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-22617_3311/ukb-d-22617_3311.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-22617_3311/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 15:34:58 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22617_3311/ukb-d-22617_3311.vcf.gz ...
Read summary statistics for 10498351 SNPs.
Dropped 8371 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, 1280699 SNPs remain.
After merging with regression SNP LD, 1280699 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.012 (0.0045)
Lambda GC: 1.0192
Mean Chi^2: 1.0247
Intercept: 1.0035 (0.0055)
Ratio: 0.1403 (0.2224)
Analysis finished at Mon Nov 25 15:36:32 2019
Total time elapsed: 1.0m:34.29s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.944,
    "inflation_factor": 1.0355,
    "mean_EFFECT": 6.8579e-06,
    "n": 91149,
    "n_snps": 10498351,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1111737,
    "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": 206560,
    "n_est": 91235.4886,
    "ratio_se_n": 1.0005,
    "mean_diff": 0,
    "ratio_diff": 23.8313,
    "sd_y_est1": 0.1478,
    "sd_y_est2": 0.1479,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1280699,
    "ldsc_nsnp_merge_regression_ld": 1280699,
    "ldsc_observed_scale_h2_beta": 0.012,
    "ldsc_observed_scale_h2_se": 0.0045,
    "ldsc_intercept_beta": 1.0035,
    "ldsc_intercept_se": 0.0055,
    "ldsc_lambda_gc": 1.0192,
    "ldsc_mean_chisq": 1.0247,
    "ldsc_ratio": 0.1417
}

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 10490547 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 49701 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30746 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.075992e+00 6.178193e+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 7.879203e+07 5.605337e+07 3.02000e+02 3.255697e+07 6.973549e+07 1.147386e+08 2.492300e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 6.900000e-06 1.898800e-03 -1.82722e-02 -8.220000e-04 -7.400000e-06 8.118000e-04 2.091720e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.563600e-03 1.042200e-03 5.72200e-04 7.705000e-04 1.085000e-03 2.055300e-03 5.919200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.941967e-01 2.902115e-01 0.00000e+00 2.414265e-01 4.924884e-01 7.454096e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.941950e-01 2.902125e-01 0.00000e+00 2.414238e-01 4.924863e-01 7.454084e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.434667e-01 2.626211e-01 6.07390e-03 3.077100e-02 1.333390e-01 3.896520e-01 9.939260e-01 ▇▂▂▁▁
numeric AF_reference 206560 0.9803245 NA NA NA NA NA 2.433669e-01 2.535592e-01 0.00000e+00 3.214860e-02 1.501600e-01 3.865810e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.114900e+04 0.000000e+00 9.11490e+04 9.114900e+04 9.114900e+04 9.114900e+04 9.114900e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0009107 0.0012104 0.4518247 0.4518240 0.1114870 0.1894970 91149
1 693731 rs12238997 A G -0.0011420 0.0011464 0.3191677 0.3191672 0.1164590 0.1417730 91149
1 707522 rs371890604 G C 0.0000192 0.0012883 0.9881140 0.9881143 0.0978765 0.1293930 91149
1 717587 rs144155419 G A -0.0055603 0.0030710 0.0702085 0.0702055 0.0157837 0.0045926 91149
1 730087 rs148120343 T C 0.0003435 0.0015890 0.8288761 0.8288750 0.0569973 0.0127796 91149
1 731718 rs142557973 T C -0.0006342 0.0010879 0.5599355 0.5599318 0.1223590 0.1543530 91149
1 732032 rs61770163 A C -0.0005678 0.0011599 0.6244519 0.6244510 0.1220470 0.1555510 91149
1 734349 rs141242758 T C -0.0005578 0.0010887 0.6083773 0.6083762 0.1215880 0.1525560 91149
1 749963 rs529266287 T TAA 0.0005788 0.0010709 0.5889047 0.5889039 0.8689170 0.7641770 91149
1 751343 rs28544273 T A -0.0007882 0.0010617 0.4578719 0.4578686 0.1236990 0.2426120 91149
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0021936 0.0012734 0.0849709 0.0849659 0.0552869 0.0309934 91149
23 154923374 rs111332691 T A -0.0020678 0.0013859 0.1356841 0.1356808 0.0448387 0.0116556 91149
23 154925045 rs509981 C T -0.0009746 0.0006679 0.1444981 0.1444945 0.2444670 0.3634440 91149
23 154925895 rs538470 C T -0.0008152 0.0006828 0.2325370 0.2325336 0.2409490 0.3634440 91149
23 154927581 rs644138 G A -0.0002379 0.0006282 0.7049284 0.7049270 0.3001640 0.4635760 91149
23 154929412 rs557132 C T -0.0009882 0.0006681 0.1390839 0.1390804 0.2443160 0.3568210 91149
23 154929637 rs35185538 CT C -0.0009200 0.0006976 0.1872078 0.1872049 0.2286640 0.3011920 91149
23 154929952 rs4012982 CAA C -0.0007814 0.0007032 0.2664238 0.2664215 0.2382530 0.3165560 91149
23 154930230 rs781880 A G -0.0009280 0.0006679 0.1646892 0.1646857 0.2447660 0.3618540 91149
23 154930487 rs781879 T A -0.0015104 0.0022650 0.5048996 0.5048958 0.0196632 0.1263580 91149

