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-6020_1/ukb-d-6020_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-6020_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 16:53:27 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-6020_1/ukb-d-6020_1.vcf.gz ...
Read summary statistics for 13546752 SNPs.
Dropped 12656 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, 1283498 SNPs remain.
After merging with regression SNP LD, 1283498 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0188 (0.0089)
Lambda GC: 1.0226
Mean Chi^2: 1.0228
Intercept: 1.0028 (0.0061)
Ratio: 0.1219 (0.2649)
Analysis finished at Mon Nov 25 16:55:33 2019
Total time elapsed: 2.0m:6.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0144,
    "mean_EFFECT": 0,
    "n": 54007,
    "n_snps": 13546752,
    "n_clumped_hits": 0,
    "n_p_sig": 5,
    "n_mono": 0,
    "n_ns": 1250464,
    "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": 557510,
    "n_est": 54247.0626,
    "ratio_se_n": 1.0022,
    "mean_diff": 0.0001,
    "ratio_diff": 79.3807,
    "sd_y_est1": 0.254,
    "sd_y_est2": 0.2546,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283498,
    "ldsc_nsnp_merge_regression_ld": 1283498,
    "ldsc_observed_scale_h2_beta": 0.0188,
    "ldsc_observed_scale_h2_se": 0.0089,
    "ldsc_intercept_beta": 1.0028,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0226,
    "ldsc_mean_chisq": 1.0228,
    "ldsc_ratio": 0.1228
}

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 13534759 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57009 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33321 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051305e+00 6.184716e+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 7.902416e+07 5.591837e+07 3.02000e+02 3.292440e+07 7.013507e+07 1.148590e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.520000e-05 8.939500e-03 -1.29538e-01 -2.313700e-03 4.830000e-05 2.466400e-03 1.063260e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 6.441600e-03 6.200400e-03 1.26810e-03 1.847100e-03 3.390200e-03 9.244900e-03 3.215730e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.977835e-01 2.885550e-01 0.00000e+00 2.478928e-01 4.969263e-01 7.471314e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.977805e-01 2.885568e-01 0.00000e+00 2.478882e-01 4.969231e-01 7.471310e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913418e-01 2.545288e-01 1.00000e-03 7.582300e-03 6.066450e-02 2.963370e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557510 0.9588455 NA NA NA NA NA 1.967195e-01 2.471864e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.400700e+04 0.000000e+00 5.40070e+04 5.400700e+04 5.400700e+04 5.400700e+04 5.400700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0020191 0.0026920 0.4532387 0.4532374 0.1121030 0.1894970 54007
1 693731 rs12238997 A G -0.0025711 0.0025523 0.3137632 0.3137590 0.1170180 0.1417730 54007
1 707522 rs371890604 G C -0.0068901 0.0028632 0.0161139 0.0161105 0.0983620 0.1293930 54007
1 717587 rs144155419 G A 0.0073947 0.0069460 0.2870668 0.2870625 0.0154496 0.0045926 54007
1 723329 rs189787166 A T -0.0222785 0.0196856 0.2577579 0.2577540 0.0017767 0.0003994 54007
1 730087 rs148120343 T C -0.0048655 0.0035549 0.1711039 0.1710973 0.0570868 0.0127796 54007
1 731718 rs142557973 T C -0.0030059 0.0024216 0.2144920 0.2144862 0.1229180 0.1543530 54007
1 732032 rs61770163 A C -0.0035712 0.0025785 0.1660600 0.1660537 0.1226450 0.1555510 54007
1 734349 rs141242758 T C -0.0030220 0.0024240 0.2125128 0.2125084 0.1220820 0.1525560 54007
1 740284 rs61770167 C T 0.0123905 0.0103302 0.2303600 0.2303552 0.0066240 0.0023962 54007
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0004850 0.0028428 0.8645460 0.8645455 0.0543009 0.0309934 54007
23 154923374 rs111332691 T A -0.0003549 0.0030863 0.9084629 0.9084628 0.0443554 0.0116556 54007
23 154925045 rs509981 C T 0.0010783 0.0014853 0.4678482 0.4678450 0.2425480 0.3634440 54007
23 154925895 rs538470 C T 0.0011091 0.0015185 0.4651468 0.4651456 0.2390400 0.3634440 54007
23 154927581 rs644138 G A 0.0007773 0.0013968 0.5778618 0.5778605 0.2972530 0.4635760 54007
23 154929412 rs557132 C T 0.0010761 0.0014859 0.4689267 0.4689222 0.2423940 0.3568210 54007
23 154929637 rs35185538 CT C 0.0020024 0.0015511 0.1967420 0.1967370 0.2266820 0.3011920 54007
23 154929952 rs4012982 CAA C 0.0014098 0.0015610 0.3664561 0.3664500 0.2367690 0.3165560 54007
23 154930230 rs781880 A G 0.0011721 0.0014854 0.4300906 0.4300861 0.2428410 0.3618540 54007
23 154930487 rs781879 T A 0.0036612 0.0051880 0.4803823 0.4803791 0.0187227 0.1263580 54007

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112103 ES:SE:LP:AF:SS:ID   -0.0020191:0.00269203:0.343673:0.112103:54007:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117018 ES:SE:LP:AF:SS:ID   -0.00257114:0.00255234:0.503398:0.117018:54007:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098362 ES:SE:LP:AF:SS:ID   -0.00689006:0.00286322:1.7928:0.098362:54007:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154496    ES:SE:LP:AF:SS:ID   0.00739468:0.00694605:0.542017:0.0154496:54007:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177671   ES:SE:LP:AF:SS:ID   -0.0222785:0.0196856:0.588788:0.00177671:54007:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570868    ES:SE:LP:AF:SS:ID   -0.00486553:0.00355489:0.76674:0.0570868:54007:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122918 ES:SE:LP:AF:SS:ID   -0.00300594:0.00242156:0.668589:0.122918:54007:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122645 ES:SE:LP:AF:SS:ID   -0.00357124:0.00257852:0.779735:0.122645:54007:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122082 ES:SE:LP:AF:SS:ID   -0.00302202:0.00242402:0.672615:0.122082:54007:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00662398   ES:SE:LP:AF:SS:ID   0.0123905:0.0103302:0.637593:0.00662398:54007:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00186766   ES:SE:LP:AF:SS:ID   0.00475187:0.0213167:0.0842837:0.00186766:54007:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868461 ES:SE:LP:AF:SS:ID   0.00257928:0.00238864:0.552484:0.868461:54007:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00154987   ES:SE:LP:AF:SS:ID   -0.00375038:0.021634:0.0643049:0.00154987:54007:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124098 ES:SE:LP:AF:SS:ID   -0.00335045:0.002366:0.804773:0.124098:54007:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143405 ES:SE:LP:AF:SS:ID   -0.00312928:0.00234726:0.738778:0.143405:54007:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124231 ES:SE:LP:AF:SS:ID   -0.00333052:0.00236219:0.799787:0.124231:54007:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869563 ES:SE:LP:AF:SS:ID   0.00320174:0.00230083:0.784995:0.869563:54007:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874342 ES:SE:LP:AF:SS:ID   0.00315002:0.00233945:0.749202:0.874342:54007:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12998  ES:SE:LP:AF:SS:ID   -0.0033903:0.00230609:0.849164:0.12998:54007:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0364212    ES:SE:LP:AF:SS:ID   -0.000113236:0.00419047:0.00946491:0.0364212:54007:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8692   ES:SE:LP:AF:SS:ID   0.00320785:0.00229892:0.788055:0.8692:54007:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869321 ES:SE:LP:AF:SS:ID   0.00328072:0.00230036:0.812976:0.869321:54007:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869211 ES:SE:LP:AF:SS:ID   0.00320877:0.00229884:0.788415:0.869211:54007:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00522899   ES:SE:LP:AF:SS:ID   -0.020296:0.0116409:1.09018:0.00522899:54007:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00519954   ES:SE:LP:AF:SS:ID   -0.0205778:0.0116714:1.10853:0.00519954:54007:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00560715   ES:SE:LP:AF:SS:ID   0.023803:0.0114388:1.42657:0.00560715:54007:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869334 ES:SE:LP:AF:SS:ID   0.00299501:0.00229526:0.716828:0.869334:54007:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127255 ES:SE:LP:AF:SS:ID   -0.00341818:0.00234163:0.840532:0.127255:54007:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868934 ES:SE:LP:AF:SS:ID   0.0030038:0.00229011:0.722054:0.868934:54007:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86804  ES:SE:LP:AF:SS:ID   0.00309779:0.00228673:0.755661:0.86804:54007:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869085 ES:SE:LP:AF:SS:ID   0.00299473:0.00229188:0.718215:0.869085:54007:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869091 ES:SE:LP:AF:SS:ID   0.00299659:0.00229203:0.718773:0.869091:54007:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8691   ES:SE:LP:AF:SS:ID   0.00299604:0.00229212:0.718553:0.8691:54007:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869495 ES:SE:LP:AF:SS:ID   0.00297668:0.00229778:0.709594:0.869495:54007:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0998575    ES:SE:LP:AF:SS:ID   -0.00425915:0.00266774:0.957133:0.0998575:54007:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00638995   ES:SE:LP:AF:SS:ID   0.0189857:0.010386:1.17035:0.00638995:54007:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87353  ES:SE:LP:AF:SS:ID   0.00322583:0.00233263:0.778075:0.87353:54007:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862691 ES:SE:LP:AF:SS:ID   0.00331814:0.00228678:0.833324:0.862691:54007:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868349 ES:SE:LP:AF:SS:ID   0.00307063:0.00231078:0.735392:0.868349:54007:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864973 ES:SE:LP:AF:SS:ID   0.00282116:0.00230873:0.654174:0.864973:54007:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997018    ES:SE:LP:AF:SS:ID   -0.00259146:0.00276452:0.457726:0.0997018:54007:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870319 ES:SE:LP:AF:SS:ID   0.00345659:0.00233549:0.857385:0.870319:54007:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870319 ES:SE:LP:AF:SS:ID   0.00345655:0.00233549:0.857373:0.870319:54007:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870316 ES:SE:LP:AF:SS:ID   0.003457:0.0023355:0.857526:0.870316:54007:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870734 ES:SE:LP:AF:SS:ID   0.00345586:0.00233712:0.856261:0.870734:54007:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.1267   ES:SE:LP:AF:SS:ID   -0.00351148:0.00233883:0.87529:0.1267:54007:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106448 ES:SE:LP:AF:SS:ID   -0.00396348:0.00254488:0.92309:0.106448:54007:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854048 ES:SE:LP:AF:SS:ID   0.00219754:0.00228824:0.472531:0.854048:54007:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168039   ES:SE:LP:AF:SS:ID   -0.0222062:0.0198259:0.580555:0.00168039:54007:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836519 ES:SE:LP:AF:SS:ID   -0.000838982:0.00224521:0.14957:0.836519:54007:rs376645387