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-22641_irnt/ukb-d-22641_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-22641_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 14:50:32 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22641_irnt/ukb-d-22641_irnt.vcf.gz ...
Read summary statistics for 13446699 SNPs.
Dropped 12522 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, 1283478 SNPs remain.
After merging with regression SNP LD, 1283478 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0309 (0.0596)
Lambda GC: 1.
Mean Chi^2: 0.9973
Intercept: 1.0014 (0.0057)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 14:53:52 2019
Total time elapsed: 3.0m:19.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9518,
    "inflation_factor": 0.9937,
    "mean_EFFECT": -0.0001,
    "n": 6708,
    "n_snps": 13446699,
    "n_clumped_hits": 1,
    "n_p_sig": 3,
    "n_mono": 0,
    "n_ns": 1246521,
    "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": 536303,
    "n_est": 6782.3444,
    "ratio_se_n": 1.0055,
    "mean_diff": -4.7893e-06,
    "ratio_diff": 0.903,
    "sd_y_est1": 1.0008,
    "sd_y_est2": 1.0063,
    "r2_sum1": 0.0046,
    "r2_sum2": 0.0046,
    "r2_sum3": 0.0045,
    "r2_sum4": 0.0046,
    "ldsc_nsnp_merge_refpanel_ld": 1283478,
    "ldsc_nsnp_merge_regression_ld": 1283478,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0014,
    "ldsc_intercept_se": 0.0057,
    "ldsc_lambda_gc": 1,
    "ldsc_mean_chisq": 0.9973,
    "ldsc_ratio": -0.5185
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 13434841 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56807 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33253 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.052040e+00 6.184012e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.901074e+07 5.592246e+07 302.0000000 3.290665e+07 7.010848e+07 1.148458e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.180000e-05 9.790310e-02 -1.5389400 -2.621970e-02 -1.121000e-04 2.597530e-02 1.291410e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.072470e-02 6.794980e-02 0.0134652 2.060070e-02 3.744640e-02 1.009795e-01 4.203750e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.010306e-01 2.883360e-01 0.0000000 2.519179e-01 5.013465e-01 7.502085e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.010068e-01 2.883503e-01 0.0000000 2.518767e-01 5.013227e-01 7.501992e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.926963e-01 2.548993e-01 0.0010003 7.918000e-03 6.227160e-02 2.991360e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 536303 0.9601164 NA NA NA NA NA 1.977843e-01 2.474349e-01 0.0000000 5.990400e-03 8.626200e-02 3.109030e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.708000e+03 0.000000e+00 6708.0000000 6.708000e+03 6.708000e+03 6.708000e+03 6.708000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0087358 0.0304280 0.7740464 0.7740365 0.1114350 0.1894970 6708
1 693731 rs12238997 A G 0.0068795 0.0287571 0.8109370 0.8109297 0.1152700 0.1417730 6708
1 707522 rs371890604 G C 0.0092038 0.0328106 0.7790925 0.7790828 0.0949025 0.1293930 6708
1 717587 rs144155419 G A 0.0403570 0.0762411 0.5965914 0.5965738 0.0161139 0.0045926 6708
1 723329 rs189787166 A T -0.2188240 0.2143840 0.3074298 0.3073916 0.0019131 0.0003994 6708
1 730087 rs148120343 T C 0.0023430 0.0394613 0.9526551 0.9526535 0.0574570 0.0127796 6708
1 731718 rs142557973 T C 0.0004990 0.0272224 0.9853760 0.9853757 0.1223690 0.1543530 6708
1 732032 rs61770163 A C 0.0026717 0.0290452 0.9267131 0.9267098 0.1216770 0.1555510 6708
1 734349 rs141242758 T C 0.0013017 0.0272544 0.9619070 0.9619061 0.1214610 0.1525560 6708
1 740284 rs61770167 C T -0.1388120 0.1332020 0.2973952 0.2973577 0.0050978 0.0023962 6708
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0519779 0.0295933 0.0790660 0.0790188 0.0580688 0.0309934 6708
23 154923374 rs111332691 T A 0.0132406 0.0329551 0.6878615 0.6878482 0.0447227 0.0116556 6708
23 154925045 rs509981 C T 0.0086755 0.0160186 0.5881201 0.5881029 0.2364910 0.3634440 6708
23 154925895 rs538470 C T 0.0088782 0.0164379 0.5891420 0.5891234 0.2318210 0.3634440 6708
23 154927581 rs644138 G A 0.0206408 0.0149543 0.1675529 0.1675071 0.2954110 0.4635760 6708
23 154929412 rs557132 C T 0.0090462 0.0160331 0.5726233 0.5726051 0.2360640 0.3568210 6708
23 154929637 rs35185538 CT C 0.0200653 0.0167240 0.2302650 0.2302206 0.2225300 0.3011920 6708
23 154929952 rs4012982 CAA C 0.0091208 0.0169323 0.5901399 0.5901216 0.2292870 0.3165560 6708
23 154930230 rs781880 A G 0.0091720 0.0160294 0.5672062 0.5671879 0.2362840 0.3618540 6708
23 154930487 rs781879 T A 0.0532995 0.0555538 0.3373813 0.3373465 0.0187321 0.1263580 6708

