Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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-22644_irnt/ukb-d-22644_irnt.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-22644_irnt/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 14:52:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22644_irnt/ukb-d-22644_irnt.vcf.gz ...
Read summary statistics for 13518067 SNPs.
Dropped 12625 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, 1283495 SNPs remain.
After merging with regression SNP LD, 1283495 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0182 (0.0215)
Lambda GC: 1.0145
Mean Chi^2: 1.0122
Intercept: 1.0053 (0.006)
Ratio: 0.4348 (0.4901)
Analysis finished at Mon Nov 25 14:55:38 2019
Total time elapsed: 2.0m:45.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0055,
    "mean_EFFECT": -0,
    "n": 19344,
    "n_snps": 13518067,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1249313,
    "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": 552110,
    "n_est": 19496.7905,
    "ratio_se_n": 1.0039,
    "mean_diff": 8.8493e-06,
    "ratio_diff": 1.0052,
    "sd_y_est1": 1.0005,
    "sd_y_est2": 1.0045,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283495,
    "ldsc_nsnp_merge_regression_ld": 1283495,
    "ldsc_observed_scale_h2_beta": 0.0182,
    "ldsc_observed_scale_h2_se": 0.0215,
    "ldsc_intercept_beta": 1.0053,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0145,
    "ldsc_mean_chisq": 1.0122,
    "ldsc_ratio": 0.4344
}

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 13506104 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56936 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33305 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051591e+00 6.184429e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 <U+2587><U+2585><U+2585><U+2582><U+2582>
numeric POS 0 1.0000000 NA NA NA NA NA 7.901667e+07 5.591774e+07 3.02000e+02 3.291582e+07 7.012260e+07 1.148508e+08 2.492309e+08 <U+2587><U+2586><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.040000e-05 5.858070e-02 -7.24328e-01 -1.561840e-02 -2.360000e-05 1.557890e-02 8.029800e-01 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.0000000 NA NA NA NA NA 4.218750e-02 4.060540e-02 8.03460e-03 1.215180e-02 2.223910e-02 6.041100e-02 2.102500e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.989888e-01 2.891294e-01 4.00000e-07 2.485290e-01 4.988213e-01 7.493246e-01 1.000000e+00 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.989805e-01 2.891344e-01 4.00000e-07 2.485148e-01 4.988136e-01 7.493200e-01 9.999999e-01 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric AF 0 1.0000000 NA NA NA NA NA 1.917197e-01 2.546392e-01 1.00010e-03 7.664000e-03 6.104960e-02 2.971300e-01 9.990000e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric AF_reference 552110 0.9591576 NA NA NA NA NA 1.970220e-01 2.472593e-01 0.00000e+00 5.790700e-03 8.526360e-02 3.095050e-01 1.000000e+00 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric N 0 1.0000000 NA NA NA NA NA 1.934400e+04 0.000000e+00 1.93440e+04 1.934400e+04 1.934400e+04 1.934400e+04 1.934400e+04 <U+2581><U+2581><U+2587><U+2581><U+2581>

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0148878 0.0178831 0.4051334 0.4051230 0.1107020 0.1894970 19344
1 693731 rs12238997 A G 0.0282449 0.0170006 0.0966474 0.0966319 0.1152340 0.1417730 19344
1 707522 rs371890604 G C 0.0254847 0.0191678 0.1836788 0.1836640 0.0962635 0.1293930 19344
1 717587 rs144155419 G A -0.0027588 0.0452159 0.9513491 0.9513479 0.0158854 0.0045926 19344
1 723329 rs189787166 A T 0.0209535 0.1253300 0.8672250 0.8672232 0.0019501 0.0003994 19344
1 730087 rs148120343 T C 0.0644538 0.0233290 0.0057357 0.0057305 0.0571540 0.0127796 19344
