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-20450/ukb-d-20450.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-20450/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 17:15:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20450/ukb-d-20450.vcf.gz ...
Read summary statistics for 13559196 SNPs.
Dropped 12677 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, 1283500 SNPs remain.
After merging with regression SNP LD, 1283500 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0448 (0.0079)
Lambda GC: 1.0549
Mean Chi^2: 1.0644
Intercept: 1.0102 (0.0065)
Ratio: 0.1586 (0.1004)
Analysis finished at Mon Nov 25 17:17:20 2019
Total time elapsed: 2.0m:18.23s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0345,
    "mean_EFFECT": -0,
    "n": 62128,
    "n_snps": 13559196,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250902,
    "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": 561449,
    "n_est": 62288.2768,
    "ratio_se_n": 1.0013,
    "mean_diff": -0,
    "ratio_diff": 17.4656,
    "sd_y_est1": 0.4939,
    "sd_y_est2": 0.4945,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283500,
    "ldsc_nsnp_merge_regression_ld": 1283500,
    "ldsc_observed_scale_h2_beta": 0.0448,
    "ldsc_observed_scale_h2_se": 0.0079,
    "ldsc_intercept_beta": 1.0102,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0549,
    "ldsc_mean_chisq": 1.0644,
    "ldsc_ratio": 0.1584
}

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 13547183 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57033 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 9.051453e+00 6.185031e+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 7.902366e+07 5.591553e+07 3.02000e+02 3.292657e+07 7.013642e+07 1.148570e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.750000e-05 1.627340e-02 -2.13512e-01 -4.413000e-03 -1.770000e-05 4.411600e-03 1.985800e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.171190e-02 1.128060e-02 2.37720e-03 3.349200e-03 6.155000e-03 1.681310e-02 5.662980e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.945396e-01 2.907869e-01 1.00000e-07 2.413532e-01 4.926880e-01 7.465072e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.945370e-01 2.907884e-01 1.00000e-07 2.413492e-01 4.926855e-01 7.465059e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911619e-01 2.544871e-01 1.00000e-03 7.528100e-03 6.047330e-02 2.960590e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561449 0.9585928 NA NA NA NA NA 1.965904e-01 2.471526e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.212800e+04 0.000000e+00 6.21280e+04 6.212800e+04 6.212800e+04 6.212800e+04 6.212800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0031838 0.0048729 0.5135243 0.5135226 0.1119250 0.1894970 62128
1 693731 rs12238997 A G 0.0040250 0.0046092 0.3825278 0.3825237 0.1171980 0.1417730 62128
1 707522 rs371890604 G C 0.0057668 0.0051645 0.2641630 0.2641592 0.0988289 0.1293930 62128
1 717587 rs144155419 G A 0.0162831 0.0124342 0.1903549 0.1903510 0.0156837 0.0045926 62128
1 723329 rs189787166 A T 0.0169037 0.0350410 0.6295265 0.6295234 0.0018794 0.0003994 62128
1 730087 rs148120343 T C 0.0033766 0.0064159 0.5986914 0.5986894 0.0570735 0.0127796 62128
1 731718 rs142557973 T C 0.0057170 0.0043748 0.1912842 0.1912790 0.1230780 0.1543530 62128
1 732032 rs61770163 A C 0.0045404 0.0046596 0.3298557 0.3298520 0.1225630 0.1555510 62128
1 734349 rs141242758 T C 0.0055736 0.0043763 0.2028080 0.2028034 0.1223650 0.1525560 62128
1 740284 rs61770167 C T -0.0113143 0.0198916 0.5694964 0.5694933 0.0058954 0.0023962 62128
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0000224 0.0052867 0.9966120 0.9966122 0.0557001 0.0309934 62128
23 154923374 rs111332691 T A 0.0003413 0.0058572 0.9535329 0.9535325 0.0434184 0.0116556 62128
23 154925045 rs509981 C T 0.0023472 0.0027710 0.3969611 0.3969574 0.2452990 0.3634440 62128
23 154925895 rs538470 C T 0.0023565 0.0028338 0.4056682 0.4056646 0.2416300 0.3634440 62128
23 154927581 rs644138 G A 0.0020829 0.0026084 0.4245668 0.4245642 0.3014190 0.4635760 62128
23 154929412 rs557132 C T 0.0022252 0.0027716 0.4220559 0.4220533 0.2451840 0.3568210 62128
23 154929637 rs35185538 CT C 0.0027384 0.0028969 0.3445149 0.3445108 0.2287380 0.3011920 62128
23 154929952 rs4012982 CAA C 0.0026100 0.0029195 0.3713351 0.3713308 0.2389280 0.3165560 62128
23 154930230 rs781880 A G 0.0023203 0.0027715 0.4024834 0.4024798 0.2454670 0.3618540 62128
23 154930487 rs781879 T A -0.0002075 0.0094046 0.9823970 0.9823973 0.0195989 0.1263580 62128

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111925 ES:SE:LP:AF:SS:ID   0.00318379:0.00487293:0.289439:0.111925:62128:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117198 ES:SE:LP:AF:SS:ID   0.00402501:0.0046092:0.417337:0.117198:62128:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0988289    ES:SE:LP:AF:SS:ID   0.0057668:0.00516454:0.578128:0.0988289:62128:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156837    ES:SE:LP:AF:SS:ID   0.0162831:0.0124342:0.720436:0.0156837:62128:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00187945   ES:SE:LP:AF:SS:ID   0.0169037:0.035041:0.200986:0.00187945:62128:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570735    ES:SE:LP:AF:SS:ID   0.00337662:0.00641594:0.222797:0.0570735:62128:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:SS:ID   0.00571701:0.0043748:0.718321:0.123078:62128:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122563 