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-20411_1/ukb-d-20411_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-20411_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 16:32:44 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20411_1/ukb-d-20411_1.vcf.gz ...
Read summary statistics for 11871350 SNPs.
Dropped 10275 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, 1282942 SNPs remain.
After merging with regression SNP LD, 1282942 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0035 (0.0037)
Lambda GC: 1.0289
Mean Chi^2: 1.0239
Intercept: 1.0158 (0.006)
Ratio: 0.6588 (0.2512)
Analysis finished at Mon Nov 25 16:34:42 2019
Total time elapsed: 1.0m:58.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.0237,
    "mean_EFFECT": 5.8438e-06,
    "n": 118002,
    "n_snps": 11871350,
    "n_clumped_hits": 2,
    "n_p_sig": 5,
    "n_mono": 0,
    "n_ns": 1178758,
    "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": 271300,
    "n_est": 118260.7114,
    "ratio_se_n": 1.0011,
    "mean_diff": 0,
    "ratio_diff": 20.087,
    "sd_y_est1": 0.191,
    "sd_y_est2": 0.1912,
    "r2_sum1": 0,
    "r2_sum2": 0.0006,
    "r2_sum3": 0.0006,
    "r2_sum4": 0.0006,
    "ldsc_nsnp_merge_refpanel_ld": 1282942,
    "ldsc_nsnp_merge_regression_ld": 1282942,
    "ldsc_observed_scale_h2_beta": 0.0035,
    "ldsc_observed_scale_h2_se": 0.0037,
    "ldsc_intercept_beta": 1.0158,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0289,
    "ldsc_mean_chisq": 1.0239,
    "ldsc_ratio": 0.6611
}

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 11861691 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 53092 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32035 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.070426e+00 6.184369e+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 7.888026e+07 5.598250e+07 3.02000e+02 3.268350e+07 6.990445e+07 1.147450e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.800000e-06 2.996900e-03 -3.19461e-02 -1.054800e-03 -7.800000e-06 1.035400e-03 3.953320e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.317200e-03 1.886000e-03 6.51700e-04 9.015000e-04 1.415000e-03 3.184800e-03 1.131450e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.965189e-01 2.896073e-01 0.00000e+00 2.448353e-01 4.949587e-01 7.476305e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.965176e-01 2.896081e-01 0.00000e+00 2.448331e-01 4.949575e-01 7.476302e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.168955e-01 2.597575e-01 2.75270e-03 1.629530e-02 9.561600e-02 3.453950e-01 9.972470e-01 ▇▂▁▁▁
numeric AF_reference 271300 0.9771467 NA NA NA NA NA 2.180614e-01 2.511810e-01 0.00000e+00 1.297920e-02 1.148160e-01 3.468450e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.180020e+05 0.000000e+00 1.18002e+05 1.180020e+05 1.180020e+05 1.180020e+05 1.180020e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0006913 0.0013705 0.6139571 0.6139548 0.1117250 0.1894970 118002
1 693731 rs12238997 A G -0.0010475 0.0012979 0.4196140 0.4196156 0.1167420 0.1417730 118002
1 707522 rs371890604 G C -0.0002194 0.0014563 0.8802710 0.8802711 0.0983656 0.1293930 118002
1 717587 rs144155419 G A -0.0030883 0.0034906 0.3762998 0.3762971 0.0157540 0.0045926 118002
1 730087 rs148120343 T C 0.0010633 0.0018058 0.5559644 0.5559626 0.0569247 0.0127796 118002
1 731718 rs142557973 T C -0.0007735 0.0012315 0.5299269 0.5299258 0.1226680 0.1543530 118002
1 732032 rs61770163 A C -0.0007448 0.0013125 0.5704177 0.5704172 0.1222730 0.1555510 118002
1 734349 rs141242758 T C -0.0007606 0.0012321 0.5370095 0.5370105 0.1219240 0.1525560 118002
1 740284 rs61770167 C T -0.0020677 0.0056247 0.7131666 0.7131668 0.0058595 0.0023962 118002
1 749963 rs529266287 T TAA 0.0004395 0.0012141 0.7173515 0.7173512 0.8690000 0.7641770 118002
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0034544 0.0014479 0.0170428 0.0170415 0.0554993 0.0309934 118002
23 154923374 rs111332691 T A -0.0008878 0.0015786 0.5738191 0.5738188 0.0447620 0.0116556 118002
23 154925045 rs509981 C T -0.0005324 0.0007601 0.4836052 0.4836040 0.2447160 0.3634440 118002
23 154925895 rs538470 C T -0.0005583 0.0007772 0.4725437 0.4725421 0.2411370 0.3634440 118002
23 154927581 rs644138 G A 0.0003610 0.0007152 0.6137125 0.6137124 0.3005770 0.4635760 118002
23 154929412 rs557132 C T -0.0005406 0.0007602 0.4770106 0.4770093 0.2445910 0.3568210 118002
23 154929637 rs35185538 CT C 0.0000432 0.0007942 0.9565769 0.9565772 0.2288060 0.3011920 118002
23 154929952 rs4012982 CAA C -0.0003200 0.0008001 0.6892408 0.6892405 0.2386720 0.3165560 118002
23 154930230 rs781880 A G -0.0006047 0.0007600 0.4262545 0.4262537 0.2450140 0.3618540 118002
23 154930487 rs781879 T A 0.0009611 0.0025834 0.7098687 0.7098673 0.0196756 0.1263580 118002

