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-2877_1/ukb-d-2877_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-2877_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 16:40:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-2877_1/ukb-d-2877_1.vcf.gz ...
Read summary statistics for 13566556 SNPs.
Dropped 12681 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, 1283499 SNPs remain.
After merging with regression SNP LD, 1283499 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0155 (0.0049)
Lambda GC: 1.0325
Mean Chi^2: 1.034
Intercept: 1.007 (0.006)
Ratio: 0.2059 (0.1772)
Analysis finished at Mon Nov 25 16:42:59 2019
Total time elapsed: 2.0m:26.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0293,
    "mean_EFFECT": -1.9011e-06,
    "n": 89224,
    "n_snps": 13566556,
    "n_clumped_hits": 1,
    "n_p_sig": 4,
    "n_mono": 0,
    "n_ns": 1251062,
    "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": 564688,
    "n_est": 89716.5121,
    "ratio_se_n": 1.0028,
    "mean_diff": -4.2714e-06,
    "ratio_diff": 83.6362,
    "sd_y_est1": 0.3097,
    "sd_y_est2": 0.3106,
    "r2_sum1": 0,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1283499,
    "ldsc_nsnp_merge_regression_ld": 1283499,
    "ldsc_observed_scale_h2_beta": 0.0155,
    "ldsc_observed_scale_h2_se": 0.0049,
    "ldsc_intercept_beta": 1.007,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0325,
    "ldsc_mean_chisq": 1.034,
    "ldsc_ratio": 0.2059
}

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 13554539 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57047 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33330 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051357e+00 6.184817e+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 7.902633e+07 5.591361e+07 3.02000e+02 3.292996e+07 7.014335e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.900000e-06 8.551500e-03 -1.18045e-01 -2.269300e-03 1.790000e-05 2.318700e-03 9.564080e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 6.136800e-03 5.916500e-03 1.17020e-03 1.753800e-03 3.223900e-03 8.805600e-03 3.053030e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.952060e-01 2.901229e-01 0.00000e+00 2.425208e-01 4.937885e-01 7.467221e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.952042e-01 2.901240e-01 0.00000e+00 2.425183e-01 4.937870e-01 7.467209e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910586e-01 2.544574e-01 1.00000e-03 7.500600e-03 6.032630e-02 2.957970e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 564688 0.9583765 NA NA NA NA NA 1.965258e-01 2.471417e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.922400e+04 0.000000e+00 8.92240e+04 8.922400e+04 8.922400e+04 8.922400e+04 8.922400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0006261 0.0025718 0.8076500 0.8076500 0.1101140 0.1894970 89224
1 693731 rs12238997 A G -0.0008191 0.0024345 0.7365394 0.7365373 0.1152820 0.1417730 89224
1 707522 rs371890604 G C -0.0021876 0.0027375 0.4242208 0.4242185 0.0969534 0.1293930 89224
1 717587 rs144155419 G A 0.0137009 0.0064614 0.0339719 0.0339693 0.0158030 0.0045926 89224
1 723329 rs189787166 A T -0.0013392 0.0195609 0.9454170 0.9454170 0.0016838 0.0003994 89224
1 730087 rs148120343 T C -0.0040140 0.0034119 0.2394131 0.2394110 0.0557130 0.0127796 89224
1 731718 rs142557973 T C 0.0001798 0.0023048 0.9378170 0.9378171 0.1214630 0.1543530 89224
1 732032 rs61770163 A C 0.0000904 0.0024614 0.9706950 0.9706946 0.1206730 0.1555510 89224
1 734349 rs141242758 T C 0.0000323 0.0023061 0.9888160 0.9888156 0.1206850 0.1525560 89224
1 740284 rs61770167 C T -0.0025269 0.0103751 0.8075801 0.8075798 0.0060019 0.0023962 89224
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0019540 0.0025814 0.4490865 0.4490834 0.0560976 0.0309934 89224
23 154923374 rs111332691 T A 0.0028749 0.0028437 0.3120233 0.3120199 0.0447525 0.0116556 89224
23 154925045 rs509981 C T 0.0012505 0.0013633 0.3590153 0.3590130 0.2467730 0.3634440 89224
23 154925895 rs538470 C T 0.0009593 0.0013955 0.4917847 0.4917820 0.2427240 0.3634440 89224
23 154927581 rs644138 G A 0.0016617 0.0012824 0.1950639 0.1950605 0.3032430 0.4635760 89224
23 154929412 rs557132 C T 0.0012373 0.0013636 0.3641816 0.3641808 0.2466620 0.3568210 89224
23 154929637 rs35185538 CT C 0.0012607 0.0014228 0.3755658 0.3755632 0.2308240 0.3011920 89224
23 154929952 rs4012982 CAA C 0.0015003 0.0014342 0.2955357 0.2955337 0.2404830 0.3165560 89224
23 154930230 rs781880 A G 0.0012977 0.0013636 0.3412848 0.3412814 0.2469950 0.3618540 89224
23 154930487 rs781879 T A -0.0041112 0.0046562 0.3772628 0.3772606 0.0195810 0.1263580 89224

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110114 ES:SE:LP:AF:SS:ID   -0.000626125:0.00257179:0.0927768:0.110114:89224:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115282 ES:SE:LP:AF:SS:ID   -0.000819069:0.0024345:0.132804:0.115282:89224:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0969534    ES:SE:LP:AF:SS:ID   -0.00218761:0.00273751:0.372408:0.0969534:89224:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015803 ES:SE:LP:AF:SS:ID   0.0137009:0.00646136:1.46888:0.015803:89224:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00168376   ES:SE:LP:AF:SS:ID   -0.0013392:0.0195609:0.0243766:0.00168376:89224:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.055713 ES:SE:LP:AF:SS:ID   -0.004014:0.00341193:0.620852:0.055713:89224:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121463 ES:SE:LP:AF:SS:ID   0.000179806:0.0023048:0.0278819:0.121463:89224:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.120673 