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-20542/ukb-d-20542.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-20542/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 17:15:45 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20542/ukb-d-20542.vcf.gz ...
Read summary statistics for 13530743 SNPs.
Dropped 12630 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, 1283493 SNPs remain.
After merging with regression SNP LD, 1283493 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0167 (0.017)
Lambda GC: 1.0063
Mean Chi^2: 1.0061
Intercept: 0.9978 (0.0055)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:18:03 2019
Total time elapsed: 2.0m:17.32s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0055,
    "mean_EFFECT": 0,
    "n": 25107,
    "n_snps": 13530743,
    "n_clumped_hits": 0,
    "n_p_sig": 3,
    "n_mono": 0,
    "n_ns": 1249780,
    "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": 554702,
    "n_est": 25202.9183,
    "ratio_se_n": 1.0019,
    "mean_diff": 0.0001,
    "ratio_diff": 73.1971,
    "sd_y_est1": 0.3784,
    "sd_y_est2": 0.3791,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283493,
    "ldsc_nsnp_merge_regression_ld": 1283493,
    "ldsc_observed_scale_h2_beta": 0.0167,
    "ldsc_observed_scale_h2_se": 0.017,
    "ldsc_intercept_beta": 0.9978,
    "ldsc_intercept_se": 0.0055,
    "ldsc_lambda_gc": 1.0063,
    "ldsc_mean_chisq": 1.0061,
    "ldsc_ratio": -0.3607
}

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 13518777 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56965 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33306 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051829e+00 6.185206e+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 7.902063e+07 5.591563e+07 3.02000e+02 3.292439e+07 7.013406e+07 1.148527e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.340000e-05 1.948100e-02 -2.51901e-01 -5.093400e-03 5.870000e-05 5.262200e-03 2.010210e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.404270e-02 1.351290e-02 2.86720e-03 4.033400e-03 7.390800e-03 2.013910e-02 7.396370e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.992017e-01 2.890394e-01 0.00000e+00 2.487499e-01 4.988305e-01 7.495835e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.991953e-01 2.890432e-01 0.00000e+00 2.487391e-01 4.988242e-01 7.495798e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.915408e-01 2.545794e-01 1.00000e-03 7.626800e-03 6.092900e-02 2.968300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 554702 0.9590043 NA NA NA NA NA 1.968776e-01 2.472176e-01 0.00000e+00 5.790700e-03 8.506390e-02 3.091050e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.510700e+04 0.000000e+00 2.51070e+04 2.510700e+04 2.510700e+04 2.510700e+04 2.510700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0053157 0.0058473 0.3633147 0.3633064 0.1131440 0.1894970 25107
1 693731 rs12238997 A G 0.0038854 0.0055054 0.4803535 0.4803477 0.1189510 0.1417730 25107
1 707522 rs371890604 G C 0.0016572 0.0062282 0.7901763 0.7901741 0.0992458 0.1293930 25107
1 717587 rs144155419 G A -0.0043629 0.0142880 0.7600987 0.7600959 0.0170637 0.0045926 25107
1 723329 rs189787166 A T 0.0362419 0.0460365 0.4311466 0.4311398 0.0016514 0.0003994 25107
1 730087 rs148120343 T C 0.0021299 0.0076989 0.7820509 0.7820477 0.0572906 0.0127796 25107
1 731718 rs142557973 T C 0.0020722 0.0052195 0.6913676 0.6913637 0.1256900 0.1543530 25107
1 732032 rs61770163 A C 0.0020842 0.0055847 0.7089996 0.7089968 0.1243150 0.1555510 25107
1 734349 rs141242758 T C 0.0022446 0.0052247 0.6674735 0.6674695 0.1248590 0.1525560 25107
1 740284 rs61770167 C T 0.0264317 0.0242002 0.2747521 0.2747408 0.0057894 0.0023962 25107
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0045636 0.0062592 0.4659454 0.4659385 0.0573346 0.0309934 25107
23 154923374 rs111332691 T A 0.0080158 0.0070217 0.2536442 0.2536335 0.0442705 0.0116556 25107
23 154925045 rs509981 C T -0.0004213 0.0033693 0.9004900 0.9004887 0.2419660 0.3634440 25107
23 154925895 rs538470 C T -0.0000216 0.0034450 0.9949900 0.9949902 0.2385670 0.3634440 25107
23 154927581 rs644138 G A -0.0016136 0.0031525 0.6087697 0.6087653 0.2998560 0.4635760 25107
23 154929412 rs557132 C T -0.0004377 0.0033704 0.8966790 0.8966780 0.2418200 0.3568210 25107
23 154929637 rs35185538 CT C 0.0012780 0.0035140 0.7160890 0.7160861 0.2263840 0.3011920 25107
23 154929952 rs4012982 CAA C -0.0007012 0.0035515 0.8434880 0.8434868 0.2356530 0.3165560 25107
23 154930230 rs781880 A G -0.0002912 0.0033696 0.9311270 0.9311260 0.2419860 0.3618540 25107
23 154930487 rs781879 T A -0.0030210 0.0112692 0.7886440 0.7886403 0.0197880 0.1263580 25107

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.113144 ES:SE:LP:AF:SS:ID   0.00531568:0.0058473:0.439717:0.113144:25107:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.118951 ES:SE:LP:AF:SS:ID   0.0038854:0.0055054:0.318439:0.118951:25107:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0992458    ES:SE:LP:AF:SS:ID   0.00165722:0.00622817:0.102276:0.0992458:25107:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0170637    ES:SE:LP:AF:SS:ID   -0.00436291:0.014288:0.11913:0.0170637:25107:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00165144   ES:SE:LP:AF:SS:ID   0.0362419:0.0460365:0.365375:0.00165144:25107:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572906    ES:SE:LP:AF:SS:ID   0.00212991:0.00769889:0.106765:0.0572906:25107:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12569  ES:SE:LP:AF:SS:ID   