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111435 ES:SE:LP:AF:SS:ID   0.00873585:0.030428:0.111233:0.111435:6708:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11527  ES:SE:LP:AF:SS:ID   0.00687947:0.0287571:0.0910129:0.11527:6708:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0949025    ES:SE:LP:AF:SS:ID   0.00920385:0.0328106:0.108411:0.0949025:6708:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0161139    ES:SE:LP:AF:SS:ID   0.040357:0.0762411:0.224323:0.0161139:6708:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00191314   ES:SE:LP:AF:SS:ID   -0.218824:0.214384:0.512254:0.00191314:6708:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.057457 ES:SE:LP:AF:SS:ID   0.00234301:0.0394613:0.0210643:0.057457:6708:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122369 ES:SE:LP:AF:SS:ID   0.000498984:0.0272224:0.00639802:0.122369:6708:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121677 ES:SE:LP:AF:SS:ID   0.00267173:0.0290452:0.0330547:0.121677:6708:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121461 ES:SE:LP:AF:SS:ID   0.00130172:0.0272544:0.0168669:0.121461:6708:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00509781   ES:SE:LP:AF:SS:ID   -0.138812:0.133202:0.526666:0.00509781:6708:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00168514   ES:SE:LP:AF:SS:ID   -0.113442:0.24991:0.187158:0.00168514:6708:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.870009 ES:SE:LP:AF:SS:ID   0.00603005:0.0269064:0.0847706:0.870009:6708:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00169216   ES:SE:LP:AF:SS:ID   0.169921:0.231422:0.334586:0.00169216:6708:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122572 ES:SE:LP:AF:SS:ID   -0.00278845:0.026699:0.0377145:0.122572:6708:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142146 ES:SE:LP:AF:SS:ID   -0.00922104:0.0265064:0.137904:0.142146:6708:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.122721 ES:SE:LP:AF:SS:ID   -0.00359423:0.0266587:0.0492677:0.122721:6708:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870164 ES:SE:LP:AF:SS:ID   0.0067771:0.0258611:0.100571:0.870164:6708:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875984 ES:SE:LP:AF:SS:ID   0.00296764:0.0264016:0.0407167:0.875984:6708:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129338 ES:SE:LP:AF:SS:ID   -0.00349342:0.0259858:0.0491184:0.129338:6708:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0362254    ES:SE:LP:AF:SS:ID   -0.0310265:0.0469705:0.293349:0.0362254:6708:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869678 ES:SE:LP:AF:SS:ID   0.00480323:0.0258448:0.0692705:0.869678:6708:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869822 ES:SE:LP:AF:SS:ID   0.00428932:0.0258556:0.0613582:0.869822:6708:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869679 ES:SE:LP:AF:SS:ID   0.00471417:0.0258449:0.0678957:0.869679:6708:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00475844   ES:SE:LP:AF:SS:ID   -0.140717:0.140008:0.501822:0.00475844:6708:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00471313   ES:SE:LP:AF:SS:ID   -0.143458:0.140526:0.512358:0.00471313:6708:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00549943   ES:SE:LP:AF:SS:ID   -0.0691684:0.128445:0.228966:0.00549943:6708:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   0.00728147:0.025771:0.109281:0.8698:6708:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126305 ES:SE:LP:AF:SS:ID   -0.00706902:0.0263686:0.10312:0.126305:6708:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869186 ES:SE:LP:AF:SS:ID   0.00910987:0.0256974:0.140879:0.869186:6708:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868509 ES:SE:LP:AF:SS:ID   0.00586894:0.0257096:0.0864844:0.868509:6708:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869431 ES:SE:LP:AF:SS:ID   0.0088751:0.025724:0.13662:0.869431:6708:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869435 ES:SE:LP:AF:SS:ID   0.00886187:0.0257261:0.136377:0.869435:6708:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869432 ES:SE:LP:AF:SS:ID   0.00890044:0.0257258:0.13705:0.869432:6708:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87001  ES:SE:LP:AF:SS:ID   0.00714485:0.0258062:0.106853:0.87001:6708:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0965029    ES:SE:LP:AF:SS:ID   0.00617548:0.0305153:0.0759115:0.0965029:6708:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00611181   ES:SE:LP:AF:SS:ID   0.00589862:0.118338:0.017617:0.00611181:6708:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874456 ES:SE:LP:AF:SS:ID   0.00338908:0.0262478:0.0470778:0.874456:6708:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86302  ES:SE:LP:AF:SS:ID   0.00674761:0.0256191:0.10113:0.86302:6708:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868611 ES:SE:LP:AF:SS:ID   0.00720511:0.0259269:0.107295:0.868611:6708:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865694 ES:SE:LP:AF:SS:ID   0.00429996:0.0260031:0.0611487:0.865694:6708:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0973476    ES:SE:LP:AF:SS:ID   -0.0119749:0.0314482:0.152811:0.0973476:6708:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871368 ES:SE:LP:AF:SS:ID   0.00332692:0.0263235:0.0460326:0.871368:6708:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871368 ES:SE:LP:AF:SS:ID   0.00332692:0.0263235:0.0460326:0.871368:6708:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871365 ES:SE:LP:AF:SS:ID   0.00334559:0.0263234:0.0463036:0.871365:6708:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871492 ES:SE:LP:AF:SS:ID   0.00444958:0.026321:0.0626015:0.871492:6708:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125863 ES:SE:LP:AF:SS:ID   -0.00439553:0.0263779:0.0616499:0.125863:6708:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105216 ES:SE:LP:AF:SS:ID   -0.00698416:0.0286407:0.0929376:0.105216:6708:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854476 ES:SE:LP:AF:SS:ID   0.00851818:0.0255719:0.131318:0.854476:6708:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00170502   ES:SE:LP:AF:SS:ID   -0.227714:0.219992:0.521926:0.00170502:6708:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839771 ES:SE:LP:AF:SS:ID   0.00281741:0.0255263:0.0399495:0.839771:6708:rs376645387