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111725 ES:SE:LP:AF:SS:ID   -0.00069133:0.0013705:0.211862:0.111725:118002:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116742 ES:SE:LP:AF:SS:ID   -0.00104752:0.0012979:0.37715:0.116742:118002:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983656    ES:SE:LP:AF:SS:ID   -0.000219362:0.00145634:0.0553836:0.0983656:118002:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015754 ES:SE:LP:AF:SS:ID   -0.00308829:0.00349062:0.424466:0.015754:118002:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569247    ES:SE:LP:AF:SS:ID   0.00106332:0.00180576:0.254953:0.0569247:118002:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122668 ES:SE:LP:AF:SS:ID   -0.00077351:0.00123147:0.275784:0.122668:118002:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122273 ES:SE:LP:AF:SS:ID   -0.000744784:0.00131254:0.243807:0.122273:118002:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121924 ES:SE:LP:AF:SS:ID   -0.000760637:0.00123212:0.270018:0.121924:118002:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00585949   ES:SE:LP:AF:SS:ID   -0.00206769:0.00562474:0.146809:0.00585949:118002:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869    ES:SE:LP:AF:SS:ID   0.000439491:0.00121406:0.144268:0.869:118002:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123707 ES:SE:LP:AF:SS:ID   -0.000801573:0.00120286:0.296568:0.123707:118002:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143341 ES:SE:LP:AF:SS:ID   -0.000557563:0.00118964:0.194297:0.143341:118002:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123828 ES:SE:LP:AF:SS:ID   -0.000780719:0.0012012:0.287582:0.123828:118002:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869757 ES:SE:LP:AF:SS:ID   0.00042203:0.00116976:0.143716:0.869757:118002:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874545 ES:SE:LP:AF:SS:ID   0.000463678:0.00118946:0.156974:0.874545:118002:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129703 ES:SE:LP:AF:SS:ID   -0.000578155:0.00117304:0.206136:0.129703:118002:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036546 ES:SE:LP:AF:SS:ID   0.000908698:0.00212984:0.174162:0.036546:118002:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86935  ES:SE:LP:AF:SS:ID   0.00052633:0.00116865:0.185458:0.86935:118002:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869422 ES:SE:LP:AF:SS:ID   0.000546625:0.00116908:0.193756:0.869422:118002:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86935  ES:SE:LP:AF:SS:ID   0.000507685:0.00116862:0.177848:0.86935:118002:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00511994   ES:SE:LP:AF:SS:ID   -0.0020679:0.00597633:0.137075:0.00511994:118002:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00508903   ES:SE:LP:AF:SS:ID   -0.0019364:0.0059895:0.126988:0.00508903:118002:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0056895    ES:SE:LP:AF:SS:ID   -0.00649097:0.00575878:0.585555:0.0056895:118002:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869423 ES:SE:LP:AF:SS:ID   0.000440688:0.00116647:0.151453:0.869423:118002:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126979 ES:SE:LP:AF:SS:ID   -0.000504809:0.00119073:0.172887:0.126979:118002:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868943 ES:SE:LP:AF:SS:ID   0.000381415:0.0011634:0.128994:0.868943:118002:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868344 ES:SE:LP:AF:SS:ID   0.000541673:0.00116296:0.192885:0.868344:118002:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869132 ES:SE:LP:AF:SS:ID   0.000439527:0.00116456:0.15128:0.869132:118002:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869139 ES:SE:LP:AF:SS:ID   0.0004417:0.00116464:0.152121:0.869139:118002:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869142 ES:SE:LP:AF:SS:ID   0.000441188:0.00116465:0.151919:0.869142:118002:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869577 ES:SE:LP:AF:SS:ID   0.000435857:0.00116763:0.149391:0.869577:118002:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0995897    ES:SE:LP:AF:SS:ID   0.000438952:0.00135746:0.127016:0.0995897:118002:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0065479    ES:SE:LP:AF:SS:ID   -0.00675282:0.00522906:0.706489:0.0065479:118002:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873646 ES:SE:LP:AF:SS:ID   0.000489349:0.00118558:0.167626:0.873646:118002:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862925 ES:SE:LP:AF:SS:ID   0.000431385:0.00116266:0.148366:0.862925:118002:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868327 ES:SE:LP:AF:SS:ID   0.00063704:0.00117387:0.231104:0.868327:118002:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865338 ES:SE:LP:AF:SS:ID   0.000483832:0.00117405:0.167323:0.865338:118002:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997644    ES:SE:LP:AF:SS:ID   -0.00140648:0.00140292:0.500199:0.0997644:118002:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870635 ES:SE:LP:AF:SS:ID   0.00070823:0.00118794:0.258807:0.870635:118002:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870635 ES:SE:LP:AF:SS:ID   0.0007084:0.00118794:0.258882:0.870635:118002:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870634 ES:SE:LP:AF:SS:ID   0.000707961:0.00118794:0.258687:0.870634:118002:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870956 ES:SE:LP:AF:SS:ID   0.0006459:0.00118844:0.231512:0.870956:118002:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126564 ES:SE:LP:AF:SS:ID   -0.000736863:0.00118945:0.271168:0.126564:118002:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10635  ES:SE:LP:AF:SS:ID   4.67595e-06:0.0012926:0.00125519:0.10635:118002:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854373 ES:SE:LP:AF:SS:ID   0.000703615:0.00116237:0.263633:0.854373:118002:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839097 ES:SE:LP:AF:SS:ID   0.0021121:0.00115168:1.17608:0.839097:118002:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.76302  ES:SE:LP:AF:SS:ID   0.00108618:0.000923071:0.62103:0.76302:118002:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10524  ES:SE:LP:AF:SS:ID   -0.0016809:0.00127698:0.725676:0.10524:118002:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00773588   ES:SE:LP:AF:SS:ID   0.000826444:0.00471563:0.0650584:0.00773588:118002:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129982 ES:SE:LP:AF:SS:ID   -0.000676455:0.00117245:0.248746:0.129982:118002:rs762168062