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-1747_5/ukb-d-1747_5.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-1747_5/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 16:55:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1747_5/ukb-d-1747_5.vcf.gz ...
Read summary statistics for 13586530 SNPs.
Dropped 12711 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0586 (0.0148)
Lambda GC: 1.1349
Mean Chi^2: 1.4218
Intercept: 1.0401 (0.0098)
Ratio: 0.095 (0.0232)
Analysis finished at Mon Nov 25 16:57:27 2019
Total time elapsed: 2.0m:18.27s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0916,
    "mean_EFFECT": 6.8972e-06,
    "n": 360270,
    "n_snps": 13586530,
    "n_clumped_hits": 67,
    "n_p_sig": 13698,
    "n_mono": 0,
    "n_ns": 1251807,
    "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": 569284,
    "n_est": 361644.1047,
    "ratio_se_n": 1.0019,
    "mean_diff": 0,
    "ratio_diff": 106.0413,
    "sd_y_est1": 0.2026,
    "sd_y_est2": 0.203,
    "r2_sum1": 0.0017,
    "r2_sum2": 0.0407,
    "r2_sum3": 0.0405,
    "r2_sum4": 0.0397,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0586,
    "ldsc_observed_scale_h2_se": 0.0148,
    "ldsc_intercept_beta": 1.0401,
    "ldsc_intercept_se": 0.0098,
    "ldsc_lambda_gc": 1.1349,
    "ldsc_mean_chisq": 1.4218,
    "ldsc_ratio": 0.0951
}
 

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 TRUE
n_p_sig TRUE
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 13574483 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33336 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051332e+00 6.184976e+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 7.902492e+07 5.591479e+07 3.02000e+02 3.293086e+07 7.013828e+07 1.148589e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 6.900000e-06 2.847800e-03 -8.41459e-02 -7.873000e-04 -4.800000e-06 7.738000e-04 1.069690e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.005800e-03 1.934800e-03 3.92500e-04 5.710000e-04 1.052300e-03 2.882600e-03 9.732500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.852622e-01 2.935717e-01 0.00000e+00 2.279570e-01 4.809988e-01 7.396087e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.852618e-01 2.935719e-01 0.00000e+00 2.279563e-01 4.809988e-01 7.396081e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908023e-01 2.544021e-01 1.00000e-03 7.429300e-03 6.003020e-02 2.953080e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569284 0.9580994 NA NA NA NA NA 1.963336e-01 2.471006e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.602700e+05 0.000000e+00 3.60270e+05 3.602700e+05 3.602700e+05 3.602700e+05 3.602700e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0009932 0.0008358 0.2347351 0.2347342 0.1106500 0.1894970 360270
1 693731 rs12238997 A G -0.0000698 0.0007898 0.9295411 0.9295408 0.1158380 0.1417730 360270
1 707522 rs371890604 G C 0.0004109 0.0008880 0.6435585 0.6435578 0.0972910 0.1293930 360270
1 717587 rs144155419 G A -0.0019896 0.0021178 0.3475042 0.3475032 0.0157019 0.0045926 360270
1 723329 rs189787166 A T -0.0008386 0.0062575 0.8933929 0.8933929 0.0017308 0.0003994 360270
1 730087 rs148120343 T C -0.0009629 0.0011004 0.3815566 0.3815572 0.0564472 0.0127796 360270
1 731718 rs142557973 T C 0.0002762 0.0007490 0.7122837 0.7122824 0.1217410 0.1543530 360270
1 732032 rs61770163 A C 0.0000129 0.0007990 0.9871170 0.9871171 0.1211730 0.1555510 360270
1 734349 rs141242758 T C 0.0002038 0.0007494 0.7857077 0.7857079 0.1209690 0.1525560 360270
1 740284 rs61770167 C T 0.0019973 0.0034271 0.5600335 0.5600341 0.0057907 0.0023962 360270
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0010943 0.0008658 0.2062719 0.2062704 0.0561460 0.0309934 360270
23 154923374 rs111332691 T A -0.0020233 0.0009513 0.0334357 0.0334346 0.0447845 0.0116556 360270
23 154925045 rs509981 C T -0.0000174 0.0004577 0.9696181 0.9696179 0.2456300 0.3634440 360270
23 154925895 rs538470 C T -0.0001036 0.0004682 0.8249380 0.8249385 0.2419380 0.3634440 360270
23 154927581 rs644138 G A -0.0002914 0.0004304 0.4984332 0.4984334 0.3021610 0.4635760 360270
23 154929412 rs557132 C T -0.0000246 0.0004578 0.9570810 0.9570808 0.2454820 0.3568210 360270
23 154929637 rs35185538 CT C -0.0002834 0.0004778 0.5530444 0.5530437 0.2297100 0.3011920 360270
23 154929952 rs4012982 CAA C 0.0000250 0.0004815 0.9585611 0.9585613 0.2394580 0.3165560 360270
23 154930230 rs781880 A G -0.0000292 0.0004578 0.9490990 0.9490986 0.2458930 0.3618540 360270
23 154930487 rs781879 T A -0.0015964 0.0015696 0.3091320 0.3091304 0.0195732 0.1263580 360270

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11065  ES:SE:LP:AF:SS:ID   -0.000993186:0.000835838:0.629422:0.11065:360270:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115838 ES:SE:LP:AF:SS:ID   -6.98354e-05:0.000789791:0.0317314:0.115838:360270:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097291 ES:SE:LP:AF:SS:ID   0.000410903:0.000887997:0.191412:0.097291:360270:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157019    ES:SE:LP:AF:SS:ID   -0.0019896:0.00211785:0.45904:0.0157019:360270:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173076   ES:SE:LP:AF:SS:ID   -0.000838587:0.00625754:0.0489575:0.00173076:360270:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564472    ES:SE:LP:AF:SS:ID   -0.00096291:0.00110043:0.418441:0.0564472:360270:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121741 ES:SE:LP:AF:SS:ID   0.00027624:0.000749039:0.147347:0.121741:360270:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121173 