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_6/ukb-d-1747_6.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_6/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 16:55:35 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1747_6/ukb-d-1747_6.vcf.gz ...
Read summary statistics for 11847797 SNPs.
Dropped 10241 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, 1282914 SNPs remain.
After merging with regression SNP LD, 1282914 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0041 (0.0016)
Lambda GC: 1.0279
Mean Chi^2: 1.0373
Intercept: 1.0094 (0.0057)
Ratio: 0.2507 (0.1535)
Analysis finished at Mon Nov 25 16:57:25 2019
Total time elapsed: 1.0m:49.88s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9486,
    "inflation_factor": 1.0236,
    "mean_EFFECT": 2.2605e-07,
    "n": 360270,
    "n_snps": 11847797,
    "n_clumped_hits": 3,
    "n_p_sig": 1077,
    "n_mono": 0,
    "n_ns": 1177682,
    "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": 269402,
    "n_est": 360950.9236,
    "ratio_se_n": 1.0009,
    "mean_diff": 2.0198e-06,
    "ratio_diff": 9.4926,
    "sd_y_est1": 0.1111,
    "sd_y_est2": 0.1112,
    "r2_sum1": 0,
    "r2_sum2": 0.0013,
    "r2_sum3": 0.0013,
    "r2_sum4": 0.0013,
    "ldsc_nsnp_merge_refpanel_ld": 1282914,
    "ldsc_nsnp_merge_regression_ld": 1282914,
    "ldsc_observed_scale_h2_beta": 0.0041,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0094,
    "ldsc_intercept_se": 0.0057,
    "ldsc_lambda_gc": 1.0279,
    "ldsc_mean_chisq": 1.0373,
    "ldsc_ratio": 0.252
}
 

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 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 11838174 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 53043 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32028 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.070554e+00 6.184215e+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 7.887925e+07 5.598227e+07 3.0200e+02 3.268211e+07 6.990278e+07 1.147444e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.000000e-07 9.959000e-04 -9.8575e-03 -3.509000e-04 -2.200000e-06 3.432000e-04 1.502690e-02 ▁▇▆▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.674000e-04 6.228000e-04 2.1530e-04 2.998000e-04 4.696000e-04 1.053700e-03 3.678300e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.964295e-01 2.897119e-01 0.0000e+00 2.445907e-01 4.949793e-01 7.472553e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.964291e-01 2.897122e-01 0.0000e+00 2.445902e-01 4.949784e-01 7.472546e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.173058e-01 2.598209e-01 2.7896e-03 1.647150e-02 9.617550e-02 3.461210e-01 9.972100e-01 ▇▂▁▁▁
numeric AF_reference 269402 0.9772614 NA NA NA NA NA 2.184304e-01 2.512364e-01 0.0000e+00 1.317890e-02 1.154150e-01 3.474440e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.602700e+05 0.000000e+00 3.6027e+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 0.0004849 0.0004586 0.2903033 0.2903023 0.1106500 0.1894970 360270
1 693731 rs12238997 A G 0.0004477 0.0004333 0.3014512 0.3014502 0.1158380 0.1417730 360270
1 707522 rs371890604 G C 0.0004680 0.0004872 0.3367480 0.3367477 0.0972910 0.1293930 360270
1 717587 rs144155419 G A -0.0007755 0.0011619 0.5044998 0.5044998 0.0157019 0.0045926 360270
1 730087 rs148120343 T C 0.0015537 0.0006037 0.0100675 0.0100670 0.0564472 0.0127796 360270
1 731718 rs142557973 T C 0.0004724 0.0004109 0.2502718 0.2502714 0.1217410 0.1543530 360270
1 732032 rs61770163 A C 0.0004512 0.0004384 0.3032892 0.3032870 0.1211730 0.1555510 360270
1 734349 rs141242758 T C 0.0004815 0.0004112 0.2416078 0.2416071 0.1209690 0.1525560 360270
1 740284 rs61770167 C T 0.0002252 0.0018802 0.9046479 0.9046477 0.0057907 0.0023962 360270
1 749963 rs529266287 T TAA -0.0002295 0.0004053 0.5712984 0.5712973 0.8697370 0.7641770 360270
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0002786 0.0004750 0.5575246 0.5575247 0.0561460 0.0309934 360270
23 154923374 rs111332691 T A -0.0001880 0.0005219 0.7187320 0.7187322 0.0447845 0.0116556 360270
23 154925045 rs509981 C T -0.0001609 0.0002511 0.5215885 0.5215867 0.2456300 0.3634440 360270
23 154925895 rs538470 C T -0.0001367 0.0002569 0.5945043 0.5945025 0.2419380 0.3634440 360270
23 154927581 rs644138 G A -0.0000269 0.0002362 0.9094261 0.9094262 0.3021610 0.4635760 360270
23 154929412 rs557132 C T -0.0001549 0.0002512 0.5373076 0.5373082 0.2454820 0.3568210 360270
23 154929637 rs35185538 CT C -0.0000603 0.0002621 0.8180631 0.8180634 0.2297100 0.3011920 360270
23 154929952 rs4012982 CAA C -0.0001655 0.0002642 0.5308979 0.5308995 0.2394580 0.3165560 360270
23 154930230 rs781880 A G -0.0001528 0.0002511 0.5428289 0.5428306 0.2458930 0.3618540 360270
23 154930487 rs781879 T A -0.0008249 0.0008611 0.3381123 0.3381115 0.0195732 0.1263580 360270