ES:SE:LP:AF:SS:ID   9.04258e-05:0.00246143:0.0129172:0.120673:89224:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120685 ES:SE:LP:AF:SS:ID   3.23273e-05:0.00230613:0.00488451:0.120685:89224:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0060019    ES:SE:LP:AF:SS:ID   -0.00252685:0.0103751:0.0928144:0.0060019:89224:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187068   ES:SE:LP:AF:SS:ID   0.00683734:0.0199589:0.135535:0.00187068:89224:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869949 ES:SE:LP:AF:SS:ID   0.000217237:0.00227272:0.0343981:0.869949:89224:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00150826   ES:SE:LP:AF:SS:ID   0.000652095:0.0207656:0.0110185:0.00150826:89224:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12264  ES:SE:LP:AF:SS:ID   -0.000547424:0.00225224:0.0926096:0.12264:89224:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142987 ES:SE:LP:AF:SS:ID   -0.000187098:0.00222436:0.0301337:0.142987:89224:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.122753 ES:SE:LP:AF:SS:ID   -0.000551001:0.00224913:0.0934123:0.122753:89224:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.871046 ES:SE:LP:AF:SS:ID   -0.000283777:0.0021902:0.0472516:0.871046:89224:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875755 ES:SE:LP:AF:SS:ID   0.000280537:0.0022279:0.0458564:0.875755:89224:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128567 ES:SE:LP:AF:SS:ID   0.000136104:0.00219524:0.0220191:0.128567:89224:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0362739    ES:SE:LP:AF:SS:ID   -0.000658695:0.00398493:0.0611247:0.0362739:89224:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870584 ES:SE:LP:AF:SS:ID   -0.000240453:0.00218762:0.0397781:0.870584:89224:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870694 ES:SE:LP:AF:SS:ID   -0.000219471:0.00218857:0.0361546:0.870694:89224:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87059  ES:SE:LP:AF:SS:ID   -0.000270569:0.00218766:0.045001:0.87059:89224:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00498758   ES:SE:LP:AF:SS:ID   -0.00446191:0.0113016:0.159274:0.00498758:89224:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00495299   ES:SE:LP:AF:SS:ID   -0.00452194:0.0113315:0.161245:0.00495299:89224:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00547252   ES:SE:LP:AF:SS:ID   0.0145276:0.0110293:0.726348:0.00547252:89224:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870757 ES:SE:LP:AF:SS:ID   -0.000420123:0.00218394:0.0718844:0.870757:89224:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125878 ES:SE:LP:AF:SS:ID   -0.000249024:0.00222742:0.0404897:0.125878:89224:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870304 ES:SE:LP:AF:SS:ID   -0.000385906:0.00217776:0.0658304:0.870304:89224:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869591 ES:SE:LP:AF:SS:ID   -0.000316443:0.00217657:0.0533483:0.869591:89224:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870467 ES:SE:LP:AF:SS:ID   -0.00037142:0.00218021:0.0631205:0.870467:89224:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870473 ES:SE:LP:AF:SS:ID   -0.000371406:0.00218037:0.0631129:0.870473:89224:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87048  ES:SE:LP:AF:SS:ID   -0.000394966:0.00218044:0.0673959:0.87048:89224:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870913 ES:SE:LP:AF:SS:ID   -0.000362602:0.00218624:0.0613447:0.870913:89224:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988102    ES:SE:LP:AF:SS:ID   -0.00246989:0.00254303:0.479607:0.0988102:89224:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00635859   ES:SE:LP:AF:SS:ID   0.00959112:0.00991349:0.477157:0.00635859:89224:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874915 ES:SE:LP:AF:SS:ID   0.0001425:0.00222036:0.0228125:0.874915:89224:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864311 ES:SE:LP:AF:SS:ID   -0.000465554:0.00217708:0.0805715:0.864311:89224:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869632 ES:SE:LP:AF:SS:ID   5.29305e-05:0.00219741:0.00842707:0.869632:89224:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866681 ES:SE:LP:AF:SS:ID   -0.000258589:0.00219732:0.0427194:0.866681:89224:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0985183    ES:SE:LP:AF:SS:ID   -0.000247896:0.00263405:0.0338489:0.0985183:89224:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871829 ES:SE:LP:AF:SS:ID   0.000208973:0.00222289:0.0338104:0.871829:89224:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871828 ES:SE:LP:AF:SS:ID   0.000208757:0.00222289:0.0337742:0.871828:89224:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871826 ES:SE:LP:AF:SS:ID   0.00020907:0.0022229:0.0338268:0.871826:89224:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.872196 ES:SE:LP:AF:SS:ID   0.00025903:0.00222438:0.042251:0.872196:89224:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125335 ES:SE:LP:AF:SS:ID   -0.000235555:0.00222678:0.0382207:0.125335:89224:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105208 ES:SE:LP:AF:SS:ID   -0.00191245:0.00242514:0.366177:0.105208:89224:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855765 ES:SE:LP:AF:SS:ID   0.000450118:0.00217796:0.0776545:0.855765:89224:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00161047   ES:SE:LP:AF:SS:ID   -0.00103823:0.0195956:0.0187497:0.00161047:89224:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837613 ES:SE:LP:AF:SS:ID   0.0025555:0.00213558:0.635537:0.837613:89224:rs376645387