0.00207216:0.00521948:0.160291:0.12569:25107:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124315 ES:SE:LP:AF:SS:ID   0.00208422:0.00558467:0.149354:0.124315:25107:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.124859 ES:SE:LP:AF:SS:ID   0.00224465:0.00522469:0.175566:0.124859:25107:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578942   ES:SE:LP:AF:SS:ID   0.0264317:0.0242002:0.561059:0.00578942:25107:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187277   ES:SE:LP:AF:SS:ID   0.085694:0.0456688:1.21747:0.00187277:25107:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.866463 ES:SE:LP:AF:SS:ID   -0.000808952:0.0051492:0.0579101:0.866463:25107:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00137865   ES:SE:LP:AF:SS:ID   0.0817523:0.0497173:0.999488:0.00137865:25107:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125751 ES:SE:LP:AF:SS:ID   0.000178493:0.00511257:0.0122667:0.125751:25107:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145648 ES:SE:LP:AF:SS:ID   0.00113065:0.00505701:0.0845548:0.145648:25107:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125793 ES:SE:LP:AF:SS:ID   0.000184741:0.0051067:0.0127173:0.125793:25107:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867399 ES:SE:LP:AF:SS:ID   -0.00234724:0.00497577:0.195778:0.867399:25107:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872609 ES:SE:LP:AF:SS:ID   -0.000899926:0.00505926:0.0660973:0.872609:25107:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132039 ES:SE:LP:AF:SS:ID   0.00148582:0.00498957:0.115845:0.132039:25107:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365038    ES:SE:LP:AF:SS:ID   0.0210851:0.00913895:1.67668:0.0365038:25107:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867007 ES:SE:LP:AF:SS:ID   -0.00191152:0.0049712:0.154532:0.867007:25107:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867054 ES:SE:LP:AF:SS:ID   -0.0018716:0.00497209:0.150822:0.867054:25107:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867003 ES:SE:LP:AF:SS:ID   -0.00191613:0.00497096:0.154966:0.867003:25107:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00505804   ES:SE:LP:AF:SS:ID   -0.0210294:0.0257007:0.383811:0.00505804:25107:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00503859   ES:SE:LP:AF:SS:ID   -0.0212789:0.0257537:0.388624:0.00503859:25107:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00597872   ES:SE:LP:AF:SS:ID   0.00583557:0.0238812:0.0931501:0.00597872:25107:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.867017 ES:SE:LP:AF:SS:ID   -0.00228166:0.00496203:0.190005:0.867017:25107:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129277 ES:SE:LP:AF:SS:ID   0.00168071:0.00506203:0.130842:0.129277:25107:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866511 ES:SE:LP:AF:SS:ID   -0.00266544:0.0049489:0.229021:0.866511:25107:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866085 ES:SE:LP:AF:SS:ID   -0.00215053:0.00494766:0.177952:0.866085:25107:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866748 ES:SE:LP:AF:SS:ID   -0.00242581:0.0049547:0.204521:0.866748:25107:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866755 ES:SE:LP:AF:SS:ID   -0.00241752:0.00495505:0.203682:0.866755:25107:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866758 ES:SE:LP:AF:SS:ID   -0.00242203:0.00495504:0.20413:0.866758:25107:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867143 ES:SE:LP:AF:SS:ID   -0.00224361:0.00496648:0.186117:0.867143:25107:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.10083  ES:SE:LP:AF:SS:ID   0.00223261:0.00578547:0.155166:0.10083:25107:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00692065   ES:SE:LP:AF:SS:ID   -0.00779436:0.021725:0.142808:0.00692065:25107:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87158  ES:SE:LP:AF:SS:ID   -0.0015709:0.00504364:0.121793:0.87158:25107:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860545 ES:SE:LP:AF:SS:ID   -0.00373488:0.00494045:0.347107:0.860545:25107:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866052 ES:SE:LP:AF:SS:ID   -0.00222708:0.00499617:0.183244:0.866052:25107:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863119 ES:SE:LP:AF:SS:ID   -0.00216468:0.00499339:0.177408:0.863119:25107:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.10169  ES:SE:LP:AF:SS:ID   -0.000806177:0.00594796:0.0495441:0.10169:25107:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868471 ES:SE:LP:AF:SS:ID   -0.00162581:0.00505132:0.126353:0.868471:25107:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868471 ES:SE:LP:AF:SS:ID   -0.00162586:0.00505131:0.126356:0.868471:25107:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.868468 ES:SE:LP:AF:SS:ID   -0.00162403:0.00505132:0.126197:0.868468:25107:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868815 ES:SE:LP:AF:SS:ID   -0.00180585:0.00505498:0.142117:0.868815:25107:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128642 ES:SE:LP:AF:SS:ID   0.00141518:0.00506126:0.108028:0.128642:25107:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107606 ES:SE:LP:AF:SS:ID   0.00291932:0.0055106:0.22455:0.107606:25107:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85222  ES:SE:LP:AF:SS:ID   -0.00182555:0.00493964:0.1477:0.85222:25107:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00158443   ES:SE:LP:AF:SS:ID   0.0348459:0.0460417:0.347602:0.00158443:25107:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836723 ES:SE:LP:AF:SS:ID   0.00574016:0.00491975:0.613824:0.836723:25107:rs376645387