Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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-22605_irnt/ukb-d-22605_irnt.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-22605_irnt/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 14:57:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22605_irnt/ukb-d-22605_irnt.vcf.gz ...
Read summary statistics for 13541175 SNPs.
Dropped 12632 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, 1283500 SNPs remain.
After merging with regression SNP LD, 1283500 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0275 (0.0133)
Lambda GC: 1.025
Mean Chi^2: 1.0134
Intercept: 0.9948 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 14:59:24 2019
Total time elapsed: 2.0m:18.03s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0107,
    "mean_EFFECT": -0.0001,
    "n": 33696,
    "n_snps": 13541175,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250284,
    "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": 556886,
    "n_est": 33879.5418,
    "ratio_se_n": 1.0027,
    "mean_diff": -7.1873e-06,
    "ratio_diff": 2.7619,
    "sd_y_est1": 0.9246,
    "sd_y_est2": 0.9272,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283500,
    "ldsc_nsnp_merge_regression_ld": 1283500,
    "ldsc_observed_scale_h2_beta": 0.0275,
    "ldsc_observed_scale_h2_se": 0.0133,
    "ldsc_intercept_beta": 0.9948,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.025,
    "ldsc_mean_chisq": 1.0134,
    "ldsc_ratio": -0.3881
}

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 13529207 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57000 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33315 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051042e+00 6.184705e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 <U+2587><U+2585><U+2585><U+2582><U+2582>
numeric POS 0 1.0000000 NA NA NA NA NA 7.902407e+07 5.591893e+07 3.02000e+02 3.292291e+07 7.013466e+07 1.148592e+08 2.492309e+08 <U+2587><U+2586><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.0000000 NA NA NA NA NA -5.840000e-05 4.124450e-02 -4.84484e-01 -1.101200e-02 -1.850000e-05 1.090110e-02 5.753750e-01 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.0000000 NA NA NA NA NA 2.966760e-02 2.856130e-02 5.82040e-03 8.513700e-03 1.561440e-02 4.255700e-02 1.500290e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.986024e-01 2.886046e-01 2.00000e-07 2.485478e-01 4.977233e-01 7.484107e-01 1.000000e+00 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.985976e-01 2.886075e-01 2.00000e-07 2.485398e-01 4.977186e-01 7.484084e-01 9.999997e-01 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric AF 0 1.0000000 NA NA NA NA NA 1.914021e-01 2.545473e-01 1.00000e-03 7.591900e-03 6.072680e-02 2.964650e-01 9.990000e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric AF_reference 556886 0.9588746 NA NA NA NA NA 1.967755e-01 2.471991e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric N 0 1.0000000 NA NA NA NA NA 3.369600e+04 0.000000e+00 3.36960e+04 3.369600e+04 3.369600e+04 3.369600e+04 3.369600e+04 <U+2581><U+2581><U+2587><U+2581><U+2581>

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0248742 0.0123669 0.0442966 0.0442882 0.1123900 0.1894970 33696
1 693731 rs12238997 A G 0.0318127 0.0116912 0.0065104 0.0065069 0.1176840 0.1417730 33696
1 707522 rs371890604 G C 0.0321714 0.0131410 0.0143635 0.0143584 0.0990234 0.1293930 33696
1 717587 rs144155419 G A 0.0137720 0.0316578 0.6635475 0.6635428 0.0157300 0.0045926 33696
1 723329 rs189787166 A T -0.0152511 0.0927650 0.8694129 0.8694117 0.0017505 0.0003994 33696
1 730087 rs148120343 T C 0.0290368 0.0161847 0.0728082 0.0727989 0.0576801 0.0127796 33696
1 731718 rs142557973 T C 0.0292396 0.0111018 0.0084479 0.0084442 0.1236850 0.1543530 33696
1 732032 rs61770163 A C 0.0365221 0.0118196 0.0020035 0.0020018 0.1237860 0.1555510 33696
1 734349 rs141242758 T C 0.0292467 0.0111100 0.0084803 0.0084767 0.1228830 0.1525560 33696
1 740284 rs61770167 C T 0.0379452 0.0517410 0.4633392 0.4633339 0.0056776 0.0023962 33696
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0177888 0.0128859 0.1674461 0.1674372 0.0560904 0.0309934 33696
23 154923374 rs111332691 T A -0.0120901 0.0142129 0.3949726 0.3949678 0.0441299 0.0116556 33696
23 154925045 rs509981 C T 0.0074007 0.0068098 0.2771431 0.2771354 0.2441090 0.3634440 33696
23 154925895 rs538470 C T 0.0068165 0.0069601 0.3274018 0.3273946 0.2405710 0.3634440 33696
23 154927581 rs644138 G A 0.0018606 0.0063943 0.7710703 0.7710691 0.3006350 0.4635760 33696
23 154929412 rs557132 C T 0.0074602 0.0068126 0.2734973 0.2734891 0.2439390 0.3568210 33696
23 154929637 rs35185538 CT C 0.0081190 0.0071164 0.2539241 0.2539163 0.2279000 0.3011920 33696
23 154929952 rs4012982 CAA C 0.0052704 0.0071744 0.4625823 0.4625771 0.2376690 0.3165560 33696
23 154930230 rs781880 A G 0.0070151 0.0068109 0.3030268 0.3030187 0.2442850 0.3618540 33696
23 154930487 rs781879 T A -0.0324641 0.0230993 0.1599068 0.1598979 0.0196279 0.1263580 33696

