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-20532/ukb-d-20532.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-20532/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 17:15:14 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20532/ukb-d-20532.vcf.gz ...
Read summary statistics for 13557164 SNPs.
Dropped 12672 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, 1283501 SNPs remain.
After merging with regression SNP LD, 1283501 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0255 (0.0089)
Lambda GC: 1.0223
Mean Chi^2: 1.0278
Intercept: 0.9988 (0.0059)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:18:06 2019
Total time elapsed: 2.0m:52.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0169,
    "mean_EFFECT": -0,
    "n": 57086,
    "n_snps": 13557164,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250819,
    "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": 561150,
    "n_est": 57250.2505,
    "ratio_se_n": 1.0014,
    "mean_diff": -0,
    "ratio_diff": 28.6244,
    "sd_y_est1": 0.3995,
    "sd_y_est2": 0.4001,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283501,
    "ldsc_nsnp_merge_regression_ld": 1283501,
    "ldsc_observed_scale_h2_beta": 0.0255,
    "ldsc_observed_scale_h2_se": 0.0089,
    "ldsc_intercept_beta": 0.9988,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0223,
    "ldsc_mean_chisq": 1.0278,
    "ldsc_ratio": -0.0432
}

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 13545155 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57030 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33315 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051384e+00 6.185000e+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 7.902450e+07 5.591661e+07 3.0200e+02 3.292669e+07 7.013818e+07 1.148581e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.960000e-05 1.374130e-02 -1.7514e-01 -3.635800e-03 2.010000e-05 3.689400e-03 1.532530e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.880400e-03 9.516300e-03 2.0074e-03 2.826200e-03 5.193100e-03 1.418160e-02 4.885650e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.971438e-01 2.891933e-01 0.0000e+00 2.463911e-01 4.964037e-01 7.471486e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.971410e-01 2.891950e-01 0.0000e+00 2.463865e-01 4.964012e-01 7.471484e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911908e-01 2.544969e-01 1.0000e-03 7.532200e-03 6.050900e-02 2.961100e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561150 0.9586086 NA NA NA NA NA 1.966141e-01 2.471585e-01 0.0000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.708600e+04 0.000000e+00 5.7086e+04 5.708600e+04 5.708600e+04 5.708600e+04 5.708600e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0018696 0.0041157 0.6496508 0.6496498 0.1121430 0.1894970 57086
1 693731 rs12238997 A G 0.0010335 0.0038935 0.7906768 0.7906767 0.1171340 0.1417730 57086
1 707522 rs371890604 G C 0.0018916 0.0043629 0.6646056 0.6646038 0.0988309 0.1293930 57086
1 717587 rs144155419 G A -0.0100285 0.0104427 0.3368930 0.3368862 0.0158264 0.0045926 57086
1 723329 rs189787166 A T -0.0151728 0.0302280 0.6157069 0.6157061 0.0018189 0.0003994 57086
1 730087 rs148120343 T C -0.0019080 0.0054267 0.7251402 0.7251393 0.0569421 0.0127796 57086
1 731718 rs142557973 T C -0.0004074 0.0036910 0.9121140 0.9121137 0.1232400 0.1543530 57086
1 732032 rs61770163 A C 0.0001596 0.0039341 0.9676460 0.9676462 0.1225970 0.1555510 57086
1 734349 rs141242758 T C -0.0000655 0.0036922 0.9858410 0.9858406 0.1225390 0.1525560 57086
1 740284 rs61770167 C T 0.0200988 0.0168017 0.2316098 0.2316044 0.0059132 0.0023962 57086
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0005712 0.0044516 0.8978970 0.8978964 0.0557881 0.0309934 57086
23 154923374 rs111332691 T A -0.0066918 0.0049037 0.1723709 0.1723649 0.0440914 0.0116556 57086
23 154925045 rs509981 C T 0.0004084 0.0023406 0.8615040 0.8615036 0.2456070 0.3634440 57086
23 154925895 rs538470 C T 0.0007869 0.0023934 0.7423112 0.7423103 0.2419310 0.3634440 57086
23 154927581 rs644138 G A 0.0006288 0.0022017 0.7752004 0.7751987 0.3018260 0.4635760 57086
23 154929412 rs557132 C T 0.0003740 0.0023411 0.8730600 0.8730595 0.2454980 0.3568210 57086
23 154929637 rs35185538 CT C 0.0007206 0.0024445 0.7681588 0.7681578 0.2294650 0.3011920 57086
23 154929952 rs4012982 CAA C 0.0009253 0.0024666 0.7075547 0.7075530 0.2391830 0.3165560 57086
23 154930230 rs781880 A G 0.0004213 0.0023405 0.8571470 0.8571467 0.2458390 0.3618540 57086
23 154930487 rs781879 T A -0.0084753 0.0079212 0.2846433 0.2846387 0.0196434 0.1263580 57086

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112143 ES:SE:LP:AF:SS:ID   -0.00186957:0.00411574:0.18732:0.112143:57086:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117134 ES:SE:LP:AF:SS:ID   0.00103347:0.00389354:0.102001:0.117134:57086:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0988309    ES:SE:LP:AF:SS:ID   0.0018916:0.00436289:0.177436:0.0988309:57086:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158264    ES:SE:LP:AF:SS:ID   -0.0100285:0.0104427:0.472508:0.0158264:57086:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00181886   ES:SE:LP:AF:SS:ID   -0.0151728:0.030228:0.210626:0.00181886:57086:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0569421    ES:SE:LP:AF:SS:ID   -0.00190802:0.0054267:0.139578:0.0569421:57086:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12324  ES:SE:LP:AF:SS:ID   -0.000407387:0.00369101:0.0399509:0.12324:57086:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122597 ES:SE:LP:AF:SS:ID   0.000159569:0.00393409:0.0142835:0.122597:57086:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122539 ES:SE:LP:AF:SS:ID   -6.5525e-05:0.00369216:0.00619312:0.122539:57086:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00591323   ES:SE:LP:AF:SS:ID   0.0200988:0.0168017:0.635243:0.00591323:57086:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00181635   ES:SE:LP:AF:SS:ID   0.0268109:0.0325818:0.386603:0.00181635:57086:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868306 ES:SE:LP:AF:SS:ID   -0.000613278:0.00363412:0.0624871:0.868306:57086:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00161524   ES:SE:LP:AF:SS:ID   -0.00475334:0.0319396:0.0546821:0.00161524:57086:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124561 ES:SE:LP:AF:SS:ID   0.000616921:0.00359847:0.0635476:0.124561:57086:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143966 ES:SE:LP:AF:SS:ID   0.000866857:0.00356469:0.0926596:0.143966:57086:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12465  ES:SE:LP:AF:SS:ID   0.000656106:0.00359378:0.0679633:0.12465:57086:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.86911  ES:SE:LP:AF:SS:ID   -0.00152969:0.00350413:0.178848:0.86911:57086:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873739 ES:SE:LP:AF:SS:ID   -0.000790414:0.00355978:0.0839231:0.873739:57086:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130309 ES:SE:LP:AF:SS:ID   0.00178512:0.0035139:0.213644:0.130309:57086:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036664 ES:SE:LP:AF:SS:ID   0.0109233:0.00638545:1.05974:0.036664:57086:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868752 ES:SE:LP:AF:SS:ID   -0.00176079:0.00350094:0.211123:0.868752:57086:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86882  ES:SE:LP:AF:SS:ID   -0.00190293:0.00350172:0.231483:0.86882:57086:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868754 ES:SE:LP:AF:SS:ID   -0.00175311:0.00350084:0.210042:0.868754:57086:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00507136   ES:SE:LP:AF:SS:ID   0.033696:0.0180459:1.2085:0.00507136:57086:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005042 ES:SE:LP:AF:SS:ID   0.0338893:0.0180868:1.21484:0.005042:57086:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.005822 ES:SE:LP:AF:SS:ID   -0.00534015:0.0170891:0.122243:0.005822:57086:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86877  ES:SE:LP:AF:SS:ID   -0.00174127:0.00349415:0.208837:0.86877:57086:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12768  ES:SE:LP:AF:SS:ID   0.00128847:0.00356535:0.143989:0.12768:57086:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868286 ES:SE:LP:AF:SS:ID   -0.00171706:0.00348477:0.206067:0.868286:57086:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86783  ES:SE:LP:AF:SS:ID   -0.00220403:0.00348401:0.278198:0.86783:57086:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868493 ES:SE:LP:AF:SS:ID   -0.00184855:0.00348837:0.224629:0.868493:57086:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868499 ES:SE:LP:AF:SS:ID   -0.00184284:0.00348862:0.223783:0.868499:57086:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868502 ES:SE:LP:AF:SS:ID   -0.00184364:0.00348863:0.223899:0.868502:57086:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868911 ES:SE:LP:AF:SS:ID   -0.0016463:0.00349755:0.195277:0.868911:57086:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100387 ES:SE:LP:AF:SS:ID   0.00108813:0.00405843:0.103138:0.100387:57086:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00677145   ES:SE:LP:AF:SS:ID   0.0053042:0.0154274:0.136091:0.00677145:57086:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872926 ES:SE:LP:AF:SS:ID   -0.000612354:0.00354985:0.0639671:0.872926:57086:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862404 ES:SE:LP:AF:SS:ID   -0.0023521:0.00348259:0.301524:0.862404:57086:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867591 ES:SE:LP:AF:SS:ID   -0.0013544:0.00351604:0.154849:0.867591:57086:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864803 ES:SE:LP:AF:SS:ID   -0.00141735:0.00352035:0.162897:0.864803:57086:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100546 ES:SE:LP:AF:SS:ID   0.00192326:0.00419875:0.189153:0.100546:57086:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869797 ES:SE:LP:AF:SS:ID   -0.000902445:0.00355721:0.097055:0.869797:57086:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869797 ES:SE:LP:AF:SS:ID   -0.000902346:0.00355721:0.0970436:0.869797:57086:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869794 ES:SE:LP:AF:SS:ID   -0.000903709:0.00355722:0.0972043:0.869794:57086:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870123 ES:SE:LP:AF:SS:ID   -0.000994787:0.0035586:0.108001:0.870123:57086:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127311 ES:SE:LP:AF:SS:ID   0.000839299:0.00356145:0.0895378:0.127311:57086:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10687  ES:SE:LP:AF:SS:ID   0.00174564:0.00387505:0.18551:0.10687:57086:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853714 ES:SE:LP:AF:SS:ID   -0.00437661:0.00348176:0.680363:0.853714:57086:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00173392   ES:SE:LP:AF:SS:ID   -0.0125616:0.0303693:0.168036:0.00173392:57086:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837347 ES:SE:LP:AF:SS:ID   0.00143158:0.00345475:0.168387:0.837347:57086:rs376645387