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-20406/ukb-d-20406.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-20406/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 17:17:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20406/ukb-d-20406.vcf.gz ...
Read summary statistics for 11012886 SNPs.
Dropped 9090 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, 1281852 SNPs remain.
After merging with regression SNP LD, 1281852 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1823 (0.0717)
Lambda GC: 1.0165
Mean Chi^2: 1.0234
Intercept: 1.0001 (0.0065)
Ratio: 0.0034 (0.2789)
Analysis finished at Mon Nov 25 17:19:23 2019
Total time elapsed: 2.0m:9.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9459,
    "inflation_factor": 1.0148,
    "mean_EFFECT": 0.0001,
    "n": 6514,
    "n_snps": 11012886,
    "n_clumped_hits": 3,
    "n_p_sig": 4,
    "n_mono": 0,
    "n_ns": 1138458,
    "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": 221472,
    "n_est": 6559.2755,
    "ratio_se_n": 1.0035,
    "mean_diff": 0.0001,
    "ratio_diff": 29.6048,
    "sd_y_est1": 0.4918,
    "sd_y_est2": 0.4935,
    "r2_sum1": 0.0041,
    "r2_sum2": 0.017,
    "r2_sum3": 0.0169,
    "r2_sum4": 0.0159,
    "ldsc_nsnp_merge_refpanel_ld": 1281852,
    "ldsc_nsnp_merge_regression_ld": 1281852,
    "ldsc_observed_scale_h2_beta": 0.1823,
    "ldsc_observed_scale_h2_se": 0.0717,
    "ldsc_intercept_beta": 1.0001,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0165,
    "ldsc_mean_chisq": 1.0234,
    "ldsc_ratio": 0.0043
}

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 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 11004381 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 51117 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31311 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.074969e+00 6.181341e+00 1.0000000 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 7.882196e+07 5.602209e+07 302.0000000 3.260080e+07 6.979774e+07 1.147373e+08 2.492309e+08 <U+2587><U+2586><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.075000e-04 2.654810e-02 -0.2961930 -1.050260e-02 3.910000e-05 1.059230e-02 3.132150e-01 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.0000000 NA NA NA NA NA 2.145090e-02 1.555260e-02 0.0069093 9.695500e-03 1.418240e-02 2.869600e-02 9.283870e-02 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.975735e-01 2.898493e-01 0.0000000 2.458708e-01 4.968382e-01 7.487141e-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 4.975489e-01 2.898640e-01 0.0000000 2.458290e-01 4.968133e-01 7.487037e-01 9.999998e-01 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric AF 0 1.0000000 NA NA NA NA NA 2.327990e-01 2.617881e-01 0.0044998 2.424130e-02 1.182150e-01 3.725200e-01 9.955000e-01 <U+2587><U+2582><U+2582><U+2581><U+2581>
numeric AF_reference 221472 0.9798897 NA NA NA NA NA 2.330481e-01 2.528816e-01 0.0000000 2.296330e-02 1.357830e-01 3.710060e-01 1.000000e+00 <U+2587><U+2582><U+2582><U+2581><U+2581>
numeric N 0 1.0000000 NA NA NA NA NA 6.514000e+03 0.000000e+00 6514.0000000 6.514000e+03 6.514000e+03 6.514000e+03 6.514000e+03 <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 0.0127497 0.0153030 0.4047911 0.4047599 0.1095770 0.1894970 6514
1 693731 rs12238997 A G 0.0266123 0.0143608 0.0639102 0.0638650 0.1161230 0.1417730 6514
1 707522 rs371890604 G C 0.0306755 0.0162049 0.0584050 0.0583610 0.0981027 0.1293930 6514
1 717587 rs144155419 G A -0.0182436 0.0384685 0.6353397 0.6353232 0.0154735 0.0045926 6514
1 730087 rs148120343 T C 0.0122159 0.0200084 0.5415256 0.5415051 0.0570476 0.0127796 6514
1 731718 rs142557973 T C 0.0194729 0.0135989 0.1522089 0.1521591 0.1225630 0.1543530 6514
