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-1448_1/ukb-d-1448_1.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-1448_1/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 17:05:36 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1448_1/ukb-d-1448_1.vcf.gz ...
Read summary statistics for 13586246 SNPs.
Dropped 12712 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0579 (0.0024)
Lambda GC: 1.3455
Mean Chi^2: 1.4226
Intercept: 1.0253 (0.0082)
Ratio: 0.0598 (0.0193)
Analysis finished at Mon Nov 25 17:07:30 2019
Total time elapsed: 1.0m:54.6s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2186,
    "mean_EFFECT": 0,
    "n": 348424,
    "n_snps": 13586246,
    "n_clumped_hits": 22,
    "n_p_sig": 1244,
    "n_mono": 0,
    "n_ns": 1251794,
    "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": 569238,
    "n_est": 349806.3655,
    "ratio_se_n": 1.002,
    "mean_diff": 0,
    "ratio_diff": 59.185,
    "sd_y_est1": 0.4362,
    "sd_y_est2": 0.4371,
    "r2_sum1": 0.0004,
    "r2_sum2": 0.0024,
    "r2_sum3": 0.0024,
    "r2_sum4": 0.0024,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0579,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0253,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.3455,
    "ldsc_mean_chisq": 1.4226,
    "ldsc_ratio": 0.0599
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 13574198 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57084 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051300e+00 6.184955e+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 7.902529e+07 5.591512e+07 3.02000e+02 3.293080e+07 7.013840e+07 1.148599e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.230000e-05 6.268300e-03 -7.33302e-02 -1.813300e-03 8.800000e-06 1.840000e-03 8.263580e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.391300e-03 4.236000e-03 8.57100e-04 1.250300e-03 2.303800e-03 6.310300e-03 2.139200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.677659e-01 2.975165e-01 0.00000e+00 2.020752e-01 4.565328e-01 7.255043e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.677654e-01 2.975168e-01 0.00000e+00 2.020739e-01 4.565332e-01 7.255050e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908060e-01 2.544035e-01 1.00000e-03 7.430600e-03 6.003200e-02 2.953218e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569238 0.9581019 NA NA NA NA NA 1.963368e-01 2.471016e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.484240e+05 0.000000e+00 3.48424e+05 3.484240e+05 3.484240e+05 3.484240e+05 3.484240e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0021554 0.0018307 0.2390622 0.2390594 0.1105660 0.1894970 348424
1 693731 rs12238997 A G -0.0000103 0.0017296 0.9952500 0.9952500 0.1157510 0.1417730 348424
1 707522 rs371890604 G C -0.0004142 0.0019443 0.8313221 0.8313227 0.0972257 0.1293930 348424
1 717587 rs144155419 G A -0.0042385 0.0046466 0.3616854 0.3616846 0.0156497 0.0045926 348424
1 723329 rs189787166 A T -0.0016753 0.0136864 0.9025771 0.9025762 0.0017334 0.0003994 348424
1 730087 rs148120343 T C -0.0016554 0.0024103 0.4922027 0.4922018 0.0564055 0.0127796 348424
1 731718 rs142557973 T C -0.0004968 0.0016404 0.7619860 0.7619861 0.1216490 0.1543530 348424
1 732032 rs61770163 A C -0.0005426 0.0017498 0.7565036 0.7565043 0.1210850 0.1555510 348424
1 734349 rs141242758 T C -0.0006944 0.0016413 0.6722426 0.6722426 0.1208790 0.1525560 348424
1 740284 rs61770167 C T 0.0151778 0.0074994 0.0429833 0.0429831 0.0057964 0.0023962 348424
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0011608 0.0018922 0.5395591 0.5395587 0.0560551 0.0309934 348424
23 154923374 rs111332691 T A -0.0010444 0.0020799 0.6155495 0.6155491 0.0446955 0.0116556 348424
23 154925045 rs509981 C T -0.0037356 0.0009992 0.0001852 0.0001851 0.2457460 0.3634440 348424
23 154925895 rs538470 C T -0.0036229 0.0010221 0.0003935 0.0003934 0.2420510 0.3634440 348424
23 154927581 rs644138 G A -0.0030286 0.0009399 0.0012720 0.0012719 0.3021920 0.4635760 348424
23 154929412 rs557132 C T -0.0037356 0.0009995 0.0001859 0.0001859 0.2455970 0.3568210 348424
23 154929637 rs35185538 CT C -0.0026604 0.0010432 0.0107627 0.0107620 0.2297910 0.3011920 348424
23 154929952 rs4012982 CAA C -0.0039127 0.0010512 0.0001975 0.0001975 0.2395410 0.3165560 348424
23 154930230 rs781880 A G -0.0037095 0.0009993 0.0002058 0.0002057 0.2460140 0.3618540 348424
23 154930487 rs781879 T A -0.0055613 0.0034273 0.1046661 0.1046656 0.0195723 0.1263580 348424

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110566 ES:SE:LP:AF:SS:ID   -0.00215537:0.00183071:0.621489:0.110566:348424:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115751 ES:SE:LP:AF:SS:ID   -1.02969e-05:0.00172962:0.00206781:0.115751:348424:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972257    ES:SE:LP:AF:SS:ID   -0.000414153:0.00194433:0.0802307:0.0972257:348424:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156497    ES:SE:LP:AF:SS:ID   -0.00423846:0.00464662:0.441669:0.0156497:348424:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173336   ES:SE:LP:AF:SS:ID   -0.00167532:0.0136864:0.0445157:0.00173336:348424:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564055    ES:SE:LP:AF:SS:ID   -0.0016554:0.00241027:0.307856:0.0564055:348424:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121649 ES:SE:LP:AF:SS:ID   -0.000496825:0.00164037:0.118053:0.121649:348424:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121085 ES:SE:LP:AF:SS:ID   -0.000542559:0.00174977:0.121189:0.121085:348424:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120879 ES:SE:LP:AF:SS:ID   -0.00069438:0.00164128:0.172474:0.120879:348424:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00579641   ES:SE:LP:AF:SS:ID   0.0151778:0.00749938:1.3667:0.00579641:348424:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188398   ES:SE:LP:AF:SS:ID   0.00671041:0.0141323:0.197287:0.00188398:348424:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869838 ES:SE:LP:AF:SS:ID   0.000600654:0.00161807:0.14845:0.869838:348424:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153811   ES:SE:LP:AF:SS:ID   -0.00638044:0.0146008:0.179065:0.00153811:348424:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122804 ES:SE:LP:AF:SS:ID   -0.000612658:0.00160267:0.153503:0.122804:348424:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142609 ES:SE:LP:AF:SS:ID   -0.00144404:0.00158397:0.44135:0.142609:348424:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12292  ES:SE:LP:AF:SS:ID   -0.000632586:0.00160043:0.159486:0.12292:348424:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870978 ES:SE:LP:AF:SS:ID   0.000782642:0.00155944:0.210591:0.870978:348424:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87557  ES:SE:LP:AF:SS:ID   0.000258499:0.00158536:0.0602427:0.87557:348424:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128532 ES:SE:LP:AF:SS:ID   -0.000866876:0.00156334:0.237145:0.128532:348424:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036325 ES:SE:LP:AF:SS:ID   -0.00181047:0.00283703:0.28119:0.036325:348424:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870576 ES:SE:LP:AF:SS:ID   0.000782795:0.00155785:0.210893:0.870576:348424:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87068  ES:SE:LP:AF:SS:ID   0.000754561:0.00155857:0.201841:0.87068:348424:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870573 ES:SE:LP:AF:SS:ID   0.000765802:0.00155779:0.205507:0.870573:348424:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504313   ES:SE:LP:AF:SS:ID   -0.00232945:0.00799591:0.113059:0.00504313:348424:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501098   ES:SE:LP:AF:SS:ID   -0.00232713:0.00801697:0.112604:0.00501098:348424:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055674    ES:SE:LP:AF:SS:ID   0.0081223:0.0077605:0.529772:0.0055674:348424:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870647 ES:SE:LP:AF:SS:ID   0.000842751:0.00155502:0.230733:0.870647:348424:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12589  ES:SE:LP:AF:SS:ID   -0.000676941:0.00158672:0.174153:0.12589:348424:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870217 ES:SE:LP:AF:SS:ID   0.000858108:0.00155131:0.236451:0.870217:348424:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869504 ES:SE:LP:AF:SS:ID   0.000827103:0.00154986:0.226524:0.869504:348424:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870367 ES:SE:LP:AF:SS:ID   0.000857526:0.00155261:0.236021:0.870367:348424:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870372 ES:SE:LP:AF:SS:ID   0.000859835:0.00155273:0.236763:0.870372:348424:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870381 ES:SE:LP:AF:SS:ID   0.000863875:0.00155277:0.238089:0.870381:348424:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870823 ES:SE:LP:AF:SS:ID   0.00086013:0.00155673:0.23613:0.870823:348424:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0987831    ES:SE:LP:AF:SS:ID   0.000118408:0.00180869:0.0232819:0.0987831:348424:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00644687   ES:SE:LP:AF:SS:ID   0.00301758:0.00701336:0.175871:0.00644687:348424:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874731 ES:SE:LP:AF:SS:ID   0.000432973:0.00158002:0.10565:0.874731:348424:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864126 ES:SE:LP:AF:SS:ID   0.000933767:0.0015493:0.262245:0.864126:348424:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.00079659:0.00156435:0.214242:0.8695:348424:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866446 ES:SE:LP:AF:SS:ID   0.000953163:0.00156467:0.265675:0.866446:348424:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987204    ES:SE:LP:AF:SS:ID   0.000418444:0.00187348:0.0844614:0.0987204:348424:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871633 ES:SE:LP:AF:SS:ID   0.000627443:0.00158258:0.160045:0.871633:348424:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871633 ES:SE:LP:AF:SS:ID   0.000627157:0.00158258:0.159961:0.871633:348424:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871633 ES:SE:LP:AF:SS:ID   0.000621868:0.00158261:0.158412:0.871633:348424:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.872009 ES:SE:LP:AF:SS:ID   0.000513151:0.00158354:0.127321:0.872009:348424:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125467 ES:SE:LP:AF:SS:ID   -0.000744224:0.00158479:0.194745:0.125467:348424:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105397 ES:SE:LP:AF:SS:ID   -0.000282778:0.00172476:0.0605961:0.105397:348424:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855446 ES:SE:LP:AF:SS:ID   0.000548461:0.00154866:0.140727:0.855446:348424:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016537    ES:SE:LP:AF:SS:ID   -0.00159573:0.013718:0.0422031:0.0016537:348424:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838377 ES:SE:LP:AF:SS:ID   0.000472318:0.00152613:0.120933:0.838377:348424:rs376645387