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-20118_16/ukb-d-20118_16.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-20118_16/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 16:51:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20118_16/ukb-d-20118_16.vcf.gz ...
Read summary statistics for 9637419 SNPs.
Dropped 7234 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, 1274784 SNPs remain.
After merging with regression SNP LD, 1274784 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0006 (0.0013)
Lambda GC: 1.0167
Mean Chi^2: 1.0217
Intercept: 1.0176 (0.0063)
Ratio: 0.8145 (0.29)
Analysis finished at Mon Nov 25 16:52:54 2019
Total time elapsed: 1.0m:24.79s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9397,
    "inflation_factor": 1.0115,
    "mean_EFFECT": 5.2687e-07,
    "n": 357712,
    "n_snps": 9637419,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1059829,
    "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": 192213,
    "n_est": 357561.7978,
    "ratio_se_n": 0.9998,
    "mean_diff": 8.6418e-06,
    "ratio_diff": 57.9227,
    "sd_y_est1": 0.0584,
    "sd_y_est2": 0.0584,
    "r2_sum1": 3.0082e-07,
    "r2_sum2": 0.0001,
    "r2_sum3": 0.0001,
    "r2_sum4": 0.0001,
    "ldsc_nsnp_merge_refpanel_ld": 1274784,
    "ldsc_nsnp_merge_regression_ld": 1274784,
    "ldsc_observed_scale_h2_beta": 0.0006,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0176,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0167,
    "ldsc_mean_chisq": 1.0217,
    "ldsc_ratio": 0.8111
}

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 9630733 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 46906 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29633 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079178e+00 6.175238e+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 7.873443e+07 5.611640e+07 3.02000e+02 3.242755e+07 6.961619e+07 1.147457e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.000000e-07 3.100000e-04 -2.96290e-03 -1.509000e-04 -1.600000e-06 1.476000e-04 3.645600e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.677000e-04 1.509000e-04 1.13700e-04 1.511000e-04 2.009000e-04 3.419000e-04 8.212000e-04 ▇▂▂▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.979396e-01 2.898349e-01 0.00000e+00 2.461263e-01 4.975411e-01 7.492884e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.979392e-01 2.898352e-01 0.00000e+00 2.461257e-01 4.975410e-01 7.492885e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.631498e-01 2.628483e-01 1.01626e-02 4.527510e-02 1.616710e-01 4.185380e-01 9.898370e-01 ▇▂▂▁▁
numeric AF_reference 192213 0.9800556 NA NA NA NA NA 2.625955e-01 2.536581e-01 0.00000e+00 5.151760e-02 1.767170e-01 4.139380e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.577120e+05 0.000000e+00 3.57712e+05 3.577120e+05 3.577120e+05 3.577120e+05 3.577120e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0002660 0.0002420 0.2717321 0.2717315 0.1107240 0.1894970 357712
1 693731 rs12238997 A G 0.0001453 0.0002287 0.5252765 0.5252761 0.1158980 0.1417730 357712
1 707522 rs371890604 G C -0.0000419 0.0002571 0.8706771 0.8706775 0.0973675 0.1293930 357712
1 717587 rs144155419 G A -0.0000059 0.0006137 0.9923460 0.9923463 0.0156859 0.0045926 357712
1 730087 rs148120343 T C 0.0003044 0.0003185 0.3391720 0.3391709 0.0565115 0.0127796 357712
1 731718 rs142557973 T C 0.0000921 0.0002169 0.6711630 0.6711634 0.1218030 0.1543530 357712
1 732032 rs61770163 A C 0.0001196 0.0002314 0.6053353 0.6053338 0.1212390 0.1555510 357712
1 734349 rs141242758 T C 0.0000905 0.0002170 0.6767449 0.6767451 0.1210310 0.1525560 357712
1 749963 rs529266287 T TAA -0.0002331 0.0002139 0.2758449 0.2758436 0.8696580 0.7641770 357712
1 751343 rs28544273 T A 0.0002209 0.0002119 0.2971112 0.2971114 0.1230010 0.2426120 357712
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0003747 0.0002507 0.1349451 0.1349438 0.0561556 0.0309934 357712
23 154923374 rs111332691 T A 0.0000659 0.0002756 0.8108830 0.8108825 0.0447734 0.0116556 357712
23 154925045 rs509981 C T -0.0002490 0.0001326 0.0603587 0.0603579 0.2456140 0.3634440 357712
23 154925895 rs538470 C T -0.0002586 0.0001356 0.0565353 0.0565347 0.2419220 0.3634440 357712
23 154927581 rs644138 G A -0.0001254 0.0001247 0.3142418 0.3142417 0.3021610 0.4635760 357712
23 154929412 rs557132 C T -0.0002476 0.0001326 0.0618543 0.0618543 0.2454660 0.3568210 357712
23 154929637 rs35185538 CT C -0.0002600 0.0001384 0.0602462 0.0602464 0.2296840 0.3011920 357712
23 154929952 rs4012982 CAA C -0.0002217 0.0001395 0.1118840 0.1118843 0.2394310 0.3165560 357712
23 154930230 rs781880 A G -0.0002485 0.0001326 0.0608429 0.0608413 0.2458740 0.3618540 357712
23 154930487 rs781879 T A -0.0002138 0.0004549 0.6384340 0.6384344 0.0195614 0.1263580 357712

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110724 ES:SE:LP:AF:SS:ID   0.000265997:0.000242017:0.565859:0.110724:357712:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115898 ES:SE:LP:AF:SS:ID   0.000145276:0.000228697:0.279612:0.115898:357712:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973675    ES:SE:LP:AF:SS:ID   -4.18552e-05:0.000257099:0.0601429:0.0973675:357712:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156859    ES:SE:LP:AF:SS:ID   -5.88726e-06:0.000613725:0.00333688:0.0156859:357712:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0565115    ES:SE:LP:AF:SS:ID   0.000304441:0.000318518:0.46958:0.0565115:357712:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121803 ES:SE:LP:AF:SS:ID   9.20853e-05:0.0002169:0.173172:0.121803:357712:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121239 