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-5832_3/ukb-d-5832_3.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-5832_3/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-5832_3/ukb-d-5832_3.vcf.gz ...
Read summary statistics for 13502209 SNPs.
Dropped 12589 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, 1283485 SNPs remain.
After merging with regression SNP LD, 1283485 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0173 (0.0297)
Lambda GC: 1.0153
Mean Chi^2: 1.0133
Intercept: 1.0081 (0.0065)
Ratio: 0.6097 (0.4885)
Analysis finished at Mon Nov 25 16:57:26 2019
Total time elapsed: 2.0m:16.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0184,
    "mean_EFFECT": -0,
    "n": 15090,
    "n_snps": 13502209,
    "n_clumped_hits": 0,
    "n_p_sig": 7,
    "n_mono": 0,
    "n_ns": 1248774,
    "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": 548168,
    "n_est": 15182.3326,
    "ratio_se_n": 1.0031,
    "mean_diff": -0.0001,
    "ratio_diff": 309.0986,
    "sd_y_est1": 0.3523,
    "sd_y_est2": 0.3534,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283485,
    "ldsc_nsnp_merge_regression_ld": 1283485,
    "ldsc_observed_scale_h2_beta": 0.0173,
    "ldsc_observed_scale_h2_se": 0.0297,
    "ldsc_intercept_beta": 1.0081,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0153,
    "ldsc_mean_chisq": 1.0133,
    "ldsc_ratio": 0.609
}

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 TRUE
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 13490281 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56937 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33288 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051239e+00 6.184409e+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 7.902165e+07 5.591995e+07 3.0200e+02 3.292012e+07 7.012817e+07 1.148596e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.720000e-05 2.332660e-02 -3.6437e-01 -6.114900e-03 8.070000e-05 6.373300e-03 2.509830e-01 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.676610e-02 1.611410e-02 3.3622e-03 4.841200e-03 8.844200e-03 2.400590e-02 9.136810e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.974543e-01 2.888418e-01 0.0000e+00 2.466982e-01 4.960917e-01 7.473930e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.974437e-01 2.888481e-01 0.0000e+00 2.466802e-01 4.960816e-01 7.473880e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.919311e-01 2.546668e-01 1.0000e-03 7.726600e-03 6.138840e-02 2.975920e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 548168 0.9594016 NA NA NA NA NA 1.971733e-01 2.472841e-01 0.0000e+00 5.790700e-03 8.546330e-02 3.097040e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.509000e+04 0.000000e+00 1.5090e+04 1.509000e+04 1.509000e+04 1.509000e+04 1.509000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0079383 0.0069433 0.2529298 0.2529120 0.1141820 0.1894970 15090
1 693731 rs12238997 A G 0.0084664 0.0066414 0.2024002 0.2023809 0.1191660 0.1417730 15090
1 707522 rs371890604 G C 0.0097339 0.0074377 0.1906492 0.1906286 0.1002410 0.1293930 15090
1 717587 rs144155419 G A 0.0160305 0.0177937 0.3676512 0.3676368 0.0160220 0.0045926 15090
1 723329 rs189787166 A T 0.0020976 0.0524048 0.9680730 0.9680725 0.0017156 0.0003994 15090
1 730087 rs148120343 T C 0.0232904 0.0092025 0.0113875 0.0113774 0.0583691 0.0127796 15090
1 731718 rs142557973 T C 0.0076117 0.0062929 0.2264650 0.2264465 0.1251690 0.1543530 15090
1 732032 rs61770163 A C 0.0047670 0.0067071 0.4772622 0.4772504 0.1249330 0.1555510 15090
1 734349 rs141242758 T C 0.0074638 0.0062983 0.2360141 0.2359951 0.1244210 0.1525560 15090
1 740284 rs61770167 C T -0.0475779 0.0286775 0.0971225 0.0971022 0.0059080 0.0023962 15090
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0011793 0.0078942 0.8812461 0.8812439 0.0505719 0.0309934 15090
23 154923374 rs111332691 T A -0.0202676 0.0082207 0.0136956 0.0136842 0.0447647 0.0116556 15090
23 154925045 rs509981 C T 0.0023533 0.0039144 0.5477230 0.5477152 0.2480630 0.3634440 15090
23 154925895 rs538470 C T 0.0019224 0.0039992 0.6307380 0.6307299 0.2443550 0.3634440 15090
23 154927581 rs644138 G A 0.0020663 0.0037088 0.5774428 0.5774348 0.2990900 0.4635760 15090
23 154929412 rs557132 C T 0.0024106 0.0039155 0.5381260 0.5381157 0.2479080 0.3568210 15090
23 154929637 rs35185538 CT C -0.0013590 0.0040772 0.7388955 0.7388926 0.2322830 0.3011920 15090
23 154929952 rs4012982 CAA C 0.0028124 0.0041268 0.4955609 0.4955501 0.2412620 0.3165560 15090
23 154930230 rs781880 A G 0.0022816 0.0039141 0.5599458 0.5599378 0.2483550 0.3618540 15090
23 154930487 rs781879 T A -0.0028581 0.0137486 0.8353210 0.8353181 0.0189192 0.1263580 15090

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.114182 ES:SE:LP:AF:SS:ID   0.00793831:0.0069433:0.597:0.114182:15090:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.119166 ES:SE:LP:AF:SS:ID   0.00846644:0.0066414:0.693789:0.119166:15090:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100241 ES:SE:LP:AF:SS:ID   0.00973388:0.0074377:0.719765:0.100241:15090:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.016022 ES:SE:LP:AF:SS:ID   0.0160305:0.0177937:0.434564:0.016022:15090:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00171559   ES:SE:LP:AF:SS:ID   0.00209755:0.0524048:0.0140919:0.00171559:15090:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0583691    ES:SE:LP:AF:SS:ID   0.0232904:0.00920246:1.94357:0.0583691:15090:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.125169 ES:SE:LP:AF:SS:ID   