ES:SE:LP:AF:SS:ID   0.00454037:0.0046596:0.481676:0.122563:62128:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122365 ES:SE:LP:AF:SS:ID   0.00557364:0.00437627:0.692915:0.122365:62128:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00589542   ES:SE:LP:AF:SS:ID   -0.0113143:0.0198916:0.244509:0.00589542:62128:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00186563   ES:SE:LP:AF:SS:ID   0.0175535:0.0379324:0.191425:0.00186563:62128:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868457 ES:SE:LP:AF:SS:ID   -0.00275016:0.00430792:0.281318:0.868457:62128:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00157426   ES:SE:LP:AF:SS:ID   0.0281409:0.0384894:0.332828:0.00157426:62128:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124373 ES:SE:LP:AF:SS:ID   0.00323899:0.00426647:0.348962:0.124373:62128:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143886 ES:SE:LP:AF:SS:ID   0.00434275:0.00422188:0.517615:0.143886:62128:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124472 ES:SE:LP:AF:SS:ID   0.00314057:0.00426079:0.336229:0.124472:62128:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869327 ES:SE:LP:AF:SS:ID   -0.00499731:0.00415402:0.640204:0.869327:62128:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873906 ES:SE:LP:AF:SS:ID   -0.00352427:0.00421985:0.394019:0.873906:62128:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130063 ES:SE:LP:AF:SS:ID   0.00499506:0.00416639:0.63719:0.130063:62128:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0361512    ES:SE:LP:AF:SS:ID   0.0174958:0.00761528:1.66563:0.0361512:62128:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868945 ES:SE:LP:AF:SS:ID   -0.00477374:0.00414989:0.602037:0.868945:62128:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869009 ES:SE:LP:AF:SS:ID   -0.00473434:0.00415109:0.59503:0.869009:62128:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868948 ES:SE:LP:AF:SS:ID   -0.0047383:0.00414977:0.595967:0.868948:62128:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00500002   ES:SE:LP:AF:SS:ID   -0.00418745:0.021585:0.0725383:0.00500002:62128:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00496893   ES:SE:LP:AF:SS:ID   -0.00388916:0.0216326:0.066855:0.00496893:62128:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00580254   ES:SE:LP:AF:SS:ID   0.0128158:0.0202794:0.277848:0.00580254:62128:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868973 ES:SE:LP:AF:SS:ID   -0.00506083:0.00414222:0.654038:0.868973:62128:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127429 ES:SE:LP:AF:SS:ID   0.00454696:0.00422824:0.549429:0.127429:62128:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868489 ES:SE:LP:AF:SS:ID   -0.00483791:0.00413141:0.616903:0.868489:62128:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867997 ES:SE:LP:AF:SS:ID   -0.00479452:0.00413029:0.609561:0.867997:62128:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868692 ES:SE:LP:AF:SS:ID   -0.00527263:0.00413536:0.693983:0.868692:62128:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868698 ES:SE:LP:AF:SS:ID   -0.00527344:0.00413566:0.69406:0.868698:62128:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868701 ES:SE:LP:AF:SS:ID   -0.00527947:0.00413567:0.695167:0.868701:62128:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869104 ES:SE:LP:AF:SS:ID   -0.00519881:0.00414609:0.678027:0.869104:62128:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100421 ES:SE:LP:AF:SS:ID   0.00408946:0.00480559:0.403639:0.100421:62128:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00666414   ES:SE:LP:AF:SS:ID   0.0157615:0.0184372:0.406023:0.00666414:62128:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873074 ES:SE:LP:AF:SS:ID   -0.00337874:0.00420809:0.37466:0.873074:62128:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862726 ES:SE:LP:AF:SS:ID   -0.00547725:0.0041293:0.733531:0.862726:62128:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867796 ES:SE:LP:AF:SS:ID   -0.00468005:0.00416865:0.582397:0.867796:62128:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865025 ES:SE:LP:AF:SS:ID   -0.00436817:0.00417245:0.529963:0.865025:62128:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100591 ES:SE:LP:AF:SS:ID   0.00423136:0.00496976:0.40391:0.100591:62128:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87004  ES:SE:LP:AF:SS:ID   -0.0033796:0.00421772:0.37369:0.87004:62128:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87004  ES:SE:LP:AF:SS:ID   -0.00337991:0.00421772:0.373736:0.87004:62128:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870037 ES:SE:LP:AF:SS:ID   -0.00337906:0.00421773:0.373615:0.870037:62128:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870343 ES:SE:LP:AF:SS:ID   -0.00321959:0.00421896:0.351258:0.870343:62128:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127088 ES:SE:LP:AF:SS:ID   0.0039152:0.00422289:0.45117:0.127088:62128:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106898 ES:SE:LP:AF:SS:ID   0.00521484:0.00458738:0.59238:0.106898:62128:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853871 ES:SE:LP:AF:SS:ID   -0.00359467:0.0041276:0.415874:0.853871:62128:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00179203   ES:SE:LP:AF:SS:ID   0.0228085:0.0352908:0.285598:0.00179203:62128:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837594 ES:SE:LP:AF:SS:ID   -0.00105888:0.00408676:0.0993276:0.837594:62128:rs376645387