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11239  ES:SE:LP:AF:SS:ID   0.0248742:0.0123669:1.35363:0.11239:33696:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117684 ES:SE:LP:AF:SS:ID   0.0318127:0.0116912:2.18639:0.117684:33696:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0990234    ES:SE:LP:AF:SS:ID   0.0321714:0.013141:1.84274:0.0990234:33696:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01573  ES:SE:LP:AF:SS:ID   0.013772:0.0316578:0.178128:0.01573:33696:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00175048   ES:SE:LP:AF:SS:ID   -0.0152511:0.092765:0.0607739:0.00175048:33696:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0576801    ES:SE:LP:AF:SS:ID   0.0290368:0.0161847:1.13782:0.0576801:33696:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123685 ES:SE:LP:AF:SS:ID   0.0292396:0.0111018:2.07325:0.123685:33696:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123786 ES:SE:LP:AF:SS:ID   0.0365221:0.0118196:2.69821:0.123786:33696:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122883 ES:SE:LP:AF:SS:ID   0.0292467:0.01111:2.07159:0.122883:33696:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00567758   ES:SE:LP:AF:SS:ID   0.0379452:0.051741:0.334101:0.00567758:33696:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00183096   ES:SE:LP:AF:SS:ID   -0.137215:0.0976496:0.795937:0.00183096:33696:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86738  ES:SE:LP:AF:SS:ID   -0.0243764:0.0109316:1.58903:0.86738:33696:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00161857   ES:SE:LP:AF:SS:ID   0.149827:0.0957596:0.929286:0.00161857:33696:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125399 ES:SE:LP:AF:SS:ID   0.0262764:0.0108249:1.81779:0.125399:33696:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145153 ES:SE:LP:AF:SS:ID   0.0267701:0.0107191:1.90259:0.145153:33696:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125554 ES:SE:LP:AF:SS:ID   0.026019:0.0108085:1.79378:0.125554:33696:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868239 ES:SE:LP:AF:SS:ID   -0.0255256:0.010547:1.80916:0.868239:33696:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872883 ES:SE:LP:AF:SS:ID   -0.0261288:0.0107095:1.83262:0.872883:33696:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131171 ES:SE:LP:AF:SS:ID   0.0260907:0.0105756:1.8656:0.131171:33696:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.03493  ES:SE:LP:AF:SS:ID   -0.000726065:0.0196965:0.012962:0.03493:33696:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867855 ES:SE:LP:AF:SS:ID   -0.0259114:0.0105376:1.85575:0.867855:33696:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867928 ES:SE:LP:AF:SS:ID   -0.0254943:0.0105426:1.80681:0.867928:33696:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867851 ES:SE:LP:AF:SS:ID   -0.0259234:0.0105373:1.85723:0.867851:33696:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00584016   ES:SE:LP:AF:SS:ID   -0.089868:0.0501871:1.13456:0.00584016:33696:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00579902   ES:SE:LP:AF:SS:ID   -0.0877565:0.0503184:1.09064:0.00579902:33696:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0056038    ES:SE:LP:AF:SS:ID   -0.083415:0.0527122:0.944798:0.0056038:33696:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.867855 ES:SE:LP:AF:SS:ID   -0.0244823:0.0105174:1.70051:0.867855:33696:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128587 ES:SE:LP:AF:SS:ID   0.0246553:0.0107189:1.66869:0.128587:33696:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867388 ES:SE:LP:AF:SS:ID   -0.0251166:0.0104888:1.77876:0.867388:33696:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866681 ES:SE:LP:AF:SS:ID   -0.024945:0.0104829:1.761:0.866681:33696:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867534 ES:SE:LP:AF:SS:ID   -0.0251392:0.0104988:1.77859:0.867534:33696:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86754  ES:SE:LP:AF:SS:ID   -0.0251432:0.0104994:1.77889:0.86754:33696:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867543 ES:SE:LP:AF:SS:ID   -0.0251429:0.0104996:1.7788:0.867543:33696:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868049 ES:SE:LP:AF:SS:ID   -0.024655:0.0105295:1.71644:0.868049:33696:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100409 ES:SE:LP:AF:SS:ID   0.0329675:0.0122424:2.14953:0.100409:33696:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00637639   ES:SE:LP:AF:SS:ID   -0.0826701:0.048271:1.06152:0.00637639:33696:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872075 ES:SE:LP:AF:SS:ID   -0.024942:0.0106806:1.70917:0.872075:33696:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86129  ES:SE:LP:AF:SS:ID   -0.0249157:0.0104828:1.75776:0.86129:33696:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866907 ES:SE:LP:AF:SS:ID   -0.0257212:0.0105881:1.82002:0.866907:33696:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863896 ES:SE:LP:AF:SS:ID   -0.0237545:0.0105872:1.60454:0.863896:33696:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100898 ES:SE:LP:AF:SS:ID   0.0321858:0.0126497:1.96053:0.100898:33696:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869067 ES:SE:LP:AF:SS:ID   -0.0244432:0.0107075:1.64883:0.869067:33696:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869067 ES:SE:LP:AF:SS:ID   -0.0244437:0.0107075:1.64889:0.869067:33696:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869064 ES:SE:LP:AF:SS:ID   -0.0244462:0.0107075:1.64915:0.869064:33696:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869379 ES:SE:LP:AF:SS:ID   -0.024911:0.0107108:1.69818:0.869379:33696:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128068 ES:SE:LP:AF:SS:ID   0.0247992:0.0107165:1.68471:0.128068:33696:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107259 ES:SE:LP:AF:SS:ID   0.0321566:0.0116539:2.23688:0.107259:33696:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852696 ES:SE:LP:AF:SS:ID   -0.0253135:0.0104635:1.80802:0.852696:33696:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00167047   ES:SE:LP:AF:SS:ID   -0.0664379:0.0931766:0.322547:0.00167047:33696:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838634 ES:SE:LP:AF:SS:ID   0.00617093:0.0104443:0.255996:0.838634:33696:rs376645387