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-22660_108/ukb-d-22660_108.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-22660_108/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 14:53:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22660_108/ukb-d-22660_108.vcf.gz ...
Read summary statistics for 13560221 SNPs.
Dropped 12671 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0096 (0.007)
Lambda GC: 1.0188
Mean Chi^2: 1.0186
Intercept: 1.0058 (0.0059)
Ratio: 0.313 (0.3174)
Analysis finished at Mon Nov 25 14:55:24 2019
Total time elapsed: 1.0m:54.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0025,
    "mean_EFFECT": -8.0669e-06,
    "n": 67655,
    "n_snps": 13560221,
    "n_clumped_hits": 1,
    "n_p_sig": 26,
    "n_mono": 0,
    "n_ns": 1250997,
    "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": 561552,
    "n_est": 67875.5186,
    "ratio_se_n": 1.0016,
    "mean_diff": -0,
    "ratio_diff": 11.8292,
    "sd_y_est1": 0.3181,
    "sd_y_est2": 0.3187,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0005,
    "r2_sum3": 0.0005,
    "r2_sum4": 0.0005,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0096,
    "ldsc_observed_scale_h2_se": 0.007,
    "ldsc_intercept_beta": 1.0058,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0188,
    "ldsc_mean_chisq": 1.0186,
    "ldsc_ratio": 0.3118
}

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 13548214 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57036 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33331 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051468e+00 6.185045e+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 7.902618e+07 5.591720e+07 3.02000e+02 3.292798e+07 7.013588e+07 1.148646e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.100000e-06 1.003880e-02 -1.28116e-01 -2.645900e-03 9.000000e-06 2.672000e-03 1.391530e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.229800e-03 6.965000e-03 1.44180e-03 2.067500e-03 3.800100e-03 1.037850e-02 3.565770e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.994524e-01 2.893153e-01 0.00000e+00 2.484002e-01 4.994672e-01 7.500963e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.994500e-01 2.893167e-01 0.00000e+00 2.483960e-01 4.994647e-01 7.500956e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911551e-01 2.544950e-01 1.00000e-03 7.523000e-03 6.040290e-02 2.959440e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561552 0.9585883 NA NA NA NA NA 1.965910e-01 2.471619e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.086090e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.765500e+04 0.000000e+00 6.76550e+04 6.765500e+04 6.765500e+04 6.765500e+04 6.765500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0046332 0.0030200 0.1249931 0.1249881 0.1113330 0.1894970 67655
1 693731 rs12238997 A G 0.0008727 0.0028610 0.7603368 0.7603366 0.1164250 0.1417730 67655
1 707522 rs371890604 G C 0.0001665 0.0032166 0.9587141 0.9587137 0.0978617 0.1293930 67655
1 717587 rs144155419 G A 0.0157464 0.0076592 0.0397988 0.0397943 0.0157910 0.0045926 67655
1 723329 rs189787166 A T -0.0320172 0.0219720 0.1450721 0.1450662 0.0018352 0.0003994 67655
1 730087 rs148120343 T C -0.0014770 0.0039680 0.7097232 0.7097225 0.0569430 0.0127796 67655
1 731718 rs142557973 T C 0.0012582 0.0027152 0.6430918 0.6430902 0.1223980 0.1543530 67655
1 732032 rs61770163 A C 0.0004135 0.0028958 0.8864591 0.8864583 0.1220450 0.1555510 67655
1 734349 rs141242758 T C 0.0012717 0.0027173 0.6397879 0.6397852 0.1216050 0.1525560 67655
1 740284 rs61770167 C T 0.0087737 0.0125554 0.4846799 0.4846767 0.0056852 0.0023962 67655
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0032933 0.0032388 0.3092431 0.3092386 0.0547784 0.0309934 67655
23 154923374 rs111332691 T A 0.0014528 0.0035245 0.6801896 0.6801892 0.0442687 0.0116556 67655
23 154925045 rs509981 C T 0.0000486 0.0016825 0.9769641 0.9769638 0.2448950 0.3634440 67655
23 154925895 rs538470 C T 0.0002327 0.0017204 0.8923980 0.8923979 0.2412550 0.3634440 67655
23 154927581 rs644138 G A 0.0008871 0.0015848 0.5756400 0.5756384 0.3000720 0.4635760 67655
23 154929412 rs557132 C T 0.0000820 0.0016830 0.9611560 0.9611556 0.2447530 0.3568210 67655
23 154929637 rs35185538 CT C 0.0017054 0.0017580 0.3320213 0.3320151 0.2291340 0.3011920 67655
23 154929952 rs4012982 CAA C 0.0000285 0.0017716 0.9871510 0.9871514 0.2385660 0.3165560 67655
23 154930230 rs781880 A G 0.0001309 0.0016826 0.9379880 0.9379873 0.2451600 0.3618540 67655
23 154930487 rs781879 T A 0.0114987 0.0057589 0.0458627 0.0458581 0.0193551 0.1263580 67655

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111333 ES:SE:LP:AF:SS:ID   0.00463319:0.00302:0.903114:0.111333:67655:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116425 ES:SE:LP:AF:SS:ID   0.000872707:0.00286097:0.118994:0.116425:67655:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978617    ES:SE:LP:AF:SS:ID   0.000166516:0.00321659:0.0183109:0.0978617:67655:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015791 ES:SE:LP:AF:SS:ID   0.0157464:0.00765921:1.40013:0.015791:67655:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00183518   ES:SE:LP:AF:SS:ID   -0.0320172:0.021972:0.838416:0.00183518:67655:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056943 ES:SE:LP:AF:SS:ID   -0.001477:0.00396799:0.148911:0.056943:67655:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122398 ES:SE:LP:AF:SS:ID   