ES:SE:LP:AF:SS:ID   1.29017e-05:0.000799017:0.00563137:0.121173:360270:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120969 ES:SE:LP:AF:SS:ID   0.000203764:0.00074944:0.104739:0.120969:360270:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00579066   ES:SE:LP:AF:SS:ID   0.0019973:0.00342713:0.251786:0.00579066:360270:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187672   ES:SE:LP:AF:SS:ID   -0.00500031:0.00647832:0.356348:0.00187672:360270:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869737 ES:SE:LP:AF:SS:ID   4.23876e-05:0.000738827:0.0203383:0.869737:360270:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153102   ES:SE:LP:AF:SS:ID   -0.000463873:0.00668715:0.0247075:0.00153102:360270:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122922 ES:SE:LP:AF:SS:ID   0.000123675:0.000731721:0.0625914:0.122922:360270:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142717 ES:SE:LP:AF:SS:ID   -8.48591e-05:0.000723257:0.0425848:0.142717:360270:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123037 ES:SE:LP:AF:SS:ID   0.000132136:0.000730703:0.0672736:0.123037:360270:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87088  ES:SE:LP:AF:SS:ID   -0.000126186:0.000712044:0.0658355:0.87088:360270:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875466 ES:SE:LP:AF:SS:ID   -1.21282e-05:0.000723858:0.0058448:0.875466:360270:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128643 ES:SE:LP:AF:SS:ID   0.000112325:0.00071382:0.0580098:0.128643:360270:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363464    ES:SE:LP:AF:SS:ID   -0.000106407:0.00129531:0.0294072:0.0363464:360270:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870474 ES:SE:LP:AF:SS:ID   -6.1467e-05:0.000711305:0.0309864:0.870474:360270:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870579 ES:SE:LP:AF:SS:ID   -4.2198e-05:0.00071163:0.021037:0.870579:360270:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870471 ES:SE:LP:AF:SS:ID   -5.80071e-05:0.000711278:0.0291875:0.870471:360270:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00505041   ES:SE:LP:AF:SS:ID   0.00174836:0.0036491:0.199384:0.00505041:360270:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501736   ES:SE:LP:AF:SS:ID   0.00180326:0.00365886:0.206125:0.00501736:360270:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558719   ES:SE:LP:AF:SS:ID   0.0018518:0.00353633:0.22147:0.00558719:360270:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870552 ES:SE:LP:AF:SS:ID   -0.000103978:0.000710022:0.0537585:0.870552:360270:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125993 ES:SE:LP:AF:SS:ID   0.000212823:0.000724485:0.114105:0.125993:360270:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870117 ES:SE:LP:AF:SS:ID   -8.15171e-05:0.000708314:0.0417339:0.870117:360270:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869406 ES:SE:LP:AF:SS:ID   -1.41252e-05:0.00070767:0.0069718:0.869406:360270:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870272 ES:SE:LP:AF:SS:ID   -9.30555e-05:0.000708925:0.0479019:0.870272:360270:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870278 ES:SE:LP:AF:SS:ID   -9.22637e-05:0.000708976:0.0474701:0.870278:360270:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   -9.39034e-05:0.000708998:0.0483556:0.870287:360270:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870728 ES:SE:LP:AF:SS:ID   -0.000112187:0.000710802:0.0581955:0.870728:360270:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988323    ES:SE:LP:AF:SS:ID   0.000373514:0.000826053:0.18632:0.0988323:360270:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647755   ES:SE:LP:AF:SS:ID   0.00345561:0.00319471:0.55377:0.00647755:360270:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874628 ES:SE:LP:AF:SS:ID   -7.31853e-05:0.000721406:0.0365923:0.874628:360270:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864021 ES:SE:LP:AF:SS:ID   -8.17207e-05:0.00070744:0.0418969:0.864021:360270:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869415 ES:SE:LP:AF:SS:ID   -7.55224e-05:0.000714307:0.0382003:0.869415:360270:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866359 ES:SE:LP:AF:SS:ID   7.50333e-05:0.000714447:0.0379348:0.866359:360270:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987912    ES:SE:LP:AF:SS:ID   0.000345916:0.000855327:0.163739:0.0987912:360270:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871548 ES:SE:LP:AF:SS:ID   8.52385e-05:0.000722598:0.0428248:0.871548:360270:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871548 ES:SE:LP:AF:SS:ID   8.52111e-05:0.000722598:0.04281:0.871548:360270:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871547 ES:SE:LP:AF:SS:ID   8.44096e-05:0.000722611:0.0423884:0.871547:360270:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871922 ES:SE:LP:AF:SS:ID   4.10579e-05:0.000723025:0.0201263:0.871922:360270:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12557  ES:SE:LP:AF:SS:ID   0.000140474:0.000723584:0.0725937:0.12557:360270:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105413 ES:SE:LP:AF:SS:ID   0.000391042:0.000787785:0.20787:0.105413:360270:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855359 ES:SE:LP:AF:SS:ID   -5.56737e-05:0.000707165:0.028145:0.855359:360270:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165156   ES:SE:LP:AF:SS:ID   -0.0036876:0.00627104:0.254529:0.00165156:360270:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838382 ES:SE:LP:AF:SS:ID   0.000617917:0.000696831:0.425722:0.838382:360270:rs376645387