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11065  ES:SE:LP:AF:SS:ID   0.000484903:0.000458555:0.537148:0.11065:360270:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115838 ES:SE:LP:AF:SS:ID   0.000447733:0.000433292:0.520783:0.115838:360270:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097291 ES:SE:LP:AF:SS:ID   0.000467981:0.00048717:0.472695:0.097291:360270:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157019    ES:SE:LP:AF:SS:ID   -0.000775476:0.00116189:0.297139:0.0157019:360270:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0564472    ES:SE:LP:AF:SS:ID   0.00155366:0.00060371:1.99708:0.0564472:360270:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121741 ES:SE:LP:AF:SS:ID   0.000472448:0.000410935:0.601588:0.121741:360270:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121173 ES:SE:LP:AF:SS:ID   0.000451246:0.000438354:0.518143:0.121173:360270:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120969 ES:SE:LP:AF:SS:ID   0.000481454:0.000411155:0.616889:0.120969:360270:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00579066   ES:SE:LP:AF:SS:ID   0.000225231:0.00188018:0.0435204:0.00579066:360270:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869737 ES:SE:LP:AF:SS:ID   -0.000229476:0.000405333:0.243137:0.869737:360270:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.122922 ES:SE:LP:AF:SS:ID   0.000283438:0.000401435:0.318623:0.122922:360270:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142717 ES:SE:LP:AF:SS:ID   0.00037145:0.000396791:0.456922:0.142717:360270:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123037 ES:SE:LP:AF:SS:ID   0.000281338:0.000400876:0.316233:0.123037:360270:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87088  ES:SE:LP:AF:SS:ID   -0.000238082:0.00039064:0.265828:0.87088:360270:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875466 ES:SE:LP:AF:SS:ID   -0.000322332:0.000397121:0.379884:0.875466:360270:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128643 ES:SE:LP:AF:SS:ID   0.000260491:0.000391614:0.295901:0.128643:360270:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363464    ES:SE:LP:AF:SS:ID   0.00044393:0.000710631:0.27395:0.0363464:360270:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870474 ES:SE:LP:AF:SS:ID   -0.000236517:0.000390234:0.264038:0.870474:360270:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870579 ES:SE:LP:AF:SS:ID   -0.000249884:0.000390413:0.282213:0.870579:360270:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870471 ES:SE:LP:AF:SS:ID   -0.000232481:0.00039022:0.258589:0.870471:360270:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00505041   ES:SE:LP:AF:SS:ID   0.000559158:0.00200196:0.107899:0.00505041:360270:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501736   ES:SE:LP:AF:SS:ID   0.000595728:0.00200731:0.115411:0.00501736:360270:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558719   ES:SE:LP:AF:SS:ID   -0.0029506:0.00194009:0.891787:0.00558719:360270:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870552 ES:SE:LP:AF:SS:ID   -0.000239606:0.00038953:0.268831:0.870552:360270:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125993 ES:SE:LP:AF:SS:ID   0.000290128:0.000397465:0.332152:0.125993:360270:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870117 ES:SE:LP:AF:SS:ID   -0.000266679:0.000388593:0.307555:0.870117:360270:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869406 ES:SE:LP:AF:SS:ID   -0.000247983:0.00038824:0.281502:0.869406:360270:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870272 ES:SE:LP:AF:SS:ID   -0.000271249:0.000388928:0.313779:0.870272:360270:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870278 ES:SE:LP:AF:SS:ID   -0.000270985:0.000388956:0.313371:0.870278:360270:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   -0.000270575:0.000388968:0.312769:0.870287:360270:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870728 ES:SE:LP:AF:SS:ID   -0.000227456:0.000389958:0.252042:0.870728:360270:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988323    ES:SE:LP:AF:SS:ID   0.00036068:0.000453187:0.370483:0.0988323:360270:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647755   ES:SE:LP:AF:SS:ID   -0.00244158:0.00175267:0.786211:0.00647755:360270:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874628 ES:SE:LP:AF:SS:ID   -0.000205478:0.000395776:0.219224:0.874628:360270:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864021 ES:SE:LP:AF:SS:ID   -0.000215989:0.000388114:0.238175:0.864021:360270:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869415 ES:SE:LP:AF:SS:ID   -0.00023248:0.000391881:0.25726:0.869415:360270:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866359 ES:SE:LP:AF:SS:ID   -0.00026317:0.000391958:0.299339:0.866359:360270:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987912    ES:SE:LP:AF:SS:ID   0.00021453:0.000469247:0.188732:0.0987912:360270:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871548 ES:SE:LP:AF:SS:ID   -0.00024527:0.00039643:0.270741:0.871548:360270:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871548 ES:SE:LP:AF:SS:ID   -0.000245314:0.00039643:0.270801:0.871548:360270:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871547 ES:SE:LP:AF:SS:ID   -0.000245458:0.000396437:0.270988:0.871547:360270:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871922 ES:SE:LP:AF:SS:ID   -0.000221234:0.000396664:0.238805:0.871922:360270:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12557  ES:SE:LP:AF:SS:ID   0.000242525:0.000396971:0.26661:0.12557:360270:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105413 ES:SE:LP:AF:SS:ID   0.000616841:0.000432191:0.813858:0.105413:360270:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855359 ES:SE:LP:AF:SS:ID   -0.00040014:0.000387962:0.519476:0.855359:360270:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838382 ES:SE:LP:AF:SS:ID   -0.000291057:0.000382294:0.350225:0.838382:360270:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763384 ES:SE:LP:AF:SS:ID   -0.000335142:0.000307631:0.559146:0.763384:360270:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105878 ES:SE:LP:AF:SS:ID   0.000301708:0.000423946:0.321781:0.105878:360270:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00768736   ES:SE:LP:AF:SS:ID   0.00147352:0.0015743:0.456824:0.00768736:360270:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.128946 ES:SE:LP:AF:SS:ID   0.000279066:0.000391415:0.322514:0.128946:360270:rs762168062