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-K11_OTHDIG/ukb-d-K11_OTHDIG.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-K11_OTHDIG/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 15:35:37 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-K11_OTHDIG/ukb-d-K11_OTHDIG.vcf.gz ...
Read summary statistics for 12651918 SNPs.
Dropped 11375 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, 1283287 SNPs remain.
After merging with regression SNP LD, 1283287 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0008 (0.0012)
Lambda GC: 1.0178
Mean Chi^2: 1.014
Intercept: 1.0085 (0.0068)
Ratio: 0.6024 (0.4819)
Analysis finished at Mon Nov 25 15:37:40 2019
Total time elapsed: 2.0m:3.38s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9505,
    "inflation_factor": 1.0221,
    "mean_EFFECT": -3.8873e-07,
    "n": 361194,
    "n_snps": 12651918,
    "n_clumped_hits": 3,
    "n_p_sig": 5115,
    "n_mono": 0,
    "n_ns": 1213555,
    "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": 368214,
    "n_est": 362237.7391,
    "ratio_se_n": 1.0014,
    "mean_diff": -3.259e-06,
    "ratio_diff": 3.8206,
    "sd_y_est1": 0.1389,
    "sd_y_est2": 0.1391,
    "r2_sum1": 0,
    "r2_sum2": 0.0006,
    "r2_sum3": 0.0006,
    "r2_sum4": 0.0006,
    "ldsc_nsnp_merge_refpanel_ld": 1283287,
    "ldsc_nsnp_merge_regression_ld": 1283287,
    "ldsc_observed_scale_h2_beta": 0.0008,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0085,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0178,
    "ldsc_mean_chisq": 1.014,
    "ldsc_ratio": 0.6071
}

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 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 12641185 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 54987 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32679 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.061795e+00 6.185740e+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 7.895728e+07 5.595443e+07 3.02000e+02 3.279602e+07 7.002059e+07 1.148102e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.000000e-07 1.520100e-03 -1.69656e-02 -4.749000e-04 -4.400000e-06 4.576000e-04 2.163210e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.129200e-03 1.001600e-03 2.68800e-04 3.817000e-04 6.428000e-04 1.587300e-03 5.611100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.961187e-01 2.900309e-01 0.00000e+00 2.436332e-01 4.953110e-01 7.473964e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.961182e-01 2.900311e-01 0.00000e+00 2.436326e-01 4.953101e-01 7.473970e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.041378e-01 2.574219e-01 1.76980e-03 1.136480e-02 7.768210e-02 3.217440e-01 9.982300e-01 ▇▂▁▁▁
numeric AF_reference 368214 0.9708966 NA NA NA NA NA 2.068477e-01 2.493009e-01 0.00000e+00 8.386600e-03 9.904150e-02 3.274760e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.611940e+05 0.000000e+00 3.61194e+05 3.611940e+05 3.611940e+05 3.611940e+05 3.611940e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0004780 0.0005726 0.4038490 0.4038482 0.1106400 0.1894970 361194
1 693731 rs12238997 A G 0.0003831 0.0005410 0.4789035 0.4789023 0.1158300 0.1417730 361194
1 707522 rs371890604 G C 0.0002366 0.0006082 0.6972508 0.6972501 0.0973034 0.1293930 361194
1 717587 rs144155419 G A 0.0012479 0.0014514 0.3899034 0.3899023 0.0156880 0.0045926 361194
1 730087 rs148120343 T C -0.0005634 0.0007537 0.4547618 0.4547618 0.0564602 0.0127796 361194
1 731718 rs142557973 T C 0.0004321 0.0005131 0.3996989 0.3996988 0.1217380 0.1543530 361194
1 732032 rs61770163 A C 0.0000005 0.0005473 0.9992010 0.9992011 0.1211710 0.1555510 361194
1 734349 rs141242758 T C 0.0004784 0.0005134 0.3514471 0.3514463 0.1209650 0.1525560 361194
1 740284 rs61770167 C T 0.0005884 0.0023487 0.8021940 0.8021931 0.0057851 0.0023962 361194
1 742813 rs112573343 C T 0.0015995 0.0044358 0.7184094 0.7184097 0.0018779 0.1030350 361194
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0006636 0.0005928 0.2629517 0.2629508 0.0561667 0.0309934 361194
23 154923374 rs111332691 T A 0.0013486 0.0006515 0.0384459 0.0384453 0.0447862 0.0116556 361194
23 154925045 rs509981 C T 0.0000475 0.0003135 0.8794539 0.8794541 0.2456060 0.3634440 361194
23 154925895 rs538470 C T 0.0001353 0.0003207 0.6731471 0.6731473 0.2419150 0.3634440 361194
23 154927581 rs644138 G A 0.0001912 0.0002948 0.5165163 0.5165156 0.3021620 0.4635760 361194
23 154929412 rs557132 C T 0.0000477 0.0003136 0.8789640 0.8789640 0.2454590 0.3568210 361194
23 154929637 rs35185538 CT C 0.0002190 0.0003272 0.5034229 0.5034225 0.2296970 0.3011920 361194
23 154929952 rs4012982 CAA C 0.0001237 0.0003298 0.7076655 0.7076638 0.2394250 0.3165560 361194
23 154930230 rs781880 A G 0.0000393 0.0003135 0.9003101 0.9003096 0.2458690 0.3618540 361194
23 154930487 rs781879 T A -0.0018153 0.0010755 0.0914240 0.0914243 0.0195623 0.1263580 361194