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111487 ES:SE:LP:AF:SS:ID   -0.000910708:0.00121044:0.34503:0.111487:91149:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116459 ES:SE:LP:AF:SS:ID   -0.00114202:0.00114641:0.495981:0.116459:91149:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978765    ES:SE:LP:AF:SS:ID   1.9192e-05:0.00128831:0.00519295:0.0978765:91149:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157837    ES:SE:LP:AF:SS:ID   -0.00556028:0.00307099:1.15361:0.0157837:91149:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569973    ES:SE:LP:AF:SS:ID   0.000343456:0.00158901:0.0815104:0.0569973:91149:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122359 ES:SE:LP:AF:SS:ID   -0.000634166:0.00108787:0.251862:0.122359:91149:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122047 ES:SE:LP:AF:SS:ID   -0.000567846:0.00115993:0.204501:0.122047:91149:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121588 ES:SE:LP:AF:SS:ID   -0.000557842:0.0010887:0.215827:0.121588:91149:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868917 ES:SE:LP:AF:SS:ID   0.000578752:0.00107092:0.229955:0.868917:91149:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123699 ES:SE:LP:AF:SS:ID   -0.000788187:0.00106173:0.339256:0.123699:91149:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143202 ES:SE:LP:AF:SS:ID   -0.000785443:0.00105112:0.342065:0.143202:91149:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123834 ES:SE:LP:AF:SS:ID   -0.000748743:0.0010602:0.318716:0.123834:91149:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869892 ES:SE:LP:AF:SS:ID   0.000693607:0.00103306:0.29933:0.869892:91149:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874553 ES:SE:LP:AF:SS:ID   0.000866968:0.00104981:0.388381:0.874553:91149:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129529 ES:SE:LP:AF:SS:ID   -0.000669727:0.0010363:0.28558:0.129529:91149:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358205    ES:SE:LP:AF:SS:ID   -0.000238948:0.00189322:0.0459679:0.0358205:91149:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869539 ES:SE:LP:AF:SS:ID   0.000691949:0.0010322:0.298754:0.869539:91149:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869616 ES:SE:LP:AF:SS:ID   0.000774962:0.00103265:0.343922:0.869616:91149:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869535 ES:SE:LP:AF:SS:ID   0.000693326:0.00103215:0.299505:0.869535:91149:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86952  ES:SE:LP:AF:SS:ID   0.000673325:0.00103003:0.289621:0.86952:91149:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126911 ES:SE:LP:AF:SS:ID   -0.000733296:0.00105148:0.313761:0.126911:91149:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86905  ES:SE:LP:AF:SS:ID   0.000678907:0.00102736:0.293517:0.86905:91149:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868436 ES:SE:LP:AF:SS:ID   0.000640602:0.00102671:0.273541:0.868436:91149:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869199 ES:SE:LP:AF:SS:ID   0.000647013:0.00102829:0.27637:0.869199:91149:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869205 ES:SE:LP:AF:SS:ID   0.000646747:0.00102836:0.276209:0.869205:91149:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869207 ES:SE:LP:AF:SS:ID   0.000645804:0.00102837:0.275714:0.869207:91149:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869687 ES:SE:LP:AF:SS:ID   0.000669173:0.00103112:0.287052:0.869687:91149:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991787    ES:SE:LP:AF:SS:ID   7.82993e-05:0.00119997:0.0232036:0.0991787:91149:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00649624   ES:SE:LP:AF:SS:ID   -0.00401239:0.00462938:0.413305:0.00649624:91149:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873682 ES:SE:LP:AF:SS:ID   0.000864944:0.00104639:0.388844:0.873682:91149:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863058 ES:SE:LP:AF:SS:ID   0.000641462:0.00102642:0.274083:0.863058:91149:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868472 ES:SE:LP:AF:SS:ID   0.000776337:0.00103661:0.343033:0.868472:91149:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865369 ES:SE:LP:AF:SS:ID   0.000789192:0.0010368:0.350127:0.865369:91149:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0995228    ES:SE:LP:AF:SS:ID   -0.000764472:0.00124086:0.269346:0.0995228:91149:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870657 ES:SE:LP:AF:SS:ID   0.000970909:0.00104861:0.450383:0.870657:91149:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870657 ES:SE:LP:AF:SS:ID   0.000970916:0.00104861:0.450387:0.870657:91149:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870654 ES:SE:LP:AF:SS:ID   0.000970922:0.00104862:0.450389:0.870654:91149:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871019 ES:SE:LP:AF:SS:ID   0.000939603:0.0010491:0.431265:0.871019:91149:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126515 ES:SE:LP:AF:SS:ID   -0.000756106:0.00105027:0.326446:0.126515:91149:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106037 ES:SE:LP:AF:SS:ID   0.000238025:0.00114166:0.0783936:0.106037:91149:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85438  ES:SE:LP:AF:SS:ID   0.000449301:0.00102603:0.179497:0.85438:91149:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839153 ES:SE:LP:AF:SS:ID   0.00171493:0.00101375:1.04233:0.839153:91149:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763195 ES:SE:LP:AF:SS:ID   0.00120573:0.000815112:0.856723:0.763195:91149:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105092 ES:SE:LP:AF:SS:ID   -0.00148714:0.00112324:0.731628:0.105092:91149:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00772317   ES:SE:LP:AF:SS:ID   -0.00607653:0.00416196:0.840767:0.00772317:91149:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129904 ES:SE:LP:AF:SS:ID   -0.000672964:0.0010356:0.287514:0.129904:91149:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129636 ES:SE:LP:AF:SS:ID   -0.000667511:0.00103424:0.285116:0.129636:91149:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104365 ES:SE:LP:AF:SS:ID   -0.00143245:0.00113196:0.686747:0.104365:91149:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00906976   ES:SE:LP:AF:SS:ID   -0.0048203:0.00397972:0.646247:0.00906976:91149:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00773917   ES:SE:LP:AF:SS:ID   -0.00605646:0.00417933:0.831794:0.00773917:91149:rs112563271