1 732032 rs61770163 A C 0.0234218 0.0145708 0.1080050 0.1079562 0.1217030 0.1555510 6514
1 734349 rs141242758 T C 0.0210028 0.0135999 0.1225561 0.1225072 0.1217990 0.1525560 6514
1 740284 rs61770167 C T 0.1417730 0.0632355 0.0249960 0.0249624 0.0054438 0.0023962 6514
1 749963 rs529266287 T TAA -0.0172967 0.0133737 0.1959400 0.1958946 0.8682550 0.7641770 6514
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0039177 0.0153509 0.7985691 0.7985611 0.0567794 0.0309934 6514
23 154923374 rs111332691 T A -0.0097587 0.0169305 0.5643662 0.5643464 0.0439822 0.0116556 6514
23 154925045 rs509981 C T -0.0017207 0.0081003 0.8317810 0.8317749 0.2452700 0.3634440 6514
23 154925895 rs538470 C T -0.0038565 0.0082642 0.6407668 0.6407510 0.2423620 0.3634440 6514
23 154927581 rs644138 G A -0.0004684 0.0076365 0.9510880 0.9510859 0.3023240 0.4635760 6514
23 154929412 rs557132 C T -0.0018394 0.0081007 0.8203789 0.8203714 0.2452050 0.3568210 6514
23 154929637 rs35185538 CT C -0.0021870 0.0084532 0.7958600 0.7958519 0.2308700 0.3011920 6514
23 154929952 rs4012982 CAA C -0.0035196 0.0085232 0.6796605 0.6796474 0.2401290 0.3165560 6514
23 154930230 rs781880 A G -0.0032320 0.0080995 0.6898823 0.6898687 0.2458890 0.3618540 6514
23 154930487 rs781879 T A 0.0023464 0.0268041 0.9302460 0.9302432 0.0205404 0.1263580 6514

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.109577 ES:SE:LP:AF:SS:ID   0.0127497:0.015303:0.392769:0.109577:6514:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116123 ES:SE:LP:AF:SS:ID   0.0266123:0.0143608:1.19443:0.116123:6514:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981027    ES:SE:LP:AF:SS:ID   0.0306755:0.0162049:1.23355:0.0981027:6514:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154735    ES:SE:LP:AF:SS:ID   -0.0182436:0.0384685:0.196994:0.0154735:6514:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0570476    ES:SE:LP:AF:SS:ID   0.0122159:0.0200084:0.266381:0.0570476:6514:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122563 ES:SE:LP:AF:SS:ID   0.0194729:0.0135989:0.81756:0.122563:6514:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121703 ES:SE:LP:AF:SS:ID   0.0234218:0.0145708:0.966556:0.121703:6514:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121799 ES:SE:LP:AF:SS:ID   0.0210028:0.0135999:0.911665:0.121799:6514:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00544378   ES:SE:LP:AF:SS:ID   0.141773:0.0632355:1.60213:0.00544378:6514:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868255 ES:SE:LP:AF:SS:ID   -0.0172967:0.0133737:0.707877:0.868255:6514:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123785 ES:SE:LP:AF:SS:ID   0.016901:0.013296:0.690949:0.123785:6514:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143445 ES:SE:LP:AF:SS:ID   0.0174068:0.0131476:0.731506:0.143445:6514:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12391  ES:SE:LP:AF:SS:ID   0.0162694:0.0132762:0.656692:0.12391:6514:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868987 ES:SE:LP:AF:SS:ID   -0.0175734:0.0128713:0.763969:0.868987:6514:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873698 ES:SE:LP:AF:SS:ID   -0.0146792:0.0130994:0.580872:0.873698:6514:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130511 ES:SE:LP:AF:SS:ID   0.0188968:0.0129078:0.843917:0.130511:6514:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0356924    ES:SE:LP:AF:SS:ID   0.0165545:0.0236316:0.315491:0.0356924:6514:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86848  ES:SE:LP:AF:SS:ID   -0.0183793:0.0128533:0.815916:0.86848:6514:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868467 ES:SE:LP:AF:SS:ID   -0.0183574:0.012853:0.814554:0.868467:6514:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868464 ES:SE:LP:AF:SS:ID   -0.0183496:0.0128523:0.814124:0.868464:6514:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00540946   ES:SE:LP:AF:SS:ID   -0.0237081:0.063401:0.149683:0.00540946:6514:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00538538   ES:SE:LP:AF:SS:ID   -0.0239237:0.0634951:0.15098:0.00538538:6514:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00620353   ES:SE:LP:AF:SS:ID   -0.0553401:0.0603336:0.444841:0.00620353:6514:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868631 ES:SE:LP:AF:SS:ID   -0.0182681:0.0128353:0.81049:0.868631:6514:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127611 ES:SE:LP:AF:SS:ID   0.0196406:0.0131311:0.870397:0.127611:6514:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868207 ES:SE:LP:AF:SS:ID   -0.0186643:0.0127996:0.839123:0.868207:6514:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867678 ES:SE:LP:AF:SS:ID   -0.0188518:0.0128093:0.850347:0.867678:6514:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868361 ES:SE:LP:AF:SS:ID   -0.0186197:0.0128163:0.834684:0.868361:6514:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868365 ES:SE:LP:AF:SS:ID   -0.0186324:0.0128168:0.835454:0.868365:6514:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868369 ES:SE:LP:AF:SS:ID   -0.0186353:0.0128172:0.835608:0.868369:6514:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868662 ES:SE:LP:AF:SS:ID   -0.0181433:0.012839:0.802276:0.868662:6514:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0993158    ES:SE:LP:AF:SS:ID   0.0345053:0.0151153:1.64832:0.0993158:6514:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00708549   ES:SE:LP:AF:SS:ID   -0.0449087:0.0548469:0.384124:0.00708549:6514:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872836 ES:SE:LP:AF:SS:ID   -0.0166381:0.0130435:0.694335:0.872836:6514:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862443 ES:SE:LP:AF:SS:ID   -0.0206942:0.0128053:0.97417:0.862443:6514:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868146 ES:SE:LP:AF:SS:ID   -0.0183093:0.0129304:0.804574:0.868146:6514:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864057 ES:SE:LP:AF:SS:ID   -0.0188815:0.0129245:0.841366:0.864057:6514:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100049 ES:SE:LP:AF:SS:ID   0.031351:0.0154374:1.37354:0.100049:6514:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869474 ES:SE:LP:AF:SS:ID   -0.0172746:0.0130864:0.72847:0.869474:6514:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869474 ES:SE:LP:AF:SS:ID   -0.0172746:0.0130864:0.72847:0.869474:6514:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.86947  ES:SE:LP:AF:SS:ID   -0.017276:0.0130864:0.728546:0.86947:6514:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869953 ES:SE:LP:AF:SS:ID   -0.0188024:0.0130925:0.820977:0.869953:6514:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127327 ES:SE:LP:AF:SS:ID   0.0177639:0.0130959:0.756952:0.127327:6514:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10682  ES:SE:LP:AF:SS:ID   0.0298773:0.0142688:1.44:0.10682:6514:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852749 ES:SE:LP:AF:SS:ID   -0.017852:0.0127598:0.790925:0.852749:6514:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839216 ES:SE:LP:AF:SS:ID   0.0254883:0.0127111:1.34696:0.839216:6514:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763121 ES:SE:LP:AF:SS:ID   -0.00384824:0.0102396:0.150542:0.763121:6514:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.104544 ES:SE:LP:AF:SS:ID   -0.0166861:0.0141523:0.622648:0.104544:6514:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00743647   ES:SE:LP:AF:SS:ID   0.0730828:0.0533022:0.768553:0.00743647:6514:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.130855 ES:SE:LP:AF:SS:ID   0.0203872:0.0129167:0.941073:0.130855:6514:rs762168062