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-30890_irnt/ukb-d-30890_irnt.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-30890_irnt/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 15:35:49 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30890_irnt/ukb-d-30890_irnt.vcf.gz ...
Read summary statistics for 13585762 SNPs.
Dropped 12709 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: 0.0963 (0.0212)
Lambda GC: 1.3512
Mean Chi^2: 1.6673
Intercept: 1.0437 (0.0113)
Ratio: 0.0655 (0.0169)
Analysis finished at Mon Nov 25 15:38:06 2019
Total time elapsed: 2.0m:17.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2238,
    "mean_EFFECT": -0,
    "n": 329247,
    "n_snps": 13585762,
    "n_clumped_hits": 60,
    "n_p_sig": 11130,
    "n_mono": 0,
    "n_ns": 1251771,
    "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": 569068,
    "n_est": 330528.9437,
    "ratio_se_n": 1.0019,
    "mean_diff": -1.1869e-06,
    "ratio_diff": 1.039,
    "sd_y_est1": 0.9971,
    "sd_y_est2": 0.9991,
    "r2_sum1": 0.0296,
    "r2_sum2": 0.0298,
    "r2_sum3": 0.0297,
    "r2_sum4": 0.0298,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0963,
    "ldsc_observed_scale_h2_se": 0.0212,
    "ldsc_intercept_beta": 1.0437,
    "ldsc_intercept_se": 0.0113,
    "ldsc_lambda_gc": 1.3512,
    "ldsc_mean_chisq": 1.6673,
    "ldsc_ratio": 0.0655
}

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 13573717 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57081 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 9.051247e+00 6.184965e+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 7.902599e+07 5.591538e+07 3.02000e+02 3.293141e+07 7.013940e+07 1.148610e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.780000e-05 1.487040e-02 -4.45630e-01 -4.351200e-03 -3.170000e-05 4.253300e-03 2.986100e-01 ▁▁▇▆▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.032460e-02 9.959500e-03 2.01550e-03 2.939700e-03 5.416900e-03 1.483600e-02 5.022400e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.669405e-01 2.982181e-01 0.00000e+00 2.002599e-01 4.555699e-01 7.255294e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.669400e-01 2.982184e-01 0.00000e+00 2.002581e-01 4.555723e-01 7.255262e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908129e-01 2.544054e-01 1.00000e-03 7.433300e-03 6.004200e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569068 0.9581129 NA NA NA NA NA 1.963414e-01 2.471033e-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 3.292470e+05 0.000000e+00 3.29247e+05 3.292470e+05 3.292470e+05 3.292470e+05 3.292470e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0023096 0.0043061 0.5917101 0.5917129 0.1104400 0.1894970 329247
1 693731 rs12238997 A G 0.0017893 0.0040656 0.6598497 0.6598594 0.1157500 0.1417730 329247
1 707522 rs371890604 G C 0.0018039 0.0045736 0.6932693 0.6932741 0.0971850 0.1293930 329247
1 717587 rs144155419 G A 0.0239500 0.0109190 0.0282872 0.0282768 0.0156580 0.0045926 329247
1 723329 rs189787166 A T -0.0395480 0.0320830 0.2176998 0.2176960 0.0017415 0.0003994 329247
1 730087 rs148120343 T C 0.0011577 0.0056699 0.8382099 0.8382101 0.0563460 0.0127796 329247
1 731718 rs142557973 T C 0.0022504 0.0038563 0.5595205 0.5595133 0.1216300 0.1543530 329247
1 732032 rs61770163 A C 0.0018705 0.0041150 0.6494205 0.6494283 0.1210400 0.1555510 329247
1 734349 rs141242758 T C 0.0025069 0.0038585 0.5158697 0.5158806 0.1208500 0.1525560 329247
1 740284 rs61770167 C T -0.0208650 0.0176760 0.2378598 0.2378355 0.0057707 0.0023962 329247
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0042592 0.0044485 0.3383499 0.3383420 0.056102 0.0309934 329247
23 154923374 rs111332691 T A 0.0015597 0.0048789 0.7492004 0.7492089 0.044857 0.0116556 329247
23 154925045 rs509981 C T 0.0041310 0.0023502 0.0788007 0.0787947 0.245590 0.3634440 329247
23 154925895 rs538470 C T 0.0045375 0.0024040 0.0590949 0.0590959 0.241930 0.3634440 329247
23 154927581 rs644138 G A 0.0046663 0.0022103 0.0347600 0.0347584 0.302080 0.4635760 329247
23 154929412 rs557132 C T 0.0040246 0.0023509 0.0869121 0.0869077 0.245450 0.3568210 329247
23 154929637 rs35185538 CT C 0.0060565 0.0024537 0.0135750 0.0135751 0.229780 0.3011920 329247
23 154929952 rs4012982 CAA C 0.0041009 0.0024724 0.0971807 0.0971820 0.239460 0.3165560 329247
23 154930230 rs781880 A G 0.0041524 0.0023505 0.0773019 0.0772948 0.245860 0.3618540 329247
23 154930487 rs781879 T A 0.0054176 0.0080670 0.5018605 0.5018539 0.019536 0.1263580 329247

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11044  ES:SE:LP:AF:SS:ID   0.0023096:0.0043061:0.227891:0.11044:329247:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11575  ES:SE:LP:AF:SS:ID   0.0017893:0.0040656:0.180555:0.11575:329247:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097185 ES:SE:LP:AF:SS:ID   0.0018039:0.0045736:0.159098:0.097185:329247:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015658 ES:SE:LP:AF:SS:ID   0.02395:0.010919:1.54841:0.015658:329247:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017415    ES:SE:LP:AF:SS:ID   -0.039548:0.032083:0.662142:0.0017415:329247:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056346 ES:SE:LP:AF:SS:ID   0.0011577:0.0056699:0.0766472:0.056346:329247:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12163  ES:SE:LP:AF:SS:ID   