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-30810_raw/ukb-d-30810_raw.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-30810_raw/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 14:54:48 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30810_raw/ukb-d-30810_raw.vcf.gz ...
Read summary statistics for 13585253 SNPs.
Dropped 12711 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1064 (0.0099)
Lambda GC: 1.3905
Mean Chi^2: 1.7272
Intercept: 1.0782 (0.0131)
Ratio: 0.1075 (0.018)
Analysis finished at Mon Nov 25 14:57:06 2019
Total time elapsed: 2.0m:18.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.25,
    "mean_EFFECT": 1.0585e-06,
    "n": 314658,
    "n_snps": 13585253,
    "n_clumped_hits": 160,
    "n_p_sig": 22506,
    "n_mono": 0,
    "n_ns": 1251740,
    "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": 568957,
    "n_est": 315878.9461,
    "ratio_se_n": 1.0019,
    "mean_diff": 4.6371e-06,
    "ratio_diff": 4.23,
    "sd_y_est1": 0.1555,
    "sd_y_est2": 0.1559,
    "r2_sum1": 0.0011,
    "r2_sum2": 0.0475,
    "r2_sum3": 0.0473,
    "r2_sum4": 0.0473,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.1064,
    "ldsc_observed_scale_h2_se": 0.0099,
    "ldsc_intercept_beta": 1.0782,
    "ldsc_intercept_se": 0.0131,
    "ldsc_lambda_gc": 1.3905,
    "ldsc_mean_chisq": 1.7272,
    "ldsc_ratio": 0.1075
}
 

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 13573206 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33335 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051268e+00 6.184974e+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 7.902543e+07 5.591517e+07 3.02000e+02 3.293043e+07 7.013909e+07 1.148604e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.100000e-06 2.378200e-03 -4.47000e-02 -6.982000e-04 9.000000e-07 7.033000e-04 3.339900e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.647400e-03 1.589000e-03 3.22000e-04 4.691000e-04 8.643000e-04 2.367100e-03 8.009700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.625595e-01 2.994731e-01 0.00000e+00 1.937898e-01 4.507804e-01 7.217703e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.625590e-01 2.994734e-01 0.00000e+00 1.937871e-01 4.507830e-01 7.217651e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908205e-01 2.544080e-01 1.00000e-03 7.434300e-03 6.004500e-02 2.953300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568957 0.9581195 NA NA NA NA NA 1.963466e-01 2.471050e-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 3.146580e+05 0.000000e+00 3.14658e+05 3.146580e+05 3.146580e+05 3.146580e+05 3.146580e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0016247 0.0006869 0.0180210 0.0180222 0.1104900 0.1894970 314658
1 693731 rs12238997 A G 0.0012379 0.0006489 0.0564066 0.0564161 0.1158100 0.1417730 314658
1 707522 rs371890604 G C 0.0010534 0.0007301 0.1490799 0.1490890 0.0971780 0.1293930 314658
1 717587 rs144155419 G A 0.0013826 0.0017387 0.4265098 0.4265019 0.0157030 0.0045926 314658
1 723329 rs189787166 A T 0.0097079 0.0051391 0.0588898 0.0588882 0.0017313 0.0003994 314658
1 730087 rs148120343 T C 0.0018966 0.0009038 0.0358641 0.0358654 0.0564700 0.0127796 314658
1 731718 rs142557973 T C 0.0011296 0.0006155 0.0664753 0.0664722 0.1216900 0.1543530 314658
1 732032 rs61770163 A C 0.0011308 0.0006569 0.0851530 0.0851559 0.1210400 0.1555510 314658
1 734349 rs141242758 T C 0.0011538 0.0006158 0.0609818 0.0609899 0.1209100 0.1525560 314658
1 740284 rs61770167 C T -0.0005419 0.0028264 0.8479601 0.8479608 0.0057414 0.0023962 314658
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0007123 0.0007106 0.3161702 0.3161678 0.056080 0.0309934 314658
23 154923374 rs111332691 T A -0.0007787 0.0007776 0.3166402 0.3166388 0.045003 0.0116556 314658
23 154925045 rs509981 C T -0.0006173 0.0003754 0.1001000 0.1000963 0.245790 0.3634440 314658
23 154925895 rs538470 C T -0.0005673 0.0003840 0.1395501 0.1395556 0.242080 0.3634440 314658
23 154927581 rs644138 G A -0.0003857 0.0003531 0.2746800 0.2746743 0.302250 0.4635760 314658
23 154929412 rs557132 C T -0.0006512 0.0003755 0.0828934 0.0828896 0.245640 0.3568210 314658
23 154929637 rs35185538 CT C -0.0003563 0.0003918 0.3631700 0.3631662 0.230030 0.3011920 314658
23 154929952 rs4012982 CAA C -0.0007192 0.0003949 0.0685772 0.0685810 0.239560 0.3165560 314658
23 154930230 rs781880 A G -0.0006504 0.0003754 0.0832224 0.0832211 0.246010 0.3618540 314658
23 154930487 rs781879 T A -0.0006076 0.0012904 0.6377405 0.6377284 0.019470 0.1263580 314658

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11049  ES:SE:LP:AF:SS:ID   0.0016247:0.00068693:1.74422:0.11049:314658:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   0.0012379:0.00064886:1.24867:0.11581:314658:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097178 ES:SE:LP:AF:SS:ID   0.0010534:0.00073013:0.826581:0.097178:314658:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015703 ES:SE:LP:AF:SS:ID   0.0013826:0.0017387:0.370071:0.015703:314658:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017313    ES:SE:LP:AF:SS:ID   0.0097079:0.0051391:1.22996:0.0017313:314658:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.05647  ES:SE:LP:AF:SS:ID   0.0018966:0.00090381:1.44534:0.05647:314658:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12169  ES:SE:LP:AF:SS:ID   