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-22609_2/ukb-d-22609_2.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-22609_2/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 16:41:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22609_2/ukb-d-22609_2.vcf.gz ...
Read summary statistics for 13188865 SNPs.
Dropped 12152 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, 1283431 SNPs remain.
After merging with regression SNP LD, 1283431 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0351 (0.0052)
Lambda GC: 1.0659
Mean Chi^2: 1.0708
Intercept: 1.0101 (0.0064)
Ratio: 0.1421 (0.091)
Analysis finished at Mon Nov 25 16:43:27 2019
Total time elapsed: 2.0m:17.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9515,
    "inflation_factor": 1.0507,
    "mean_EFFECT": 0,
    "n": 89562,
    "n_snps": 13188865,
    "n_clumped_hits": 0,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1237063,
    "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": 470344,
    "n_est": 89967.144,
    "ratio_se_n": 1.0023,
    "mean_diff": 0,
    "ratio_diff": 22.9049,
    "sd_y_est1": 0.3057,
    "sd_y_est2": 0.3064,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283431,
    "ldsc_nsnp_merge_regression_ld": 1283431,
    "ldsc_observed_scale_h2_beta": 0.0351,
    "ldsc_observed_scale_h2_se": 0.0052,
    "ldsc_intercept_beta": 1.0101,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0659,
    "ldsc_mean_chisq": 1.0708,
    "ldsc_ratio": 0.1427
}

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 13177368 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56246 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33098 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.056306e+00 6.185913e+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 7.899094e+07 5.592967e+07 3.02000e+02 3.286743e+07 7.007836e+07 1.148221e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.990000e-05 7.686700e-03 -8.26536e-02 -2.216200e-03 -4.600000e-06 2.196900e-03 1.138930e-01 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.584200e-03 5.208500e-03 1.19210e-03 1.711300e-03 3.030500e-03 7.956000e-03 2.771690e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.919542e-01 2.908391e-01 0.00000e+00 2.378198e-01 4.893245e-01 7.438922e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.919524e-01 2.908401e-01 0.00000e+00 2.378168e-01 4.893221e-01 7.438921e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.962447e-01 2.557122e-01 1.30740e-03 8.900600e-03 6.697950e-02 3.061200e-01 9.986930e-01 ▇▂▁▁▁
numeric AF_reference 470344 0.9643378 NA NA NA NA NA 2.004542e-01 2.480057e-01 0.00000e+00 6.589500e-03 8.985620e-02 3.158950e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.956200e+04 0.000000e+00 8.95620e+04 8.956200e+04 8.956200e+04 8.956200e+04 8.956200e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0020065 0.0025258 0.4269647 0.4269638 0.1113090 0.1894970 89562
1 693731 rs12238997 A G 0.0016733 0.0023928 0.4843731 0.4843693 0.1162770 0.1417730 89562
1 707522 rs371890604 G C 0.0020418 0.0026883 0.4475453 0.4475432 0.0977315 0.1293930 89562
1 717587 rs144155419 G A -0.0049053 0.0064009 0.4434687 0.4434664 0.0158008 0.0045926 89562
1 723329 rs189787166 A T 0.0126090 0.0187114 0.5003962 0.5003957 0.0017729 0.0003994 89562
1 730087 rs148120343 T C 0.0034176 0.0033203 0.3033367 0.3033350 0.0568096 0.0127796 89562
1 731718 rs142557973 T C 0.0015840 0.0022707 0.4854394 0.4854377 0.1221450 0.1543530 89562
1 732032 rs61770163 A C 0.0009972 0.0024207 0.6803745 0.6803744 0.1218650 0.1555510 89562
1 734349 rs141242758 T C 0.0016830 0.0022725 0.4589443 0.4589417 0.1213800 0.1525560 89562
1 740284 rs61770167 C T -0.0056467 0.0104092 0.5874921 0.5874914 0.0057610 0.0023962 89562
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0001033 0.0026541 0.9689581 0.9689576 0.0552866 0.0309934 89562
23 154923374 rs111332691 T A -0.0013609 0.0028854 0.6371695 0.6371665 0.0449019 0.0116556 89562
23 154925045 rs509981 C T -0.0014035 0.0013911 0.3130423 0.3130402 0.2446180 0.3634440 89562
23 154925895 rs538470 C T -0.0013978 0.0014221 0.3256597 0.3256573 0.2411630 0.3634440 89562
23 154927581 rs644138 G A -0.0012174 0.0013086 0.3522103 0.3522073 0.3003140 0.4635760 89562
23 154929412 rs557132 C T -0.0014324 0.0013915 0.3033123 0.3033121 0.2444790 0.3568210 89562
23 154929637 rs35185538 CT C -0.0013903 0.0014532 0.3387053 0.3387043 0.2288450 0.3011920 89562
23 154929952 rs4012982 CAA C -0.0019167 0.0014646 0.1906299 0.1906281 0.2384420 0.3165560 89562
23 154930230 rs781880 A G -0.0014229 0.0013910 0.3063451 0.3063431 0.2449390 0.3618540 89562
23 154930487 rs781879 T A -0.0052805 0.0047156 0.2628101 0.2628075 0.0196612 0.1263580 89562

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111309 ES:SE:LP:AF:SS:ID   0.00200653:0.00252585:0.369608:0.111309:89562:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116277 ES:SE:LP:AF:SS:ID   0.00167326:0.00239279:0.31482:0.116277:89562:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977315    ES:SE:LP:AF:SS:ID   0.00204181:0.0026883:0.349163:0.0977315:89562:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158008    ES:SE:LP:AF:SS:ID   -0.00490534:0.00640089:0.353137:0.0158008:89562:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177288   ES:SE:LP:AF:SS:ID   0.012609:0.0187114:0.300686:0.00177288:89562:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568096    ES:SE:LP:AF:SS:ID   0.00341758:0.00332027:0.518075:0.0568096:89562:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122145 