0.0022504:0.0038563:0.252184:0.12163:329247:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12104  ES:SE:LP:AF:SS:ID   0.0018705:0.004115:0.187474:0.12104:329247:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12085  ES:SE:LP:AF:SS:ID   0.0025069:0.0038585:0.28746:0.12085:329247:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057707    ES:SE:LP:AF:SS:ID   -0.020865:0.017676:0.623679:0.0057707:329247:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018587    ES:SE:LP:AF:SS:ID   -0.009853:0.033566:0.114012:0.0018587:329247:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86989  ES:SE:LP:AF:SS:ID   -0.0021197:0.0038036:0.238576:0.86989:329247:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015138    ES:SE:LP:AF:SS:ID   -0.002602:0.034632:0.0268213:0.0015138:329247:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12281  ES:SE:LP:AF:SS:ID   0.00078081:0.0037669:0.0779028:0.12281:329247:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14261  ES:SE:LP:AF:SS:ID   0.0014784:0.0037224:0.160359:0.14261:329247:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12292  ES:SE:LP:AF:SS:ID   0.0007439:0.0037617:0.074054:0.12292:329247:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87103  ES:SE:LP:AF:SS:ID   -0.0015093:0.0036659:0.16714:0.87103:329247:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87559  ES:SE:LP:AF:SS:ID   -0.00057664:0.0037264:0.0569905:0.87559:329247:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12851  ES:SE:LP:AF:SS:ID   0.0014952:0.0036749:0.16488:0.12851:329247:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036306 ES:SE:LP:AF:SS:ID   0.0081668:0.0066723:0.655686:0.036306:329247:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87062  ES:SE:LP:AF:SS:ID   -0.0014911:0.0036621:0.16502:0.87062:329247:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87072  ES:SE:LP:AF:SS:ID   -0.0015434:0.0036639:0.171611:0.87072:329247:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87062  ES:SE:LP:AF:SS:ID   -0.0014983:0.003662:0.165936:0.87062:329247:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005051 ES:SE:LP:AF:SS:ID   0.0027801:0.018777:0.0543886:0.005051:329247:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050177    ES:SE:LP:AF:SS:ID   0.0025779:0.018827:0.0500784:0.0050177:329247:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055379    ES:SE:LP:AF:SS:ID   -0.0054176:0.018287:0.115188:0.0055379:329247:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.8707   ES:SE:LP:AF:SS:ID   -0.0014493:0.0036556:0.160038:0.8707:329247:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12585  ES:SE:LP:AF:SS:ID   0.0012983:0.0037299:0.138:0.12585:329247:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87027  ES:SE:LP:AF:SS:ID   -0.0014816:0.003647:0.164582:0.87027:329247:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86955  ES:SE:LP:AF:SS:ID   -0.0014281:0.0036435:0.157965:0.86955:329247:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87042  ES:SE:LP:AF:SS:ID   -0.0015428:0.00365:0.172301:0.87042:329247:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87042  ES:SE:LP:AF:SS:ID   -0.0015416:0.0036502:0.17212:0.87042:329247:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87043  ES:SE:LP:AF:SS:ID   -0.0015658:0.0036503:0.17525:0.87043:329247:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87088  ES:SE:LP:AF:SS:ID   -0.0015429:0.0036596:0.171778:0.87088:329247:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098742 ES:SE:LP:AF:SS:ID   -0.0012037:0.0042534:0.109478:0.098742:329247:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064205    ES:SE:LP:AF:SS:ID   -0.014853:0.016528:0.433138:0.0064205:329247:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87477  ES:SE:LP:AF:SS:ID   -0.0012112:0.003714:0.128229:0.87477:329247:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86419  ES:SE:LP:AF:SS:ID   -0.0017715:0.0036428:0.202906:0.86419:329247:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86956  ES:SE:LP:AF:SS:ID   -0.0024931:0.0036776:0.302919:0.86956:329247:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86647  ES:SE:LP:AF:SS:ID   -0.00099261:0.0036781:0.103882:0.86647:329247:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098673 ES:SE:LP:AF:SS:ID   -0.00083632:0.0044031:0.0709082:0.098673:329247:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   -0.0009061:0.0037204:0.0928144:0.87167:329247:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   -0.00090652:0.0037204:0.0928628:0.87167:329247:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   -0.00090367:0.0037204:0.0925403:0.87167:329247:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87205  ES:SE:LP:AF:SS:ID   -0.0011225:0.0037225:0.117475:0.87205:329247:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12545  ES:SE:LP:AF:SS:ID   0.0016981:0.0037251:0.18809:0.12545:329247:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10533  ES:SE:LP:AF:SS:ID   -0.0019597:0.0040565:0.201336:0.10533:329247:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85555  ES:SE:LP:AF:SS:ID   -0.0018366:0.0036411:0.211853:0.85555:329247:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166  ES:SE:LP:AF:SS:ID   -0.039102:0.032175:0.649268:0.00166:329247:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83831  ES:SE:LP:AF:SS:ID   -0.0013816:0.0035852:0.154921:0.83831:329247:rs376645387