0.00761171:0.00629294:0.644999:0.125169:15090:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124933 ES:SE:LP:AF:SS:ID   0.00476695:0.0067071:0.321243:0.124933:15090:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.124421 ES:SE:LP:AF:SS:ID   0.00746383:0.00629829:0.627062:0.124421:15090:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00590795   ES:SE:LP:AF:SS:ID   -0.0475779:0.0286775:1.01268:0.00590795:15090:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00240401   ES:SE:LP:AF:SS:ID   0.015342:0.047351:0.127297:0.00240401:15090:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.865823 ES:SE:LP:AF:SS:ID   -0.00714346:0.00619168:0.604439:0.865823:15090:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00167791   ES:SE:LP:AF:SS:ID   0.0255882:0.0535929:0.198565:0.00167791:15090:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.1264   ES:SE:LP:AF:SS:ID   0.00613992:0.00613788:0.498713:0.1264:15090:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145816 ES:SE:LP:AF:SS:ID   0.00803396:0.00608899:0.728049:0.145816:15090:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12651  ES:SE:LP:AF:SS:ID   0.00640075:0.00612693:0.52844:0.12651:15090:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867093 ES:SE:LP:AF:SS:ID   -0.00600009:0.00597294:0.501508:0.867093:15090:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.871738 ES:SE:LP:AF:SS:ID   -0.00620967:0.0060597:0.514992:0.871738:15090:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132054 ES:SE:LP:AF:SS:ID   0.00631954:0.00599624:0.534709:0.132054:15090:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363486    ES:SE:LP:AF:SS:ID   -0.0148262:0.010999:0.750335:0.0363486:15090:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.866748 ES:SE:LP:AF:SS:ID   -0.00609791:0.0059678:0.513016:0.866748:15090:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86685  ES:SE:LP:AF:SS:ID   -0.00624836:0.00597116:0.529616:0.86685:15090:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866753 ES:SE:LP:AF:SS:ID   -0.00611865:0.00596747:0.515384:0.866753:15090:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00501358   ES:SE:LP:AF:SS:ID   0.0213208:0.0314945:0.302391:0.00501358:15090:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00497979   ES:SE:LP:AF:SS:ID   0.0207171:0.0315707:0.290987:0.00497979:15090:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00609493   ES:SE:LP:AF:SS:ID   0.0215458:0.0289354:0.340545:0.00609493:15090:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86685  ES:SE:LP:AF:SS:ID   -0.00614478:0.00595801:0.519427:0.86685:15090:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129382 ES:SE:LP:AF:SS:ID   0.00712975:0.00608154:0.617855:0.129382:15090:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866435 ES:SE:LP:AF:SS:ID   -0.00640068:0.00594331:0.550495:0.866435:15090:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.865611 ES:SE:LP:AF:SS:ID   -0.00666479:0.00593391:0.582723:0.865611:15090:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866618 ES:SE:LP:AF:SS:ID   -0.00621126:0.00595057:0.527843:0.866618:15090:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866626 ES:SE:LP:AF:SS:ID   -0.00622448:0.00595109:0.529287:0.866626:15090:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866628 ES:SE:LP:AF:SS:ID   -0.00621326:0.00595098:0.528021:0.866628:15090:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.866976 ES:SE:LP:AF:SS:ID   -0.00627923:0.00596311:0.534094:0.866976:15090:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.101528 ES:SE:LP:AF:SS:ID   0.00629435:0.00692876:0.439302:0.101528:15090:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00702517   ES:SE:LP:AF:SS:ID   0.0055751:0.0258647:0.0812658:0.00702517:15090:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.870911 ES:SE:LP:AF:SS:ID   -0.00675267:0.0060456:0.578345:0.870911:15090:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860219 ES:SE:LP:AF:SS:ID   -0.0063391:0.00593575:0.544304:0.860219:15090:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.865558 ES:SE:LP:AF:SS:ID   -0.00644368:0.00599186:0.549428:0.865558:15090:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.861992 ES:SE:LP:AF:SS:ID   -0.00577404:0.00598658:0.475199:0.861992:15090:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100985 ES:SE:LP:AF:SS:ID   0.0079009:0.00722569:0.561907:0.100985:15090:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.867571 ES:SE:LP:AF:SS:ID   -0.00665985:0.00605769:0.566054:0.867571:15090:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.867571 ES:SE:LP:AF:SS:ID   -0.00666002:0.00605769:0.566075:0.867571:15090:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.867567 ES:SE:LP:AF:SS:ID   -0.00665617:0.00605772:0.565628:0.867567:15090:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868076 ES:SE:LP:AF:SS:ID   -0.00633379:0.00606222:0.528512:0.868076:15090:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.129005 ES:SE:LP:AF:SS:ID   0.00662155:0.00606982:0.560139:0.129005:15090:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107962 ES:SE:LP:AF:SS:ID   0.00549556:0.00662456:0.390627:0.107962:15090:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852157 ES:SE:LP:AF:SS:ID   -0.0084578:0.00593114:0.812792:0.852157:15090:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00161619   ES:SE:LP:AF:SS:ID   0.00544538:0.0528894:0.0371583:0.00161619:15090:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837669 ES:SE:LP:AF:SS:ID   -0.00192707:0.00593114:0.127695:0.837669:15090:rs376645387