SE:LP:AF:SS:ID   -0.00063115:0.0024048:0.100742:0.0566111:98990:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122363 ES:SE:LP:AF:SS:ID   0.00077728:0.00163816:0.19712:0.122363:98990:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121983 ES:SE:LP:AF:SS:ID   0.00118326:0.0017472:0.302541:0.121983:98990:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121613 ES:SE:LP:AF:SS:ID   0.000698531:0.00163925:0.173916:0.121613:98990:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00584141   ES:SE:LP:AF:SS:ID   -0.00925886:0.00747844:0.666166:0.00584141:98990:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869274 ES:SE:LP:AF:SS:ID   -0.00078373:0.0016145:0.202476:0.869274:98990:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123375 ES:SE:LP:AF:SS:ID   0.000998151:0.00160064:0.273358:0.123375:98990:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143107 ES:SE:LP:AF:SS:ID   0.00192379:0.00158188:0.649882:0.143107:98990:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123485 ES:SE:LP:AF:SS:ID   0.00103487:0.00159847:0.2862:0.123485:98990:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870138 ES:SE:LP:AF:SS:ID   -0.00132121:0.0015565:0.40233:0.870138:98990:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874947 ES:SE:LP:AF:SS:ID   -0.000820644:0.00158308:0.218826:0.874947:98990:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129331 ES:SE:LP:AF:SS:ID   0.00141749:0.00156093:0.43911:0.129331:98990:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365845    ES:SE:LP:AF:SS:ID   -0.00141363:0.00282744:0.209644:0.0365845:98990:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869745 ES:SE:LP:AF:SS:ID   -0.00132152:0.00155514:0.402907:0.869745:98990:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869813 ES:SE:LP:AF:SS:ID   -0.00135821:0.00155561:0.417247:0.869813:98990:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869745 ES:SE:LP:AF:SS:ID   -0.00132947:0.0015551:0.406044:0.869745:98990:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512664   ES:SE:LP:AF:SS:ID   0.0169813:0.00793804:1.48919:0.00512664:98990:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509715   ES:SE:LP:AF:SS:ID   0.0171092:0.0079557:1.50151:0.00509715:98990:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00565755   ES:SE:LP:AF:SS:ID   -0.000855622:0.00767921:0.0403467:0.00565755:98990:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869823 ES:SE:LP:AF:SS:ID   -0.00133124:0.00155223:0.407713:0.869823:98990:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126603 ES:SE:LP:AF:SS:ID   0.00146583:0.00158453:0.449868:0.126603:98990:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86935  ES:SE:LP:AF:SS:ID   -0.00135607:0.00154822:0.41897:0.86935:98990:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868773 ES:SE:LP:AF:SS:ID   -0.00138793:0.00154761:0.432014:0.868773:98990:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869537 ES:SE:LP:AF:SS:ID   -0.00137947:0.00154972:0.427836:0.869537:98990:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869544 ES:SE:LP:AF:SS:ID   -0.00137695:0.00154983:0.42678:0.869544:98990:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869546 ES:SE:LP:AF:SS:ID   -0.0013764:0.00154984:0.426556:0.869546:98990:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869975 ES:SE:LP:AF:SS:ID   -0.00133087:0.00155378:0.407045:0.869975:98990:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09923  ES:SE:LP:AF:SS:ID   -0.000362681:0.0018079:0.0752019:0.09923:98990:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00652328   ES:SE:LP:AF:SS:ID   0.00138711:0.00696129:0.0746575:0.00652328:98990:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874033 ES:SE:LP:AF:SS:ID   -0.000980758:0.00157784:0.272281:0.874033:98990:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863358 ES:SE:LP:AF:SS:ID   -0.00148909:0.00154731:0.47384:0.863358:98990:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868717 ES:SE:LP:AF:SS:ID   -0.00131022:0.00156211:0.396191:0.868717:98990:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865738 ES:SE:LP:AF:SS:ID   -0.0015052:0.00156206:0.474634:0.865738:98990:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.09949  ES:SE:LP:AF:SS:ID   0.000761976:0.00186564:0.165603:0.09949:98990:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87108  ES:SE:LP:AF:SS:ID   -0.00144914:0.00158096:0.44449:0.87108:98990:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87108  ES:SE:LP:AF:SS:ID   -0.00144895:0.00158096:0.444411:0.87108:98990:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871079 ES:SE:LP:AF:SS:ID   -0.00144796:0.00158097:0.444016:0.871079:98990:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871404 ES:SE:LP:AF:SS:ID   -0.00126177:0.00158165:0.371596:0.871404:98990:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126213 ES:SE:LP:AF:SS:ID   0.00127534:0.00158271:0.376376:0.126213:98990:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105813 ES:SE:LP:AF:SS:ID   -0.000578791:0.00172181:0.132676:0.105813:98990:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854841 ES:SE:LP:AF:SS:ID   -0.000823947:0.0015471:0.225973:0.854841:98990:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839409 ES:SE:LP:AF:SS:ID   -0.00240616:0.00153061:0.935737:0.839409:98990:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763643 ES:SE:LP:AF:SS:ID   -0.00168359:0.00122759:0.768956:0.763643:98990:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105051 ES:SE:LP:AF:SS:ID   0.00161272:0.00169746:0.465877:0.105051:98990:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00769385   ES:SE:LP:AF:SS:ID   -0.00525483:0.00627881:0.39508:0.00769385:98990:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129579 ES:SE:LP:AF:SS:ID   0.00153331:0.00156011:0.487186:0.129579:98990:rs762168062