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-5855_3/ukb-d-5855_3.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-5855_3/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 17:08:02 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5855_3/ukb-d-5855_3.vcf.gz ...
Read summary statistics for 12563508 SNPs.
Dropped 11239 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, 1283271 SNPs remain.
After merging with regression SNP LD, 1283271 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0874 (0.043)
Lambda GC: 1.0142
Mean Chi^2: 1.0116
Intercept: 0.9948 (0.0055)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:10:07 2019
Total time elapsed: 2.0m:4.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.0018,
    "mean_EFFECT": -0,
    "n": 9749,
    "n_snps": 12563508,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1209790,
    "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": 356001,
    "n_est": 9802.3774,
    "ratio_se_n": 1.0027,
    "mean_diff": -0,
    "ratio_diff": 11.9419,
    "sd_y_est1": 0.4652,
    "sd_y_est2": 0.4665,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283271,
    "ldsc_nsnp_merge_regression_ld": 1283271,
    "ldsc_observed_scale_h2_beta": 0.0874,
    "ldsc_observed_scale_h2_se": 0.043,
    "ldsc_intercept_beta": 0.9948,
    "ldsc_intercept_se": 0.0055,
    "ldsc_lambda_gc": 1.0142,
    "ldsc_mean_chisq": 1.0116,
    "ldsc_ratio": -0.4483
}

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 12552907 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 54757 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32601 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.061494e+00 6.184726e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.894965e+07 5.595913e+07 3.0200e+02 3.278102e+07 7.000557e+07 1.148072e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.220000e-05 3.005950e-02 -3.9049e-01 -9.245500e-03 1.460000e-05 9.364600e-03 3.094960e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.260210e-02 1.986780e-02 5.5656e-03 7.764000e-03 1.296330e-02 3.170100e-02 1.218410e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.993723e-01 2.888252e-01 2.0000e-07 2.489178e-01 4.996150e-01 7.494506e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.993559e-01 2.888350e-01 2.0000e-07 2.488897e-01 4.995996e-01 7.494439e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.055449e-01 2.577311e-01 1.8646e-03 1.186140e-02 7.961640e-02 3.242900e-01 9.981350e-01 ▇▂▁▁▁
numeric AF_reference 356001 0.9716639 NA NA NA NA NA 2.080879e-01 2.495348e-01 0.0000e+00 8.785900e-03 1.008390e-01 3.296730e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.749000e+03 0.000000e+00 9.7490e+03 9.749000e+03 9.749000e+03 9.749000e+03 9.749000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0184244 0.0115274 0.1100079 0.1099732 0.1142420 0.1894970 9749
1 693731 rs12238997 A G -0.0101426 0.0108782 0.3511648 0.3511409 0.1187010 0.1417730 9749
1 707522 rs371890604 G C -0.0163874 0.0122620 0.1814379 0.1814062 0.1007710 0.1293930 9749
1 717587 rs144155419 G A -0.0015357 0.0292910 0.9581890 0.9581876 0.0159707 0.0045926 9749
1 723329 rs189787166 A T 0.0453295 0.0797173 0.5696223 0.5696085 0.0019912 0.0003994 9749
1 730087 rs148120343 T C -0.0227027 0.0153765 0.1398531 0.1398220 0.0571894 0.0127796 9749
1 731718 rs142557973 T C -0.0080877 0.0103217 0.4333163 0.4332961 0.1248650 0.1543530 9749
1 732032 rs61770163 A C -0.0087494 0.0110425 0.4281806 0.4281616 0.1241390 0.1555510 9749
1 734349 rs141242758 T C -0.0084092 0.0103391 0.4160418 0.4160211 0.1239920 0.1525560 9749
1 740284 rs61770167 C T -0.0299374 0.0460399 0.5155467 0.5155314 0.0062404 0.0023962 9749
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0089562 0.0126692 0.4796285 0.4796118 0.0528342 0.0309934 9749
23 154923374 rs111332691 T A 0.0071082 0.0134858 0.5981457 0.5981342 0.0460047 0.0116556 9749
23 154925045 rs509981 C T 0.0023764 0.0065489 0.7167076 0.7166984 0.2399570 0.3634440 9749
23 154925895 rs538470 C T 0.0030049 0.0066951 0.6535728 0.6535632 0.2362200 0.3634440 9749
23 154927581 rs644138 G A 0.0044907 0.0061584 0.4658971 0.4658799 0.2933230 0.4635760 9749
23 154929412 rs557132 C T 0.0020757 0.0065532 0.7514447 0.7514371 0.2397070 0.3568210 9749
23 154929637 rs35185538 CT C 0.0021936 0.0068396 0.7484297 0.7484229 0.2242450 0.3011920 9749
23 154929952 rs4012982 CAA C 0.0027924 0.0068823 0.6849471 0.6849377 0.2333320 0.3165560 9749
23 154930230 rs781880 A G 0.0013550 0.0065538 0.8362120 0.8362075 0.2398920 0.3618540 9749
23 154930487 rs781879 T A 0.0137764 0.0223582 0.5378003 0.5377839 0.0185018 0.1263580 9749

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.114242 ES:SE:LP:AF:SS:ID   -0.0184244:0.0115274:0.958576:0.114242:9749:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.118701 ES:SE:LP:AF:SS:ID   -0.0101426:0.0108782:0.454489:0.118701:9749:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100771 ES:SE:LP:AF:SS:ID   -0.0163874:0.012262:0.741272:0.100771:9749:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0159707    ES:SE:LP:AF:SS:ID   -0.00153567:0.029291:0.0185488:0.0159707:9749:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00199115   ES:SE:LP:AF:SS:ID   0.0453295:0.0797173:0.244413:0.00199115:9749:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0571894    ES:SE:LP:AF:SS:ID   -0.0227027:0.0153765:0.854328:0.0571894:9749:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124865 ES:SE:LP:AF:SS:ID   -0.00808771:0.0103217:0.363195:0.124865:9749:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124139 ES:SE:LP:AF:SS:ID   -0.00874943:0.0110425:0.368373:0.124139:9749:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123992 ES:SE:LP:AF:SS:ID   -0.00840924:0.0103391:0.380863:0.123992:9749:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00624036   ES:SE:LP:AF:SS:ID   -0.0299374:0.0460399:0.287732:0.00624036:9749:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187249   ES:SE:LP:AF:SS:ID   0.104188:0.0915589:0.593162:0.00187249:9749:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.866531 ES:SE:LP:AF:SS:ID   0.00835551:0.0101693:0.385837:0.866531:9749:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.125949 ES:SE:LP:AF:SS:ID   -0.0071351:0.010093:0.319098:0.125949:9749:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144819 ES:SE:LP:AF:SS:ID   -0.00723963:0.0100524:0.326588:0.144819:9749:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.126104 ES:SE:LP:AF:SS:ID   -0.00718257:0.0100769:0.322393:0.126104:9749:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867084 ES:SE:LP:AF:SS:ID   0.00838329:0.00980415:0.406127:0.867084:9749:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872272 ES:SE:LP:AF:SS:ID   0.00737284:0.00997745:0.337285:0.872272:9749:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132153 ES:SE:LP:AF:SS:ID   -0.00886978:0.0098292:0.435485:0.132153:9749:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0374397    ES:SE:LP:AF:SS:ID   -0.0268718:0.0178198:0.880761:0.0374397:9749:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.866829 ES:SE:LP:AF:SS:ID   0.00884359:0.00980032:0.435477:0.866829:9749:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.866825 ES:SE:LP:AF:SS:ID   0.00883454:0.00980058:0.434882:0.866825:9749:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866826 ES:SE:LP:AF:SS:ID   0.00883037:0.00979993:0.434653:0.866826:9749:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00531216   ES:SE:LP:AF:SS:ID   -0.0276309:0.0491382:0.241151:0.00531216:9749:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00528521   ES:SE:LP:AF:SS:ID   -0.0277364:0.0492736:0.241457:0.00528521:9749:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00508448   ES:SE:LP:AF:SS:ID   0.00094008:0.0524088:0.00626009:0.00508448:9749:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.866917 ES:SE:LP:AF:SS:ID   0.00865611:0.00977977:0.42467:0.866917:9749:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129067 ES:SE:LP:AF:SS:ID   -0.00700231:0.00997642:0.316262:0.129067:9749:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866345 ES:SE:LP:AF:SS:ID   0.00849767:0.00974969:0.416283:0.866345:9749:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.865774 ES:SE:LP:AF:SS:ID   0.00842775:0.00974923:0.411885:0.865774:9749:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866606 ES:SE:LP:AF:SS:ID   0.00860742:0.00976164:0.42259:0.866606:9749:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866611 ES:SE:LP:AF:SS:ID   0.00859574:0.00976233:0.421808:0.866611:9749:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866635 ES:SE:LP:AF:SS:ID   0.00866829:0.00976315:0.426387:0.866635:9749:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867029 ES:SE:LP:AF:SS:ID   0.00861921:0.00978796:0.421865:0.867029:9749:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.102203 ES:SE:LP:AF:SS:ID   -0.0109888:0.0113711:0.476412:0.102203:9749:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00559776   ES:SE:LP:AF:SS:ID   0.0277637:0.0480582:0.249126:0.00559776:9749:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.871134 ES:SE:LP:AF:SS:ID   0.00829129:0.00994111:0.39332:0.871134:9749:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860725 ES:SE:LP:AF:SS:ID   0.00942775:0.00976168:0.47603:0.860725:9749:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.865849 ES:SE:LP:AF:SS:ID   0.00929662:0.00985459:0.461539:0.865849:9749:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.862713 ES:SE:LP:AF:SS:ID   0.00838904:0.00984314:0.404411:0.862713:9749:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.101338 ES:SE:LP:AF:SS:ID   -0.00702065:0.0117489:0.259521:0.101338:9749:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868004 ES:SE:LP:AF:SS:ID   0.00915387:0.00996588:0.44567:0.868004:9749:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868004 ES:SE:LP:AF:SS:ID   0.00915258:0.00996588:0.445587:0.868004:9749:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.868002 ES:SE:LP:AF:SS:ID   0.00915307:0.0099659:0.445617:0.868002:9749:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868382 ES:SE:LP:AF:SS:ID   0.00871834:0.00997454:0.417815:0.868382:9749:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128883 ES:SE:LP:AF:SS:ID   -0.00874091:0.00996873:0.419532:0.128883:9749:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.108582 ES:SE:LP:AF:SS:ID   -0.00815959:0.0108734:0.343881:0.108582:9749:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.851426 ES:SE:LP:AF:SS:ID   0.00642339:0.00975377:0.292261:0.851426:9749:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00188597   ES:SE:LP:AF:SS:ID   0.071635:0.0809647:0.424461:0.00188597:9749:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837626 ES:SE:LP:AF:SS:ID   0.00281375:0.00974201:0.111978:0.837626:9749:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.759154 ES:SE:LP:AF:SS:ID   0.00644556:0.00778724:0.389493:0.759154:9749:rs2977608