0.00125819:0.00271523:0.191727:0.122398:67655:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122045 ES:SE:LP:AF:SS:ID   0.00041349:0.00289585:0.0523413:0.122045:67655:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121605 ES:SE:LP:AF:SS:ID   0.00127168:0.00271727:0.193964:0.121605:67655:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00568516   ES:SE:LP:AF:SS:ID   0.00877372:0.0125554:0.314545:0.00568516:67655:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00185636   ES:SE:LP:AF:SS:ID   0.0066632:0.0235842:0.109278:0.00185636:67655:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86888  ES:SE:LP:AF:SS:ID   -0.000354009:0.00267203:0.0483716:0.86888:67655:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00154315   ES:SE:LP:AF:SS:ID   -0.00487267:0.0242243:0.0754194:0.00154315:67655:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123646 ES:SE:LP:AF:SS:ID   -0.000316016:0.00265019:0.0433116:0.123646:67655:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143073 ES:SE:LP:AF:SS:ID   -0.00212401:0.00262298:0.378744:0.143073:67655:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123779 ES:SE:LP:AF:SS:ID   -0.000478936:0.00264631:0.0673325:0.123779:67655:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869863 ES:SE:LP:AF:SS:ID   9.95717e-05:0.00257819:0.0135897:0.869863:67655:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874632 ES:SE:LP:AF:SS:ID   0.000606648:0.00262116:0.0877928:0.874632:67655:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129534 ES:SE:LP:AF:SS:ID   9.98165e-05:0.00258594:0.0135821:0.129534:67655:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358436    ES:SE:LP:AF:SS:ID   0.00316595:0.00472033:0.298942:0.0358436:67655:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   7.99312e-05:0.0025759:0.0108863:0.869516:67655:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869601 ES:SE:LP:AF:SS:ID   1.86516e-05:0.00257722:0.00251488:0.869601:67655:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86951  ES:SE:LP:AF:SS:ID   8.49379e-05:0.00257578:0.0115775:0.86951:67655:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00535705   ES:SE:LP:AF:SS:ID   -0.0100049:0.0128303:0.360995:0.00535705:67655:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00532268   ES:SE:LP:AF:SS:ID   -0.0107694:0.0128626:0.395289:0.00532268:67655:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00587606   ES:SE:LP:AF:SS:ID   -0.0161847:0.0123922:0.717731:0.00587606:67655:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869521 ES:SE:LP:AF:SS:ID   0.000113715:0.00257088:0.0155992:0.869521:67655:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   -3.50124e-05:0.00262409:0.00464829:0.126879:67655:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869086 ES:SE:LP:AF:SS:ID   0.000196552:0.00256436:0.0273788:0.869086:67655:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86843  ES:SE:LP:AF:SS:ID   -6.92358e-05:0.00256165:0.00946669:0.86843:67655:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   0.000159822:0.00256645:0.0221187:0.869213:67655:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869219 ES:SE:LP:AF:SS:ID   0.000158985:0.00256662:0.0219985:0.869219:67655:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:SS:ID   0.000158509:0.00256663:0.0219309:0.869221:67655:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869661 ES:SE:LP:AF:SS:ID   0.000210042:0.00257332:0.029213:0.869661:67655:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991549    ES:SE:LP:AF:SS:ID   -0.00187531:0.00299573:0.274643:0.0991549:67655:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00672466   ES:SE:LP:AF:SS:ID   -0.0131237:0.0112979:0.610122:0.00672466:67655:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873693 ES:SE:LP:AF:SS:ID   0.000153282:0.00261125:0.0208201:0.873693:67655:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86311  ES:SE:LP:AF:SS:ID   -0.000444288:0.00256115:0.0643512:0.86311:67655:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868459 ES:SE:LP:AF:SS:ID   -0.000225032:0.00258703:0.0311978:0.868459:67655:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865449 ES:SE:LP:AF:SS:ID   -0.000267253:0.0025872:0.0372865:0.865449:67655:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996966    ES:SE:LP:AF:SS:ID   7.74372e-05:0.00309356:0.00876063:0.0996966:67655:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   5.6984e-05:0.00261678:0.00761175:0.870704:67655:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   5.66206e-05:0.00261678:0.00756269:0.870704:67655:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870702 ES:SE:LP:AF:SS:ID   5.71276e-05:0.00261679:0.00763075:0.870702:67655:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871042 ES:SE:LP:AF:SS:ID   0.000136748:0.00261804:0.018479:0.871042:67655:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126524 ES:SE:LP:AF:SS:ID   7.05232e-05:0.00262068:0.00942541:0.126524:67655:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105925 ES:SE:LP:AF:SS:ID   -0.00193084:0.00285206:0.302413:0.105925:67655:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854403 ES:SE:LP:AF:SS:ID   0.000454319:0.00256002:0.0659351:0.854403:67655:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00175177   ES:SE:LP:AF:SS:ID   -0.0334206:0.0220034:0.890094:0.00175177:67655:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839355 ES:SE:LP:AF:SS:ID   0.000817991:0.00252863:0.127073:0.839355:67655:rs376645387