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-41218_1/ukb-d-41218_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-41218_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 16:53:20 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-41218_1/ukb-d-41218_1.vcf.gz ...
Read summary statistics for 9676250 SNPs.
Dropped 7277 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, 1274148 SNPs remain.
After merging with regression SNP LD, 1274148 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0093 (0.5171)
Lambda GC: 1.0023
Mean Chi^2: 1.0026
Intercept: 1.0028 (0.0063)
Ratio: 1.0508 (2.3785)
Analysis finished at Mon Nov 25 16:54:55 2019
Total time elapsed: 1.0m:35.16s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9393,
    "inflation_factor": 0.9998,
    "mean_EFFECT": -0.0001,
    "n": 787,
    "n_snps": 9676250,
    "n_clumped_hits": 2,
    "n_p_sig": 3,
    "n_mono": 0,
    "n_ns": 1061530,
    "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": 192828,
    "n_est": 792.1661,
    "ratio_se_n": 1.0033,
    "mean_diff": -0.0001,
    "ratio_diff": 11.8842,
    "sd_y_est1": 0.412,
    "sd_y_est2": 0.4133,
    "r2_sum1": 0.0142,
    "r2_sum2": 0.0836,
    "r2_sum3": 0.0831,
    "r2_sum4": 0.0786,
    "ldsc_nsnp_merge_refpanel_ld": 1274148,
    "ldsc_nsnp_merge_regression_ld": 1274148,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0028,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0023,
    "ldsc_mean_chisq": 1.0026,
    "ldsc_ratio": 1.0769
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 TRUE
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 1.000000 3 94 0 9669518 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 98 0 46986 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 29624 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.077928e+00 6.174449e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.875509e+07 5.611008e+07 302.0000000 3.244853e+07 6.965733e+07 1.147591e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA -5.270000e-05 4.658440e-02 -0.4384890 -2.287140e-02 -5.877000e-04 2.192750e-02 5.639810e-01 ▁▂▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 4.051900e-02 2.304460e-02 0.0168631 2.275470e-02 3.029730e-02 5.182350e-02 1.362430e-01 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 5.000515e-01 2.885908e-01 0.0000000 2.497422e-01 5.000414e-01 7.499702e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.998421e-01 2.887167e-01 0.0000000 2.493797e-01 4.998367e-01 7.498820e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 2.622277e-01 2.629659e-01 0.0099684 4.450010e-02 1.602840e-01 4.173930e-01 9.900320e-01 ▇▂▂▁▁
numeric AF_reference 192828 0.980072 NA NA NA NA NA 2.615808e-01 2.537231e-01 0.0000000 5.031950e-02 1.753640e-01 4.125400e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.000000 NA NA NA NA NA 7.870000e+02 0.000000e+00 787.0000000 7.870000e+02 7.870000e+02 7.870000e+02 7.870000e+02 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0347786 0.0350927 0.3219771 0.3216614 0.1190220 0.1894970 787
1 693731 rs12238997 A G -0.0258593 0.0313392 0.4095510 0.4092908 0.1342730 0.1417730 787
1 707522 rs371890604 G C -0.0099114 0.0360876 0.7836624 0.7835875 0.1062460 0.1293930 787
1 717587 rs144155419 G A -0.0354496 0.0797840 0.6569374 0.6568115 0.0209632 0.0045926 787
1 730087 rs148120343 T C -0.0206253 0.0466636 0.6586156 0.6584894 0.0590602 0.0127796 787
1 731718 rs142557973 T C -0.0208348 0.0301885 0.4903058 0.4900956 0.1378300 0.1543530 787
1 732032 rs61770163 A C -0.0077494 0.0323611 0.8108070 0.8107429 0.1357230 0.1555510 787
1 734349 rs141242758 T C -0.0208969 0.0302015 0.4891995 0.4889901 0.1372870 0.1525560 787
1 749963 rs529266287 T TAA 0.0222750 0.0297963 0.4549483 0.4547159 0.8510400 0.7641770 787
1 751343 rs28544273 T A -0.0239426 0.0296102 0.4190019 0.4187493 0.1404990 0.2426120 787
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0034119 0.0391552 0.9305840 0.9305611 0.0513142 0.0309934 787
23 154923374 rs111332691 T A -0.0934921 0.0448662 0.0375120 0.0371785 0.0393901 0.0116556 787
23 154925045 rs509981 C T -0.0022569 0.0209666 0.9143061 0.9142777 0.2267480 0.3634440 787
23 154925895 rs538470 C T -0.0041160 0.0215073 0.8482831 0.8482318 0.2234250 0.3634440 787
23 154927581 rs644138 G A -0.0030495 0.0196537 0.8767369 0.8766955 0.2798740 0.4635760 787
23 154929412 rs557132 C T -0.0022795 0.0209683 0.9134591 0.9134300 0.2267310 0.3568210 787
23 154929637 rs35185538 CT C -0.0073992 0.0218161 0.7345798 0.7344860 0.2099830 0.3011920 787
23 154929952 rs4012982 CAA C -0.0030102 0.0219392 0.8909040 0.8908676 0.2225480 0.3165560 787
23 154930230 rs781880 A G -0.0019464 0.0209642 0.9260521 0.9260275 0.2272190 0.3618540 787
23 154930487 rs781879 T A 0.0321363 0.0737534 0.6631595 0.6630353 0.0163839 0.1263580 787