ES:SE:LP:AF:SS:ID   0.000119562:0.000231375:0.218004:0.121239:357712:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121031 ES:SE:LP:AF:SS:ID   9.04763e-05:0.000217017:0.169575:0.121031:357712:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869658 ES:SE:LP:AF:SS:ID   -0.000233128:0.000213937:0.559335:0.869658:357712:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123001 ES:SE:LP:AF:SS:ID   0.00022091:0.000211874:0.527081:0.123001:357712:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142797 ES:SE:LP:AF:SS:ID   0.000167646:0.000209422:0.373236:0.142797:357712:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123117 ES:SE:LP:AF:SS:ID   0.000224446:0.000211579:0.53944:0.123117:357712:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870799 ES:SE:LP:AF:SS:ID   -0.000181508:0.000206175:0.421745:0.870799:357712:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875387 ES:SE:LP:AF:SS:ID   -0.000200489:0.000209598:0.470055:0.875387:357712:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128727 ES:SE:LP:AF:SS:ID   0.000203407:0.000206687:0.488046:0.128727:357712:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363491    ES:SE:LP:AF:SS:ID   0.00016071:0.000375146:0.174986:0.0363491:357712:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87039  ES:SE:LP:AF:SS:ID   -0.000177253:0.00020596:0.409549:0.87039:357712:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870496 ES:SE:LP:AF:SS:ID   -0.000168855:0.000206054:0.384556:0.870496:357712:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870389 ES:SE:LP:AF:SS:ID   -0.000177528:0.000205953:0.410388:0.870389:357712:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.870472 ES:SE:LP:AF:SS:ID   -0.000198209:0.000205592:0.474951:0.870472:357712:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126072 ES:SE:LP:AF:SS:ID   0.000213698:0.000209781:0.510942:0.126072:357712:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870038 ES:SE:LP:AF:SS:ID   -0.000201583:0.0002051:0.487208:0.870038:357712:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869322 ES:SE:LP:AF:SS:ID   -0.000199947:0.000204908:0.48258:0.869322:357712:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87019  ES:SE:LP:AF:SS:ID   -0.000197188:0.000205274:0.472695:0.87019:357712:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870196 ES:SE:LP:AF:SS:ID   -0.000197087:0.000205288:0.47233:0.870196:357712:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870205 ES:SE:LP:AF:SS:ID   -0.000197205:0.000205295:0.472683:0.870205:357712:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870648 ES:SE:LP:AF:SS:ID   -0.000189239:0.000205816:0.446292:0.870648:357712:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0989131    ES:SE:LP:AF:SS:ID   0.000192263:0.00023917:0.375235:0.0989131:357712:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.874551 ES:SE:LP:AF:SS:ID   -0.000187206:0.000208889:0.431627:0.874551:357712:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863924 ES:SE:LP:AF:SS:ID   -0.000153711:0.000204837:0.34389:0.863924:357712:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869335 ES:SE:LP:AF:SS:ID   -0.000190054:0.000206832:0.445927:0.869335:357712:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866284 ES:SE:LP:AF:SS:ID   -0.000173957:0.000206872:0.397497:0.866284:357712:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0988419    ES:SE:LP:AF:SS:ID   0.000218362:0.000247695:0.4225:0.0988419:357712:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871475 ES:SE:LP:AF:SS:ID   -0.000141903:0.000209231:0.303086:0.871475:357712:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871475 ES:SE:LP:AF:SS:ID   -0.0001419:0.000209231:0.303079:0.871475:357712:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871474 ES:SE:LP:AF:SS:ID   -0.00014182:0.000209235:0.30286:0.871474:357712:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871846 ES:SE:LP:AF:SS:ID   -0.00014859:0.000209354:0.320701:0.871846:357712:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125652 ES:SE:LP:AF:SS:ID   0.000201132:0.000209517:0.472284:0.125652:357712:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10551  ES:SE:LP:AF:SS:ID   0.000248889:0.000228068:0.560437:0.10551:357712:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855281 ES:SE:LP:AF:SS:ID   -0.000219294:0.000204764:0.546393:0.855281:357712:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838262 ES:SE:LP:AF:SS:ID   -0.000256564:0.000201762:0.691412:0.838262:357712:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763181 ES:SE:LP:AF:SS:ID   -0.000135591:0.000162362:0.393993:0.763181:357712:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105997 ES:SE:LP:AF:SS:ID   3.60703e-05:0.000223679:0.0595388:0.105997:357712:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129033 ES:SE:LP:AF:SS:ID   0.000186804:0.000206582:0.436686:0.129033:357712:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.128701 ES:SE:LP:AF:SS:ID   0.000201089:0.000206392:0.481611:0.128701:357712:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.10529  ES:SE:LP:AF:SS:ID   4.89548e-05:0.000225367:0.0819513:0.10529:357712:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.104344 ES:SE:LP:AF:SS:ID   5.47634e-05:0.000227169:0.0917821:0.104344:357712:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.829989 ES:SE:LP:AF:SS:ID   -0.000134813:0.0002011:0.298762:0.829989:357712:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.870025 ES:SE:LP:AF:SS:ID   -0.000184622:0.000205468:0.433095:0.870025:357712:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128763 ES:SE:LP:AF:SS:ID   0.00019855:0.000206293:0.473897:0.128763:357712:rs59066358