0.0011296:0.00061551:1.17734:0.12169:314658:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12104  ES:SE:LP:AF:SS:ID   0.0011308:0.00065686:1.0698:0.12104:314658:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12091  ES:SE:LP:AF:SS:ID   0.0011538:0.00061583:1.2148:0.12091:314658:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057414    ES:SE:LP:AF:SS:ID   -0.00054188:0.0028264:0.0716246:0.0057414:314658:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018554    ES:SE:LP:AF:SS:ID   0.0020237:0.0053605:0.151324:0.0018554:314658:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86978  ES:SE:LP:AF:SS:ID   -0.0011946:0.00060712:1.30888:0.86978:314658:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015107    ES:SE:LP:AF:SS:ID   -0.0069447:0.0055326:0.679023:0.0015107:314658:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12287  ES:SE:LP:AF:SS:ID   0.001181:0.00060133:1.30508:0.12287:314658:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14268  ES:SE:LP:AF:SS:ID   0.0012797:0.00059425:1.50469:0.14268:314658:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   0.0011614:0.00060048:1.27497:0.12299:314658:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87101  ES:SE:LP:AF:SS:ID   -0.0011853:0.00058529:1.36799:0.87101:314658:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87554  ES:SE:LP:AF:SS:ID   -0.0011852:0.00059485:1.33428:0.87554:314658:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12854  ES:SE:LP:AF:SS:ID   0.0012507:0.0005867:1.48117:0.12854:314658:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036328 ES:SE:LP:AF:SS:ID   -0.0016406:0.0010644:0.909248:0.036328:314658:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   -0.0012298:0.00058466:1.45058:0.8706:314658:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87071  ES:SE:LP:AF:SS:ID   -0.0011988:0.00058495:1.39341:0.87071:314658:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   -0.0012281:0.00058464:1.44766:0.8706:314658:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050258    ES:SE:LP:AF:SS:ID   -0.0005188:0.003003:0.0640697:0.0050258:314658:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0049925    ES:SE:LP:AF:SS:ID   -0.00042747:0.0030111:0.0520225:0.0049925:314658:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055162    ES:SE:LP:AF:SS:ID   0.001389:0.0029238:0.197411:0.0055162:314658:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87069  ES:SE:LP:AF:SS:ID   -0.0011743:0.00058367:1.35431:0.87069:314658:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12588  ES:SE:LP:AF:SS:ID   0.0012196:0.00059546:1.39198:0.12588:314658:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87026  ES:SE:LP:AF:SS:ID   -0.0011666:0.00058227:1.34568:0.87026:314658:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86954  ES:SE:LP:AF:SS:ID   -0.0012387:0.00058175:1.47843:0.86954:314658:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   -0.0012064:0.00058276:1.41522:0.87041:314658:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   -0.0012063:0.00058281:1.41495:0.87041:314658:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87042  ES:SE:LP:AF:SS:ID   -0.0012113:0.00058282:1.42382:0.87042:314658:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87087  ES:SE:LP:AF:SS:ID   -0.0011954:0.0005843:1.38956:0.87087:314658:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098764 ES:SE:LP:AF:SS:ID   0.0014732:0.00067911:1.52203:0.098764:314658:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0063964    ES:SE:LP:AF:SS:ID   5.7954e-05:0.0026426:0.00766744:0.0063964:314658:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   -0.0012579:0.00059287:1.47025:0.87471:314658:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86414  ES:SE:LP:AF:SS:ID   -0.0011895:0.00058157:1.38901:0.86414:314658:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86954  ES:SE:LP:AF:SS:ID   -0.0013061:0.0005871:1.58324:0.86954:314658:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86649  ES:SE:LP:AF:SS:ID   -0.0012827:0.00058722:1.53862:0.86649:314658:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098748 ES:SE:LP:AF:SS:ID   0.0012999:0.0007028:1.19129:0.098748:314658:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87165  ES:SE:LP:AF:SS:ID   -0.0012212:0.00059388:1.40054:0.87165:314658:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87165  ES:SE:LP:AF:SS:ID   -0.0012211:0.00059388:1.40049:0.87165:314658:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87165  ES:SE:LP:AF:SS:ID   -0.0012221:0.00059389:1.40222:0.87165:314658:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87201  ES:SE:LP:AF:SS:ID   -0.0012103:0.00059422:1.38023:0.87201:314658:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12549  ES:SE:LP:AF:SS:ID   0.0012296:0.00059465:1.41264:0.12549:314658:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10534  ES:SE:LP:AF:SS:ID   0.0013241:0.0006477:1.38802:0.10534:314658:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85548  ES:SE:LP:AF:SS:ID   -0.0011572:0.00058131:1.33235:0.85548:314658:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016488    ES:SE:LP:AF:SS:ID   0.010058:0.0051535:1.29269:0.0016488:314658:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83826  ES:SE:LP:AF:SS:ID   -0.00033032:0.00057177:0.249137:0.83826:314658:rs376645387