ES:SE:LP:AF:SS:ID   0.00158401:0.00227071:0.313865:0.122145:89562:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121865 ES:SE:LP:AF:SS:ID   0.000997213:0.0024207:0.167252:0.121865:89562:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12138  ES:SE:LP:AF:SS:ID   0.00168297:0.00227247:0.33824:0.12138:89562:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00576098   ES:SE:LP:AF:SS:ID   -0.00564673:0.0104092:0.230998:0.00576098:89562:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00181104   ES:SE:LP:AF:SS:ID   -0.0127673:0.0200134:0.281069:0.00181104:89562:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869125 ES:SE:LP:AF:SS:ID   -0.00105847:0.00223501:0.196683:0.869125:89562:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158168   ES:SE:LP:AF:SS:ID   -0.0216409:0.019868:0.559008:0.00158168:89562:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12349  ES:SE:LP:AF:SS:ID   0.0016226:0.0022158:0.333486:0.12349:89562:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142997 ES:SE:LP:AF:SS:ID   0.000646573:0.00219358:0.114537:0.142997:89562:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123626 ES:SE:LP:AF:SS:ID   0.00156715:0.00221259:0.319874:0.123626:89562:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870103 ES:SE:LP:AF:SS:ID   -0.00115482:0.00215573:0.227554:0.870103:89562:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874761 ES:SE:LP:AF:SS:ID   -0.00142088:0.00219081:0.286826:0.874761:89562:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12933  ES:SE:LP:AF:SS:ID   0.00132527:0.0021625:0.267619:0.12933:89562:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.035735 ES:SE:LP:AF:SS:ID   0.011304:0.00395275:2.37258:0.035735:89562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86975  ES:SE:LP:AF:SS:ID   -0.00109657:0.00215393:0.214185:0.86975:89562:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869821 ES:SE:LP:AF:SS:ID   -0.00110219:0.00215473:0.215392:0.869821:89562:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869746 ES:SE:LP:AF:SS:ID   -0.00109784:0.00215384:0.21449:0.869746:89562:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0053199    ES:SE:LP:AF:SS:ID   -0.0101999:0.0107515:0.46499:0.0053199:89562:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00528515   ES:SE:LP:AF:SS:ID   -0.010209:0.0107779:0.464032:0.00528515:89562:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00567824   ES:SE:LP:AF:SS:ID   -0.00865804:0.0105824:0.383767:0.00567824:89562:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869731 ES:SE:LP:AF:SS:ID   -0.000961303:0.00214936:0.183961:0.869731:89562:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126712 ES:SE:LP:AF:SS:ID   0.0011034:0.00219415:0.211092:0.126712:89562:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869258 ES:SE:LP:AF:SS:ID   -0.00084535:0.00214376:0.159054:0.869258:89562:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868646 ES:SE:LP:AF:SS:ID   -0.000827814:0.00214238:0.155397:0.868646:89562:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869412 ES:SE:LP:AF:SS:ID   -0.000871902:0.00214574:0.164631:0.869412:89562:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869418 ES:SE:LP:AF:SS:ID   -0.000872949:0.00214588:0.164846:0.869418:89562:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86942  ES:SE:LP:AF:SS:ID   -0.000873064:0.0021459:0.164869:0.86942:89562:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869902 ES:SE:LP:AF:SS:ID   -0.000929908:0.00215168:0.176778:0.869902:89562:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0990065    ES:SE:LP:AF:SS:ID   0.00227838:0.00250415:0.440203:0.0990065:89562:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00651815   ES:SE:LP:AF:SS:ID   -0.00938251:0.00963631:0.481187:0.00651815:89562:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873896 ES:SE:LP:AF:SS:ID   -0.000838557:0.00218364:0.154303:0.873896:89562:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863289 ES:SE:LP:AF:SS:ID   -0.0015313:0.00214183:0.323636:0.863289:89562:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868694 ES:SE:LP:AF:SS:ID   -0.00112116:0.00216307:0.218793:0.868694:89562:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865572 ES:SE:LP:AF:SS:ID   -0.000761159:0.00216336:0.139687:0.865572:89562:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993349    ES:SE:LP:AF:SS:ID   -1.22667e-05:0.00259032:0.00164387:0.0993349:89562:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870874 ES:SE:LP:AF:SS:ID   -0.000768612:0.00218835:0.139412:0.870874:89562:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870874 ES:SE:LP:AF:SS:ID   -0.000768593:0.00218835:0.139408:0.870874:89562:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870871 ES:SE:LP:AF:SS:ID   -0.000768404:0.00218836:0.139369:0.870871:89562:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87123  ES:SE:LP:AF:SS:ID   -0.000650001:0.00218939:0.115457:0.87123:89562:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126307 ES:SE:LP:AF:SS:ID   0.00109339:0.00219172:0.209103:0.126307:89562:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10582  ES:SE:LP:AF:SS:ID   0.00204989:0.0023829:0.409322:0.10582:89562:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85461  ES:SE:LP:AF:SS:ID   -0.000564455:0.00214113:0.101237:0.85461:89562:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168487   ES:SE:LP:AF:SS:ID   0.012472:0.0187688:0.295535:0.00168487:89562:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839219 ES:SE:LP:AF:SS:ID   0.00109803:0.00211466:0.219257:0.839219:89562:rs376645387