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-6070_1/ukb-d-6070_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-6070_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 17:14:14 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-6070_1/ukb-d-6070_1.vcf.gz ...
Read summary statistics for 13547107 SNPs.
Dropped 12654 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, 1283498 SNPs remain.
After merging with regression SNP LD, 1283498 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0033 (0.008)
Lambda GC: 1.0211
Mean Chi^2: 1.0163
Intercept: 1.0128 (0.0059)
Ratio: 0.7836 (0.3602)
Analysis finished at Mon Nov 25 17:16:30 2019
Total time elapsed: 2.0m:16.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0157,
    "mean_EFFECT": -8.1116e-06,
    "n": 54608,
    "n_snps": 13547107,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250493,
    "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": 557695,
    "n_est": 54849.073,
    "ratio_se_n": 1.0022,
    "mean_diff": -0,
    "ratio_diff": 121.8137,
    "sd_y_est1": 0.3465,
    "sd_y_est2": 0.3473,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283498,
    "ldsc_nsnp_merge_regression_ld": 1283498,
    "ldsc_observed_scale_h2_beta": 0.0033,
    "ldsc_observed_scale_h2_se": 0.008,
    "ldsc_intercept_beta": 1.0128,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0211,
    "ldsc_mean_chisq": 1.0163,
    "ldsc_ratio": 0.7853
}
 

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 13535116 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57009 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33322 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051422e+00 6.184654e+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 7.902271e+07 5.591770e+07 3.02000e+02 3.292300e+07 7.013526e+07 1.148568e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.100000e-06 1.219090e-02 -1.70595e-01 -3.190800e-03 2.570000e-05 3.282900e-03 1.263860e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.739100e-03 8.412100e-03 1.71960e-03 2.505800e-03 4.599400e-03 1.254240e-02 4.339010e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.977896e-01 2.890834e-01 1.00000e-07 2.470080e-01 4.966564e-01 7.482091e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.977867e-01 2.890851e-01 1.00000e-07 2.470029e-01 4.966527e-01 7.482083e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913358e-01 2.545265e-01 1.00000e-03 7.583100e-03 6.065250e-02 2.963100e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 557695 0.9588329 NA NA NA NA NA 1.967169e-01 2.471854e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.460800e+04 0.000000e+00 5.46080e+04 5.460800e+04 5.460800e+04 5.460800e+04 5.460800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0047593 0.0036497 0.1922370 0.1922315 0.1121640 0.1894970 54608
1 693731 rs12238997 A G -0.0027172 0.0034582 0.4320241 0.4320205 0.1171970 0.1417730 54608
1 707522 rs371890604 G C -0.0063793 0.0038800 0.1001449 0.1001394 0.0985104 0.1293930 54608
1 717587 rs144155419 G A 0.0001165 0.0094148 0.9901310 0.9901308 0.0154725 0.0045926 54608
1 723329 rs189787166 A T -0.0008760 0.0266909 0.9738171 0.9738169 0.0017767 0.0003994 54608
1 730087 rs148120343 T C -0.0027963 0.0048176 0.5616296 0.5616271 0.0572041 0.0127796 54608
1 731718 rs142557973 T C -0.0037263 0.0032822 0.2562530 0.2562481 0.1230530 0.1543530 54608
1 732032 rs61770163 A C -0.0048955 0.0034927 0.1610371 0.1610317 0.1228210 0.1555510 54608
1 734349 rs141242758 T C -0.0036047 0.0032850 0.2725060 0.2725015 0.1222260 0.1525560 54608
1 740284 rs61770167 C T 0.0086337 0.0140783 0.5397045 0.5397006 0.0065706 0.0023962 54608
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0002950 0.0038551 0.9390149 0.9390143 0.0543048 0.0309934 54608
23 154923374 rs111332691 T A -0.0092129 0.0041913 0.0279454 0.0279412 0.0443159 0.0116556 54608
23 154925045 rs509981 C T 0.0035238 0.0020142 0.0802140 0.0802070 0.2426730 0.3634440 54608
23 154925895 rs538470 C T 0.0038716 0.0020595 0.0601284 0.0601239 0.2390640 0.3634440 54608
23 154927581 rs644138 G A 0.0031012 0.0018945 0.1016471 0.1016410 0.2974080 0.4635760 54608
23 154929412 rs557132 C T 0.0035966 0.0020150 0.0742763 0.0742705 0.2425120 0.3568210 54608
23 154929637 rs35185538 CT C 0.0040567 0.0021038 0.0538307 0.0538257 0.2267730 0.3011920 54608
23 154929952 rs4012982 CAA C 0.0036743 0.0021172 0.0826723 0.0826655 0.2368080 0.3165560 54608
23 154930230 rs781880 A G 0.0035011 0.0020146 0.0822394 0.0822338 0.2428990 0.3618540 54608
23 154930487 rs781879 T A 0.0108379 0.0070552 0.1245031 0.1244986 0.0186654 0.1263580 54608

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112164 ES:SE:LP:AF:SS:ID   -0.00475927:0.00364973:0.716163:0.112164:54608:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117197 ES:SE:LP:AF:SS:ID   -0.00271725:0.00345821:0.364492:0.117197:54608:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0985104    ES:SE:LP:AF:SS:ID   -0.00637933:0.00387995:0.999371:0.0985104:54608:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154725    ES:SE:LP:AF:SS:ID   0.000116457:0.0094148:0.00430734:0.0154725:54608:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177673   ES:SE:LP:AF:SS:ID   -0.000876037:0.0266909:0.0115226:0.00177673:54608:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572041    ES:SE:LP:AF:SS:ID   -0.00279628:0.00481763:0.25055:0.0572041:54608:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123053 ES:SE:LP:AF:SS:ID   -0.00372626:0.00328217:0.591331:0.123053:54608:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122821 ES:SE:LP:AF:SS:ID   -0.00489546:0.00349274:0.793074:0.122821:54608:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122226 ES:SE:LP:AF:SS:ID   -0.00360474:0.00328504:0.564624:0.122226:54608:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00657061   ES:SE:LP:AF:SS:ID   0.00863374:0.0140783:0.267844:0.00657061:54608:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018554    ES:SE:LP:AF:SS:ID   0.0280756:0.0290284:0.476958:0.0018554:54608:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868283 ES:SE:LP:AF:SS:ID   0.00402628:0.00323609:0.670726:0.868283:54608:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015535    ES:SE:LP:AF:SS:ID   -0.00890804:0.0292461:0.118798:0.0015535:54608:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124285 ES:SE:LP:AF:SS:ID   -0.00569504:0.00320599:1.12104:0.124285:54608:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143512 ES:SE:LP:AF:SS:ID   -0.0047238:0.00318176:0.861246:0.143512:54608:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124417 ES:SE:LP:AF:SS:ID   -0.0056909:0.00320083:1.12252:0.124417:54608:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.86939  ES:SE:LP:AF:SS:ID   0.00449505:0.00311814:0.825571:0.86939:54608:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87416  ES:SE:LP:AF:SS:ID   0.00539744:0.00316994:1.05242:0.87416:54608:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130151 ES:SE:LP:AF:SS:ID   -0.00467137:0.00312535:0.869647:0.130151:54608:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366521    ES:SE:LP:AF:SS:ID   0.00191183:0.00566821:0.133181:0.0366521:54608:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86902  ES:SE:LP:AF:SS:ID   0.0042896:0.00311552:0.773235:0.86902:54608:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869139 ES:SE:LP:AF:SS:ID   0.00442664:0.00311745:0.807918:0.869139:54608:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869031 ES:SE:LP:AF:SS:ID   0.00438706:0.00311541:0.798379:0.869031:54608:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00525571   ES:SE:LP:AF:SS:ID   -0.0199342:0.0157405:0.687471:0.00525571:54608:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00522623   ES:SE:LP:AF:SS:ID   -0.0200206:0.0157815:0.689126:0.00522623:54608:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558199   ES:SE:LP:AF:SS:ID   -0.00059609:0.0155596:0.0134786:0.00558199:54608:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869139 ES:SE:LP:AF:SS:ID   0.00457605:0.00311039:0.850045:0.869139:54608:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12743  ES:SE:LP:AF:SS:ID   -0.00530153:0.00317289:1.02342:0.12743:54608:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868737 ES:SE:LP:AF:SS:ID   0.00470031:0.0031034:0.886431:0.868737:54608:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867829 ES:SE:LP:AF:SS:ID   0.00482511:0.00309854:0.922908:0.867829:54608:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868887 ES:SE:LP:AF:SS:ID   0.00452091:0.00310578:0.837146:0.868887:54608:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868893 ES:SE:LP:AF:SS:ID   0.00451846:0.00310599:0.836415:0.868893:54608:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868903 ES:SE:LP:AF:SS:ID   0.00452816:0.0031061:0.83895:0.868903:54608:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8693   ES:SE:LP:AF:SS:ID   0.00459909:0.00311378:0.854872:0.8693:54608:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100007 ES:SE:LP:AF:SS:ID   -0.00529428:0.00361646:0.844008:0.100007:54608:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00633355   ES:SE:LP:AF:SS:ID   -0.00784117:0.0141591:0.236779:0.00633355:54608:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873384 ES:SE:LP:AF:SS:ID   0.00516036:0.00316115:0.988874:0.873384:54608:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862461 ES:SE:LP:AF:SS:ID   0.00458612:0.0030988:0.857335:0.862461:54608:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868167 ES:SE:LP:AF:SS:ID   0.00492424:0.00313188:0.935965:0.868167:54608:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864809 ES:SE:LP:AF:SS:ID   0.00518719:0.00312888:1.01164:0.864809:54608:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0998323    ES:SE:LP:AF:SS:ID   -0.00426616:0.00374637:0.593775:0.0998323:54608:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870153 ES:SE:LP:AF:SS:ID   0.00565921:0.00316486:1.13219:0.870153:54608:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870153 ES:SE:LP:AF:SS:ID   0.00565974:0.00316486:1.13234:0.870153:54608:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87015  ES:SE:LP:AF:SS:ID   0.00565858:0.00316487:1.13199:0.87015:54608:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870574 ES:SE:LP:AF:SS:ID   0.00555208:0.00316708:1.0991:0.870574:54608:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126835 ES:SE:LP:AF:SS:ID   -0.00525386:0.00316997:1.01123:0.126835:54608:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10661  ES:SE:LP:AF:SS:ID   -0.00417723:0.00345042:0.645819:0.10661:54608:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853905 ES:SE:LP:AF:SS:ID   0.00438915:0.00310179:0.803929:0.853905:54608:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168021   ES:SE:LP:AF:SS:ID   -0.00531691:0.0268798:0.0740694:0.00168021:54608:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836395 ES:SE:LP:AF:SS:ID   0.00289007:0.0030435:0.46556:0.836395:54608:rs376645387