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.119022 ES:SE:LP:AF:SS:ID   -0.0347786:0.0350927:0.492175:0.119022:787:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.134273 ES:SE:LP:AF:SS:ID   -0.0258593:0.0313392:0.387692:0.134273:787:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.106246 ES:SE:LP:AF:SS:ID   -0.00991135:0.0360876:0.105871:0.106246:787:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0209632    ES:SE:LP:AF:SS:ID   -0.0354496:0.079784:0.182476:0.0209632:787:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0590602    ES:SE:LP:AF:SS:ID   -0.0206253:0.0466636:0.181368:0.0590602:787:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.13783  ES:SE:LP:AF:SS:ID   -0.0208348:0.0301885:0.309533:0.13783:787:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.135723 ES:SE:LP:AF:SS:ID   -0.00774944:0.0323611:0.0910825:0.135723:787:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.137287 ES:SE:LP:AF:SS:ID   -0.0208969:0.0302015:0.310514:0.137287:787:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.85104  ES:SE:LP:AF:SS:ID   0.022275:0.0297963:0.342038:0.85104:787:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.140499 ES:SE:LP:AF:SS:ID   -0.0239426:0.0296102:0.377784:0.140499:787:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.159287 ES:SE:LP:AF:SS:ID   -0.0300773:0.0296061:0.508647:0.159287:787:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.140549 ES:SE:LP:AF:SS:ID   -0.0241421:0.0295883:0.382168:0.140549:787:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.851865 ES:SE:LP:AF:SS:ID   0.0215509:0.0287203:0.34365:0.851865:787:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.856646 ES:SE:LP:AF:SS:ID   0.0279658:0.0292636:0.469095:0.856646:787:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.146835 ES:SE:LP:AF:SS:ID   -0.0187764:0.0288121:0.288359:0.146835:787:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0336722    ES:SE:LP:AF:SS:ID   0.0539616:0.05877:0.445129:0.0336722:787:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.851145 ES:SE:LP:AF:SS:ID   0.0221928:0.0286849:0.357177:0.851145:787:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.851142 ES:SE:LP:AF:SS:ID   0.0222121:0.0286859:0.357553:0.851142:787:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.851145 ES:SE:LP:AF:SS:ID   0.0222755:0.0286848:0.358863:0.851145:787:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.8527   ES:SE:LP:AF:SS:ID   0.0250611:0.0286826:0.417325:0.8527:787:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.142512 ES:SE:LP:AF:SS:ID   -0.0239324:0.0293808:0.381345:0.142512:787:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.852605 ES:SE:LP:AF:SS:ID   0.0251445:0.0286617:0.419522:0.852605:787:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.851379 ES:SE:LP:AF:SS:ID   0.0259548:0.0286415:0.437564:0.851379:787:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.852622 ES:SE:LP:AF:SS:ID   0.0251135:0.0286657:0.418776:0.852622:787:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.852625 ES:SE:LP:AF:SS:ID   0.0251624:0.0286678:0.419793:0.852625:787:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.852635 ES:SE:LP:AF:SS:ID   0.0251448:0.0286666:0.419435:0.852635:787:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.852822 ES:SE:LP:AF:SS:ID   0.0249307:0.028711:0.413991:0.852822:787:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.113895 ES:SE:LP:AF:SS:ID   -0.0261398:0.0329329:0.368961:0.113895:787:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.855781 ES:SE:LP:AF:SS:ID   0.027204:0.0291521:0.454662:0.855781:787:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.846805 ES:SE:LP:AF:SS:ID   0.0213818:0.0287109:0.3404:0.846805:787:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.850111 ES:SE:LP:AF:SS:ID   0.0250381:0.0287378:0.415797:0.850111:787:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.849127 ES:SE:LP:AF:SS:ID   0.0222642:0.0289439:0.354575:0.849127:787:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.113504 ES:SE:LP:AF:SS:ID   -0.0316681:0.0345567:0.444008:0.113504:787:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.853071 ES:SE:LP:AF:SS:ID   0.02184:0.0292592:0.341381:0.853071:787:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.853071 ES:SE:LP:AF:SS:ID   0.02184:0.0292592:0.341381:0.853071:787:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.853066 ES:SE:LP:AF:SS:ID   0.0218309:0.0292594:0.341199:0.853066:787:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.853108 ES:SE:LP:AF:SS:ID   0.0217595:0.0292569:0.339833:0.853108:787:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.143371 ES:SE:LP:AF:SS:ID   -0.0228378:0.0292564:0.361235:0.143371:787:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.116611 ES:SE:LP:AF:SS:ID   -0.0327739:0.0313873:0.527631:0.116611:787:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.835683 ES:SE:LP:AF:SS:ID   0.0209219:0.0286439:0.332209:0.835683:787:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838423 ES:SE:LP:AF:SS:ID   0.0641132:0.0299266:1.48835:0.838423:787:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.756016 ES:SE:LP:AF:SS:ID   0.0499882:0.0231003:1.51176:0.756016:787:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.0946633    ES:SE:LP:AF:SS:ID   -0.0846253:0.0348436:1.81295:0.0946633:787:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.146456 ES:SE:LP:AF:SS:ID   -0.0217757:0.0288748:0.345825:0.146456:787:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.145983 ES:SE:LP:AF:SS:ID   -0.0197516:0.0288622:0.3063:0.145983:787:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.0941226    ES:SE:LP:AF:SS:ID   -0.0843976:0.0350917:1.78494:0.0941226:787:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.093288 ES:SE:LP:AF:SS:ID   -0.0847443:0.0354701:1.76626:0.093288:787:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.810277 ES:SE:LP:AF:SS:ID   0.0294307:0.0283732:0.522966:0.810277:787:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.851765 ES:SE:LP:AF:SS:ID   0.0229388:0.0287018:0.372207:0.851765:787:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.146102 ES:SE:LP:AF:SS:ID   -0.0195747:0.0288371:0.303234:0.146102:787:rs59066358