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-22630_1/ukb-d-22630_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-22630_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 16:45:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22630_1/ukb-d-22630_1.vcf.gz ...
Read summary statistics for 12374888 SNPs.
Dropped 10991 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, 1283209 SNPs remain.
After merging with regression SNP LD, 1283209 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0233 (0.018)
Lambda GC: 1.0111
Mean Chi^2: 1.0089
Intercept: 0.9973 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:47:10 2019
Total time elapsed: 2.0m:0.38s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.0032,
    "mean_EFFECT": -0,
    "n": 25697,
    "n_snps": 12374888,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1201093,
    "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": 327969,
    "n_est": 25848.6403,
    "ratio_se_n": 1.0029,
    "mean_diff": -0,
    "ratio_diff": 2.9524,
    "sd_y_est1": 0.4171,
    "sd_y_est2": 0.4183,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283209,
    "ldsc_nsnp_merge_regression_ld": 1283209,
    "ldsc_observed_scale_h2_beta": 0.0233,
    "ldsc_observed_scale_h2_se": 0.018,
    "ldsc_intercept_beta": 0.9973,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0111,
    "ldsc_mean_chisq": 1.0089,
    "ldsc_ratio": -0.3034
}

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 12364529 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 54277 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32453 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.063799e+00 6.184807e+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 7.893171e+07 5.596075e+07 3.02000e+02 3.275870e+07 6.998066e+07 1.147853e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.730000e-05 1.586110e-02 -1.99437e-01 -5.104200e-03 -3.360000e-05 5.024200e-03 2.438780e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.200800e-02 1.035480e-02 2.94740e-03 4.269400e-03 7.005100e-03 1.674330e-02 6.599820e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.993732e-01 2.885874e-01 0.00000e+00 2.496342e-01 4.993200e-01 7.488882e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.993670e-01 2.885911e-01 0.00000e+00 2.496226e-01 4.993137e-01 7.488855e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.084881e-01 2.582879e-01 2.06750e-03 1.292510e-02 8.360680e-02 3.297960e-01 9.979320e-01 ▇▂▁▁▁
numeric AF_reference 327969 0.9734972 NA NA NA NA NA 2.105863e-01 2.499789e-01 0.00000e+00 9.784400e-03 1.042330e-01 3.340650e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.569700e+04 0.000000e+00 2.56970e+04 2.569700e+04 2.569700e+04 2.569700e+04 2.569700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0055598 0.0064032 0.3852477 0.3852400 0.1121430 0.1894970 25697
1 693731 rs12238997 A G -0.0040142 0.0061150 0.5115358 0.5115299 0.1165660 0.1417730 25697
1 707522 rs371890604 G C -0.0020602 0.0068840 0.7647280 0.7647264 0.0975760 0.1293930 25697
1 717587 rs144155419 G A -0.0101270 0.0162240 0.5325017 0.5324971 0.0160183 0.0045926 25697
1 730087 rs148120343 T C -0.0130511 0.0083984 0.1201990 0.1201852 0.0579332 0.0127796 25697
1 731718 rs142557973 T C -0.0061856 0.0057951 0.2858110 0.2858015 0.1229090 0.1543530 25697
1 732032 rs61770163 A C -0.0058542 0.0061741 0.3430370 0.3430279 0.1227700 0.1555510 25697
1 734349 rs141242758 T C -0.0060640 0.0057985 0.2956698 0.2956599 0.1221900 0.1525560 25697
1 740284 rs61770167 C T 0.0148716 0.0274787 0.5883720 0.5883665 0.0054168 0.0023962 25697
1 749963 rs529266287 T TAA 0.0046120 0.0056921 0.4177986 0.4177916 0.8679320 0.7641770 25697
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0026294 0.0064669 0.6843133 0.6843099 0.0569276 0.0309934 25697
23 154923374 rs111332691 T A 0.0023289 0.0071630 0.7450887 0.7450851 0.0445188 0.0116556 25697
23 154925045 rs509981 C T 0.0043630 0.0034717 0.2088618 0.2088506 0.2412010 0.3634440 25697
23 154925895 rs538470 C T 0.0047203 0.0035478 0.1833711 0.1833580 0.2377450 0.3634440 25697
23 154927581 rs644138 G A 0.0030825 0.0032528 0.3433278 0.3433207 0.2986200 0.4635760 25697
23 154929412 rs557132 C T 0.0042934 0.0034733 0.2164188 0.2164076 0.2409870 0.3568210 25697
23 154929637 rs35185538 CT C 0.0053253 0.0036190 0.1411731 0.1411603 0.2268160 0.3011920 25697
23 154929952 rs4012982 CAA C 0.0045231 0.0036561 0.2160548 0.2160439 0.2348550 0.3165560 25697
23 154930230 rs781880 A G 0.0044235 0.0034710 0.2025228 0.2025112 0.2415200 0.3618540 25697
23 154930487 rs781879 T A 0.0101068 0.0120450 0.4014274 0.4014206 0.0189835 0.1263580 25697

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112143 ES:SE:LP:AF:SS:ID   -0.0055598:0.00640322:0.41426:0.112143:25697:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116566 ES:SE:LP:AF:SS:ID   -0.00401421:0.00611496:0.291124:0.116566:25697:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097576 ES:SE:LP:AF:SS:ID   -0.00206025:0.00688402:0.116493:0.097576:25697:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0160183    ES:SE:LP:AF:SS:ID   -0.010127:0.016224:0.273679:0.0160183:25697:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0579332    ES:SE:LP:AF:SS:ID   -0.0130511:0.00839841:0.920099:0.0579332:25697:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122909 ES:SE:LP:AF:SS:ID   -0.00618558:0.00579512:0.543921:0.122909:25697:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12277  