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-3446_2/ukb-d-3446_2.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-3446_2/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 16:45:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-3446_2/ukb-d-3446_2.vcf.gz ...
Read summary statistics for 12492317 SNPs.
Dropped 11147 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, 1283238 SNPs remain.
After merging with regression SNP LD, 1283238 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0272 (0.0155)
Lambda GC: 1.0213
Mean Chi^2: 1.0211
Intercept: 1.0061 (0.0062)
Ratio: 0.2891 (0.291)
Analysis finished at Mon Nov 25 16:47:04 2019
Total time elapsed: 2.0m:4.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9501,
    "inflation_factor": 1.0198,
    "mean_EFFECT": 3.9806e-07,
    "n": 27583,
    "n_snps": 12492317,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1206319,
    "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": 346003,
    "n_est": 27755.3947,
    "ratio_se_n": 1.0031,
    "mean_diff": 1.1033e-07,
    "ratio_diff": 0.246,
    "sd_y_est1": 0.4147,
    "sd_y_est2": 0.416,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283238,
    "ldsc_nsnp_merge_regression_ld": 1283238,
    "ldsc_observed_scale_h2_beta": 0.0272,
    "ldsc_observed_scale_h2_se": 0.0155,
    "ldsc_intercept_beta": 1.0061,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0213,
    "ldsc_mean_chisq": 1.0211,
    "ldsc_ratio": 0.2891
}
 

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 12481803 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 54580 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32544 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.062930e+00 6.184820e+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 7.893381e+07 5.595730e+07 3.02000e+02 3.277016e+07 6.997330e+07 1.147887e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.000000e-07 1.571430e-02 -1.87234e-01 -4.990400e-03 -2.020000e-05 4.938600e-03 2.052450e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.181160e-02 1.031370e-02 2.84070e-03 4.110100e-03 6.815500e-03 1.652250e-02 6.199870e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.967164e-01 2.893900e-01 0.00000e+00 2.449689e-01 4.957937e-01 7.471039e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.967106e-01 2.893935e-01 0.00000e+00 2.449586e-01 4.957893e-01 7.471011e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.066095e-01 2.579040e-01 1.93240e-03 1.222360e-02 8.118230e-02 3.262980e-01 9.980670e-01 ▇▂▁▁▁
numeric AF_reference 346003 0.9723027 NA NA NA NA NA 2.089732e-01 2.496866e-01 0.00000e+00 9.185300e-03 1.020370e-01 3.312700e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.758300e+04 0.000000e+00 2.75830e+04 2.758300e+04 2.758300e+04 2.758300e+04 2.758300e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0021314 0.0061942 0.7307806 0.7307781 0.1100050 0.1894970 27583
1 693731 rs12238997 A G 0.0041980 0.0058496 0.4729781 0.4729717 0.1148600 0.1417730 27583
1 707522 rs371890604 G C 0.0058876 0.0066150 0.3734573 0.3734488 0.0955608 0.1293930 27583
1 717587 rs144155419 G A 0.0059288 0.0155301 0.7026434 0.7026404 0.0159292 0.0045926 27583
1 730087 rs148120343 T C -0.0010217 0.0081167 0.8998319 0.8998310 0.0568384 0.0127796 27583
1 731718 rs142557973 T C 0.0048085 0.0055266 0.3842758 0.3842690 0.1214620 0.1543530 27583
1 732032 rs61770163 A C 0.0088158 0.0059120 0.1359280 0.1359167 0.1199310 0.1555510 27583
1 734349 rs141242758 T C 0.0051697 0.0055307 0.3499387 0.3499302 0.1206270 0.1525560 27583
1 740284 rs61770167 C T -0.0095202 0.0258219 0.7123624 0.7123599 0.0056100 0.0023962 27583
1 749963 rs529266287 T TAA -0.0069421 0.0054743 0.2047618 0.2047514 0.8706360 0.7641770 27583
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0049858 0.0062935 0.4282408 0.4282345 0.0555972 0.0309934 27583
23 154923374 rs111332691 T A 0.0018529 0.0070652 0.7931238 0.7931204 0.0431788 0.0116556 27583
23 154925045 rs509981 C T -0.0025878 0.0033151 0.4350448 0.4350377 0.2466770 0.3634440 27583
23 154925895 rs538470 C T -0.0029699 0.0033869 0.3805572 0.3805496 0.2435400 0.3634440 27583
23 154927581 rs644138 G A -0.0035154 0.0031197 0.2598232 0.2598134 0.3026300 0.4635760 27583
23 154929412 rs557132 C T -0.0024244 0.0033162 0.4647335 0.4647283 0.2464860 0.3568210 27583
23 154929637 rs35185538 CT C 0.0005274 0.0034590 0.8788290 0.8788274 0.2309790 0.3011920 27583
23 154929952 rs4012982 CAA C -0.0016766 0.0034840 0.6303707 0.6303672 0.2408190 0.3165560 27583
23 154930230 rs781880 A G -0.0027316 0.0033143 0.4098463 0.4098382 0.2471770 0.3618540 27583
23 154930487 rs781879 T A 0.0015412 0.0117053 0.8952499 0.8952492 0.0186709 0.1263580 27583