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11064  ES:SE:LP:AF:SS:ID   0.000477975:0.000572584:0.393781:0.11064:361194:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11583  ES:SE:LP:AF:SS:ID   0.000383081:0.000541022:0.319752:0.11583:361194:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973034    ES:SE:LP:AF:SS:ID   0.000236619:0.00060822:0.156611:0.0973034:361194:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015688 ES:SE:LP:AF:SS:ID   0.00124788:0.00145137:0.409043:0.015688:361194:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0564602    ES:SE:LP:AF:SS:ID   -0.000563402:0.000753715:0.342216:0.0564602:361194:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121738 ES:SE:LP:AF:SS:ID   0.000432117:0.000513106:0.398267:0.121738:361194:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121171 ES:SE:LP:AF:SS:ID   5.48025e-07:0.000547327:0.00034714:0.121171:361194:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120965 ES:SE:LP:AF:SS:ID   0.000478363:0.000513382:0.45414:0.120965:361194:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578512   ES:SE:LP:AF:SS:ID   0.00058838:0.00234873:0.0957206:0.00578512:361194:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187787   ES:SE:LP:AF:SS:ID   0.00159949:0.00443582:0.143628:0.00187787:361194:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869742 ES:SE:LP:AF:SS:ID   -0.000416918:0.000506113:0.387137:0.869742:361194:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.122916 ES:SE:LP:AF:SS:ID   0.000371191:0.000501239:0.338217:0.122916:361194:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142712 ES:SE:LP:AF:SS:ID   0.000554234:0.000495447:0.579569:0.142712:361194:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123031 ES:SE:LP:AF:SS:ID   0.000386518:0.000500541:0.356551:0.123031:361194:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87089  ES:SE:LP:AF:SS:ID   -0.000386162:0.000487761:0.368015:0.87089:361194:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875472 ES:SE:LP:AF:SS:ID   -0.000469434:0.000495843:0.463728:0.875472:361194:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.000409797:0.000488984:0.395775:0.128631:361194:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363613    ES:SE:LP:AF:SS:ID   -0.00146065:0.000887127:1.00147:0.0363613:361194:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   -0.000394318:0.000487254:0.378448:0.870484:361194:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870589 ES:SE:LP:AF:SS:ID   -0.000388444:0.000487476:0.371059:0.870589:361194:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870481 ES:SE:LP:AF:SS:ID   -0.000393611:0.000487236:0.377599:0.870481:361194:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504367   ES:SE:LP:AF:SS:ID   0.00233059:0.00250138:0.454097:0.00504367:361194:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501064   ES:SE:LP:AF:SS:ID   0.00238914:0.00250808:0.467495:0.00501064:361194:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558665   ES:SE:LP:AF:SS:ID   -0.00354166:0.00242264:0.842335:0.00558665:361194:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870563 ES:SE:LP:AF:SS:ID   -0.000402454:0.000486378:0.389359:0.870563:361194:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125985 ES:SE:LP:AF:SS:ID   0.000385436:0.000496284:0.359152:0.125985:361194:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870127 ES:SE:LP:AF:SS:ID   -0.00036532:0.000485208:0.345341:0.870127:361194:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869414 ES:SE:LP:AF:SS:ID   -0.000380054:0.000484765:0.363469:0.869414:361194:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870281 ES:SE:LP:AF:SS:ID   -0.000390425:0.000485625:0.375287:0.870281:361194:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   -0.000390073:0.00048566:0.37482:0.870287:361194:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870295 ES:SE:LP:AF:SS:ID   -0.000391188:0.000485675:0.376173:0.870295:361194:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870739 ES:SE:LP:AF:SS:ID   -0.000409559:0.000486911:0.397645:0.870739:361194:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988442    ES:SE:LP:AF:SS:ID   0.000475788:0.000565821:0.39749:0.0988442:361194:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647588   ES:SE:LP:AF:SS:ID   -0.00249754:0.00218862:0.595493:0.00647588:361194:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874635 ES:SE:LP:AF:SS:ID   -0.00046638:0.000494168:0.461817:0.874635:361194:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864027 ES:SE:LP:AF:SS:ID   -0.000299201:0.000484605:0.270056:0.864027:361194:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869425 ES:SE:LP:AF:SS:ID   -0.000436924:0.00048931:0.429585:0.869425:361194:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866371 ES:SE:LP:AF:SS:ID   -0.000424319:0.000489409:0.413479:0.866371:361194:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987831    ES:SE:LP:AF:SS:ID   0.000988225:0.000585913:1.03776:0.0987831:361194:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871556 ES:SE:LP:AF:SS:ID   -0.000448123:0.000494985:0.437359:0.871556:361194:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871556 ES:SE:LP:AF:SS:ID   -0.000448113:0.000494985:0.437346:0.871556:361194:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871555 ES:SE:LP:AF:SS:ID   -0.000448313:0.000494994:0.437589:0.871555:361194:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871929 ES:SE:LP:AF:SS:ID   -0.000494642:0.000495277:0.497667:0.871929:361194:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125562 ES:SE:LP:AF:SS:ID   0.000427849:0.000495667:0.411124:0.125562:361194:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105428 ES:SE:LP:AF:SS:ID   0.000300379:0.000539602:0.238256:0.105428:361194:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855376 ES:SE:LP:AF:SS:ID   -0.000395707:0.000484423:0.382991:0.855376:361194:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838358 ES:SE:LP:AF:SS:ID   -0.000177453:0.000477244:0.148729:0.838358:361194:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763351 ES:SE:LP:AF:SS:ID   -0.000177831:0.000384092:0.191538:0.763351:361194:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105921 ES:SE:LP:AF:SS:ID   -0.000174296:0.000529186:0.129666:0.105921:361194:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00768395   ES:SE:LP:AF:SS:ID   -0.00178613:0.00196616:0.439316:0.00768395:361194:rs12562811