ES:SE:LP:AF:SS:ID   -0.00585425:0.00617407:0.464659:0.12277:25697:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12219  ES:SE:LP:AF:SS:ID   -0.006064:0.00579851:0.529193:0.12219:25697:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00541682   ES:SE:LP:AF:SS:ID   0.0148716:0.0274787:0.230348:0.00541682:25697:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.867932 ES:SE:LP:AF:SS:ID   0.00461204:0.00569206:0.379033:0.867932:25697:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.12446  ES:SE:LP:AF:SS:ID   -0.0066704:0.00564616:0.624422:0.12446:25697:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143673 ES:SE:LP:AF:SS:ID   -0.00745217:0.00559747:0.737345:0.143673:25697:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124586 ES:SE:LP:AF:SS:ID   -0.00686368:0.00563905:0.650623:0.124586:25697:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869298 ES:SE:LP:AF:SS:ID   0.00547456:0.00550143:0.495271:0.869298:25697:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873888 ES:SE:LP:AF:SS:ID   0.00523499:0.00558666:0.457497:0.873888:25697:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130223 ES:SE:LP:AF:SS:ID   -0.00548713:0.00551835:0.494762:0.130223:25697:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0356073    ES:SE:LP:AF:SS:ID   0.0163827:0.0100902:0.981008:0.0356073:25697:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86893  ES:SE:LP:AF:SS:ID   0.00515278:0.00549744:0.45766:0.86893:25697:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869072 ES:SE:LP:AF:SS:ID   0.00521725:0.00550058:0.464848:0.869072:25697:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868931 ES:SE:LP:AF:SS:ID   0.00513867:0.00549726:0.456037:0.868931:25697:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0049226    ES:SE:LP:AF:SS:ID   -0.00459134:0.0288001:0.0588171:0.0049226:25697:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00489216   ES:SE:LP:AF:SS:ID   -0.00515272:0.0288681:0.0663417:0.00489216:25697:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00561735   ES:SE:LP:AF:SS:ID   -0.0104298:0.0269666:0.155565:0.00561735:25697:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868988 ES:SE:LP:AF:SS:ID   0.00511154:0.00548647:0.45405:0.868988:25697:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127576 ES:SE:LP:AF:SS:ID   -0.00562161:0.00559528:0.501623:0.127576:25697:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868487 ES:SE:LP:AF:SS:ID   0.00520201:0.00547221:0.466223:0.868487:25697:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867984 ES:SE:LP:AF:SS:ID   0.00482924:0.00547187:0.423101:0.867984:25697:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868672 ES:SE:LP:AF:SS:ID   0.00527454:0.0054765:0.474314:0.868672:25697:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868677 ES:SE:LP:AF:SS:ID   0.00527324:0.00547682:0.474122:0.868677:25697:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868677 ES:SE:LP:AF:SS:ID   0.00527848:0.00547683:0.474743:0.868677:25697:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86918  ES:SE:LP:AF:SS:ID   0.00527683:0.00549311:0.472695:0.86918:25697:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09951  ES:SE:LP:AF:SS:ID   -0.00482235:0.00640088:0.345608:0.09951:25697:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00646211   ES:SE:LP:AF:SS:ID   -0.0184381:0.0245276:0.344649:0.00646211:25697:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873078 ES:SE:LP:AF:SS:ID   0.00496352:0.00557007:0.42843:0.873078:25697:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862503 ES:SE:LP:AF:SS:ID   0.00347447:0.00546527:0.279879:0.862503:25697:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867879 ES:SE:LP:AF:SS:ID   0.00494343:0.00551823:0.43139:0.867879:25697:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86493  ES:SE:LP:AF:SS:ID   0.0062391:0.00552427:0.587136:0.86493:25697:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994497    ES:SE:LP:AF:SS:ID   -0.00267721:0.00661851:0.163774:0.0994497:25697:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   0.0059571:0.00558727:0.543107:0.870274:25697:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   0.0059578:0.00558727:0.543192:0.870274:25697:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870271 ES:SE:LP:AF:SS:ID   0.00595877:0.00558728:0.543311:0.870271:25697:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870593 ES:SE:LP:AF:SS:ID   0.00583942:0.00558844:0.5286:0.870593:25697:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12718  ES:SE:LP:AF:SS:ID   -0.00523488:0.00558966:0.457162:0.12718:25697:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106621 ES:SE:LP:AF:SS:ID   -0.00453086:0.00607642:0.341142:0.106621:25697:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853855 ES:SE:LP:AF:SS:ID   0.00265317:0.00544847:0.203222:0.853855:25697:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838998 ES:SE:LP:AF:SS:ID   0.00434946:0.00539996:0.376172:0.838998:25697:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763662 ES:SE:LP:AF:SS:ID   0.00194095:0.00434392:0.183753:0.763662:25697:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.104137 ES:SE:LP:AF:SS:ID   0.00110086:0.00599909:0.0683372:0.104137:25697:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00725285   ES:SE:LP:AF:SS:ID   0.0286341:0.0228963:0.67553:0.00725285:25697:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.13049  ES:SE:LP:AF:SS:ID   -0.00580134:0.00551328:0.533583:0.13049:25697:rs762168062