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110005 ES:SE:LP:AF:SS:ID   0.00213137:0.00619421:0.136213:0.110005:27583:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11486  ES:SE:LP:AF:SS:ID   0.004198:0.00584963:0.325159:0.11486:27583:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0955608    ES:SE:LP:AF:SS:ID   0.00588756:0.006615:0.427759:0.0955608:27583:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0159292    ES:SE:LP:AF:SS:ID   0.00592875:0.0155301:0.153265:0.0159292:27583:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0568384    ES:SE:LP:AF:SS:ID   -0.00102169:0.00811671:0.0458386:0.0568384:27583:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121462 ES:SE:LP:AF:SS:ID   0.00480846:0.0055266:0.415357:0.121462:27583:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.119931 ES:SE:LP:AF:SS:ID   0.0088158:0.005912:0.866691:0.119931:27583:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120627 ES:SE:LP:AF:SS:ID   0.0051697:0.00553072:0.456008:0.120627:27583:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00560995   ES:SE:LP:AF:SS:ID   -0.00952024:0.0258219:0.147299:0.00560995:27583:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.870636 ES:SE:LP:AF:SS:ID   -0.0069421:0.00547428:0.688751:0.870636:27583:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.122504 ES:SE:LP:AF:SS:ID   0.00578402:0.00540741:0.54548:0.122504:27583:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143502 ES:SE:LP:AF:SS:ID   0.00524306:0.00531965:0.489004:0.143502:27583:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12255  ES:SE:LP:AF:SS:ID   0.00575456:0.00540152:0.542539:0.12255:27583:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.871449 ES:SE:LP:AF:SS:ID   -0.00405339:0.00526672:0.35504:0.871449:27583:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87633  ES:SE:LP:AF:SS:ID   -0.00542706:0.00535268:0.50774:0.87633:27583:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128345 ES:SE:LP:AF:SS:ID   0.00421892:0.00527187:0.373084:0.128345:27583:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365805    ES:SE:LP:AF:SS:ID   0.016878:0.00956415:1.11001:0.0365805:27583:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.871139 ES:SE:LP:AF:SS:ID   -0.003994:0.00525953:0.349081:0.871139:27583:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.871234 ES:SE:LP:AF:SS:ID   -0.00404048:0.00526104:0.354094:0.871234:27583:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.871125 ES:SE:LP:AF:SS:ID   -0.00398681:0.0052591:0.348325:0.871125:27583:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00482863   ES:SE:LP:AF:SS:ID   -0.00823674:0.0276601:0.115845:0.00482863:27583:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00478129   ES:SE:LP:AF:SS:ID   -0.00768792:0.0277694:0.10685:0.00478129:27583:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00563853   ES:SE:LP:AF:SS:ID   0.00444319:0.0261658:0.0629026:0.00563853:27583:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.871121 ES:SE:LP:AF:SS:ID   -0.00476492:0.0052523:0.438534:0.871121:27583:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125557 ES:SE:LP:AF:SS:ID   0.00572692:0.0053586:0.544852:0.125557:27583:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870699 ES:SE:LP:AF:SS:ID   -0.00533298:0.00524094:0.510189:0.870699:27583:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.870017 ES:SE:LP:AF:SS:ID   -0.00419218:0.0052344:0.373452:0.870017:27583:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870903 ES:SE:LP:AF:SS:ID   -0.00469699:0.0052459:0.431095:0.870903:27583:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870912 ES:SE:LP:AF:SS:ID   -0.00469302:0.00524631:0.430576:0.870912:27583:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870912 ES:SE:LP:AF:SS:ID   -0.00469769:0.00524625:0.431141:0.870912:27583:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.871332 ES:SE:LP:AF:SS:ID   -0.00478607:0.00525887:0.440357:0.871332:27583:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0978378    ES:SE:LP:AF:SS:ID   0.00641695:0.00612943:0.529954:0.0978378:27583:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00629586   ES:SE:LP:AF:SS:ID   0.0145942:0.0241685:0.262851:0.00629586:27583:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.875526 ES:SE:LP:AF:SS:ID   -0.00546175:0.00533856:0.51388:0.875526:27583:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864818 ES:SE:LP:AF:SS:ID   -0.00459184:0.00523457:0.419786:0.864818:27583:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.870067 ES:SE:LP:AF:SS:ID   -0.00447259:0.00528771:0.400503:0.870067:27583:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866746 ES:SE:LP:AF:SS:ID   -0.00437494:0.00528596:0.389474:0.866746:27583:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0982305    ES:SE:LP:AF:SS:ID   0.00712475:0.00632079:0.585578:0.0982305:27583:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.872339 ES:SE:LP:AF:SS:ID   -0.00497024:0.0053495:0.452417:0.872339:27583:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.872339 ES:SE:LP:AF:SS:ID   -0.00497078:0.00534951:0.452481:0.872339:27583:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.872354 ES:SE:LP:AF:SS:ID   -0.00503901:0.0053506:0.460521:0.872354:27583:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87266  ES:SE:LP:AF:SS:ID   -0.00492262:0.00535329:0.44634:0.87266:27583:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125094 ES:SE:LP:AF:SS:ID   0.00559021:0.00534913:0.528707:0.125094:27583:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.104772 ES:SE:LP:AF:SS:ID   0.00515215:0.0058365:0.42322:0.104772:27583:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855328 ES:SE:LP:AF:SS:ID   -0.00583338:0.00523035:0.57719:0.855328:27583:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.835305 ES:SE:LP:AF:SS:ID   -0.00606045:0.00513511:0.623549:0.835305:27583:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.761034 ES:SE:LP:AF:SS:ID   -0.0056699:0.00415122:0.764472:0.761034:27583:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108726 ES:SE:LP:AF:SS:ID   0.00547099:0.00568068:0.474292:0.108726:27583:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00755971   ES:SE:LP:AF:SS:ID   0.0130803:0.0216017:0.263733:0.00755971:27583:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.00521696:0.00527394:0.491368:0.128631:27583:rs762168062