1 731718 rs142557973 T C 0.0206161 0.0161181 0.2008908 0.2008741 0.1215310 0.1543530 19344
1 732032 rs61770163 A C 0.0297159 0.0171607 0.0833566 0.0833403 0.1218520 0.1555510 19344
1 734349 rs141242758 T C 0.0209047 0.0161314 0.1950271 0.1950095 0.1207780 0.1525560 19344
1 740284 rs61770167 C T 0.1117210 0.0758378 0.1407239 0.1407087 0.0053920 0.0023962 19344
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0156436 0.0177542 0.3782614 0.3782523 0.0565041 0.0309934 19344
23 154923374 rs111332691 T A 0.0261281 0.0194748 0.1797289 0.1797139 0.0450010 0.0116556 19344
23 154925045 rs509981 C T 0.0200243 0.0094930 0.0349253 0.0349128 0.2401350 0.3634440 19344
23 154925895 rs538470 C T 0.0193977 0.0097035 0.0456173 0.0456030 0.2367070 0.3634440 19344
23 154927581 rs644138 G A 0.0141006 0.0088932 0.1128579 0.1128418 0.2972620 0.4635760 19344
23 154929412 rs557132 C T 0.0196400 0.0094973 0.0386581 0.0386441 0.2399540 0.3568210 19344
23 154929637 rs35185538 CT C 0.0206412 0.0098916 0.0369241 0.0369107 0.2260380 0.3011920 19344
23 154929952 rs4012982 CAA C 0.0226718 0.0100024 0.0234234 0.0234125 0.2338080 0.3165560 19344
23 154930230 rs781880 A G 0.0193350 0.0094890 0.0416016 0.0415879 0.2404670 0.3618540 19344
23 154930487 rs781879 T A 0.0356821 0.0326953 0.2751313 0.2751178 0.0189242 0.1263580 19344

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110702 ES:SE:LP:AF:SS:ID   0.0148878:0.0178831:0.392402:0.110702:19344:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115234 ES:SE:LP:AF:SS:ID   0.0282449:0.0170006:1.01481:0.115234:19344:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0962635    ES:SE:LP:AF:SS:ID   0.0254847:0.0191678:0.735941:0.0962635:19344:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158854    ES:SE:LP:AF:SS:ID   -0.00275881:0.0452159:0.0216601:0.0158854:19344:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00195014   ES:SE:LP:AF:SS:ID   0.0209535:0.12533:0.0618682:0.00195014:19344:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.057154 ES:SE:LP:AF:SS:ID   0.0644538:0.023329:2.24141:0.057154:19344:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121531 ES:SE:LP:AF:SS:ID   0.0206161:0.0161181:0.69704:0.121531:19344:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121852 ES:SE:LP:AF:SS:ID   0.0297159:0.0171607:1.07906:0.121852:19344:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120778 ES:SE:LP:AF:SS:ID   0.0209047:0.0161314:0.709905:0.120778:19344:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00539195   ES:SE:LP:AF:SS:ID   0.111721:0.0758378:0.851632:0.00539195:19344:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00166075   ES:SE:LP:AF:SS:ID   -0.122945:0.148436:0.389843:0.00166075:19344:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869434 ES:SE:LP:AF:SS:ID   -0.0148794:0.0158508:0.458561:0.869434:19344:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00178461   ES:SE:LP:AF:SS:ID   -0.0352408:0.130927:0.103581:0.00178461:19344:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123203 ES:SE:LP:AF:SS:ID   0.0184337:0.0157059:0.618816:0.123203:19344:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14271  ES:SE:LP:AF:SS:ID   0.0186607:0.0155745:0.636633:0.14271:19344:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123359 ES:SE:LP:AF:SS:ID   0.0182433:0.0156839:0.611242:0.123359:19344:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870502 ES:SE:LP:AF:SS:ID   -0.0136214:0.0152883:0.428345:0.870502:19344:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875238 ES:SE:LP:AF:SS:ID   -0.0164246:0.015548:0.536395:0.875238:19344:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128982 ES:SE:LP:AF:SS:ID   0.0149142:0.0153411:0.480202:0.128982:19344:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0362128    ES:SE:LP:AF:SS:ID   -0.0274191:0.0276755:0.492376:0.0362128:19344:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870198 ES:SE:LP:AF:SS:ID   -0.013607:0.0152826:0.427962:0.870198:19344:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870307 ES:SE:LP:AF:SS:ID   -0.0125939:0.0152877:0.387145:0.870307:19344:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870198 ES:SE:LP:AF:SS:ID   -0.0135817:0.0152818:0.426958:0.870198:19344:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00505431   ES:SE:LP:AF:SS:ID   -0.0367607:0.0782991:0.194687:0.00505431:19344:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00502583   ES:SE:LP:AF:SS:ID   -0.0372961:0.0784883:0.197456:0.00502583:19344:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00577379   ES:SE:LP:AF:SS:ID   -0.0163925:0.0733187:0.0845543:0.00577379:19344:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870199 ES:SE:LP:AF:SS:ID   -0.0134726:0.0152453:0.423821:0.870199:19344:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12628  ES:SE:LP:AF:SS:ID   0.0148868:0.0155571:0.470284:0.12628:19344:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869675 ES:SE:LP:AF:SS:ID   -0.0133973:0.0152035:0.422254:0.869675:19344:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869227 ES:SE:LP:AF:SS:ID   -0.012182:0.0152056:0.373604:0.869227:19344:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869864 ES:SE:LP:AF:SS:ID   -0.0131272:0.0152145:0.410885:0.869864:19344:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869868 ES:SE:LP:AF:SS:ID   -0.0131333:0.0152154:0.411099:0.869868:19344:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869869 ES:SE:LP:AF:SS:ID   -0.0131013:0.0152155:0.409806:0.869869:19344:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870364 ES:SE:LP:AF:SS:ID   -0.013238:0.0152615:0.413717:0.870364:19344:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0980185    ES:SE:LP:AF:SS:ID   0.0185193:0.0178317:0.524295:0.0980185:19344:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00674111   ES:SE:LP:AF:SS:ID   -0.028528:0.0661058:0.176478:0.00674111:19344:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874396 ES:SE:LP:AF:SS:ID   -0.0134591:0.0154942:0.41449:0.874396:19344:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863824 ES:SE:LP:AF:SS:ID   -0.0131068:0.0151902:0.410909:0.863824:19344:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869119 ES:SE:LP:AF:SS:ID   -0.0123545:0.0153361:0.37624:0.869119:19344:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865954 ES:SE:LP:AF:SS:ID   -0.0152108:0.0153421:0.492846:0.865954:19344:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0982834    ES:SE:LP:AF:SS:ID   0.026073:0.0184264:0.803849:0.0982834:19344:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871366 ES:SE:LP:AF:SS:ID   -0.0168389:0.0155317:0.555481:0.871366:19344:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871366 ES:SE:LP:AF:SS:ID   -0.0168388:0.0155317:0.555477:0.871366:19344:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871363 ES:SE:LP:AF:SS:ID   -0.0168359:0.0155317:0.555346:0.871363:19344:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871665 ES:SE:LP:AF:SS:ID   -0.0172255:0.015534:0.572691:0.871665:19344:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125886 ES:SE:LP:AF:SS:ID   0.0151614:0.0155506:0.482029:0.125886:19344:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105288 ES:SE:LP:AF:SS:ID   0.019149:0.016876:0.590879:0.105288:19344:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855131 ES:SE:LP:AF:SS:ID   -0.0116266:0.0151352:0.354198:0.855131:19344:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00182232   ES:SE:LP:AF:SS:ID   -0.00210512:0.126327:0.00581267:0.00182232:19344:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838267 ES:SE:LP:AF:SS:ID   0.00975866:0.0149218:0.289774:0.838267:19344:rs376645387