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-22601_31113033/ukb-d-22601_31113033.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-22601_31113033/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 14:58:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22601_31113033/ukb-d-22601_31113033.vcf.gz ...
Read summary statistics for 10582923 SNPs.
Dropped 8495 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, 1280985 SNPs remain.
After merging with regression SNP LD, 1280985 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0008 (0.0052)
Lambda GC: 1.0014
Mean Chi^2: 1.0016
Intercept: 1.003 (0.0062)
Ratio: 1.8556 (3.8848)
Analysis finished at Mon Nov 25 15:00:38 2019
Total time elapsed: 2.0m:32.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9443,
    "inflation_factor": 0.9992,
    "mean_EFFECT": -4.4111e-06,
    "n": 89866,
    "n_snps": 10582923,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1116371,
    "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": 208366,
    "n_est": 89971.8147,
    "ratio_se_n": 1.0006,
    "mean_diff": -0,
    "ratio_diff": 36.5,
    "sd_y_est1": 0.1537,
    "sd_y_est2": 0.1538,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1280985,
    "ldsc_nsnp_merge_regression_ld": 1280985,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.003,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0014,
    "ldsc_mean_chisq": 1.0016,
    "ldsc_ratio": 1.875
}

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 10574998 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 49943 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30869 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.075231e+00 6.178534e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.879881e+07 5.605266e+07 3.0200e+02 3.256587e+07 6.974175e+07 1.147421e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.400000e-06 2.007600e-03 -1.9320e-02 -8.627000e-04 -1.390000e-05 8.282000e-04 2.491410e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.663500e-03 1.125000e-03 5.9970e-04 8.083000e-04 1.145100e-03 2.193500e-03 6.376400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.000458e-01 2.883348e-01 0.0000e+00 2.505238e-01 5.001693e-01 7.494057e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.000441e-01 2.883359e-01 0.0000e+00 2.505213e-01 5.001674e-01 7.494053e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.416659e-01 2.625198e-01 5.7817e-03 2.958050e-02 1.307520e-01 3.868590e-01 9.942180e-01 ▇▂▂▁▁
numeric AF_reference 208366 0.9803111 NA NA NA NA NA 2.416067e-01 2.534808e-01 0.0000e+00 3.035140e-02 1.477640e-01 3.839860e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.986600e+04 0.000000e+00 8.9866e+04 8.986600e+04 8.986600e+04 8.986600e+04 8.986600e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0002842 0.0012670 0.8225110 0.8225101 0.1114870 0.1894970 89866
1 693731 rs12238997 A G 0.0000260 0.0012002 0.9826960 0.9826960 0.1164980 0.1417730 89866
1 707522 rs371890604 G C 0.0005475 0.0013493 0.6849360 0.6849347 0.0978285 0.1293930 89866
1 717587 rs144155419 G A -0.0010307 0.0032140 0.7484486 0.7484488 0.0158090 0.0045926 89866
1 730087 rs148120343 T C 0.0010657 0.0016643 0.5219441 0.5219432 0.0569661 0.0127796 89866
1 731718 rs142557973 T C 0.0001762 0.0011389 0.8770319 0.8770308 0.1223780 0.1543530 89866
1 732032 rs61770163 A C -0.0001196 0.0012142 0.9215640 0.9215632 0.1220530 0.1555510 89866
1 734349 rs141242758 T C 0.0001318 0.0011398 0.9079679 0.9079673 0.1216170 0.1525560 89866
1 740284 rs61770167 C T 0.0055570 0.0052085 0.2860230 0.2860206 0.0057975 0.0023962 89866
1 749963 rs529266287 T TAA 0.0002121 0.0011214 0.8499610 0.8499606 0.8689590 0.7641770 89866
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0008954 0.0013331 0.5017935 0.5017900 0.0553576 0.0309934 89866
23 154923374 rs111332691 T A -0.0021748 0.0014513 0.1339930 0.1339887 0.0449113 0.0116556 89866
23 154925045 rs509981 C T 0.0006464 0.0006999 0.3557124 0.3557089 0.2444280 0.3634440 89866
23 154925895 rs538470 C T 0.0007586 0.0007157 0.2891479 0.2891447 0.2408760 0.3634440 89866
23 154927581 rs644138 G A 0.0003677 0.0006584 0.5764637 0.5764629 0.3001910 0.4635760 89866
23 154929412 rs557132 C T 0.0006596 0.0007002 0.3461728 0.3461700 0.2442750 0.3568210 89866
23 154929637 rs35185538 CT C 0.0003675 0.0007311 0.6151825 0.6151809 0.2286930 0.3011920 89866
23 154929952 rs4012982 CAA C 0.0005883 0.0007368 0.4246157 0.4246139 0.2381980 0.3165560 89866
23 154930230 rs781880 A G 0.0006678 0.0006999 0.3400322 0.3400298 0.2447120 0.3618540 89866
23 154930487 rs781879 T A 0.0005594 0.0023743 0.8137311 0.8137308 0.0196791 0.1263580 89866

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111487 ES:SE:LP:AF:SS:ID   0.000284215:0.00126702:0.0848583:0.111487:89866:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116498 ES:SE:LP:AF:SS:ID   2.60316e-05:0.00120022:0.00758081:0.116498:89866:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978285    ES:SE:LP:AF:SS:ID   0.000547463:0.0013493:0.16435:0.0978285:89866:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015809 ES:SE:LP:AF:SS:ID   -0.00103067:0.00321396:0.125838:0.015809:89866:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569661    ES:SE:LP:AF:SS:ID   0.00106572:0.00166427:0.282376:0.0569661:89866:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122378 ES:SE:LP:AF:SS:ID   0.000176233:0.00113894:0.0569846:0.122378:89866:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122053 ES:SE:LP:AF:SS:ID   -0.00011956:0.00121424:0.0354745:0.122053:89866:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121617 ES:SE:LP:AF:SS:ID   0.000131763:0.00113979:0.0419295:0.121617:89866:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00579754   ES:SE:LP:AF:SS:ID   0.00555695:0.00520854:0.543599:0.00579754:89866:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868959 ES:SE:LP:AF:SS:ID   0.00021213:0.00112138:0.070601:0.868959:89866:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123678 ES:SE:LP:AF:SS:ID   0.000280751:0.00111169:0.096573:0.123678:89866:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143191 ES:SE:LP:AF:SS:ID   0.000935113:0.00110063:0.402807:0.143191:89866:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123813 ES:SE:LP:AF:SS:ID   0.000278015:0.00111009:0.095693:0.123813:89866:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869927 ES:SE:LP:AF:SS:ID   -0.000507154:0.00108162:0.194394:0.869927:89866:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87461  ES:SE:LP:AF:SS:ID   -0.000436117:0.00109926:0.16017:0.87461:89866:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12951  ES:SE:LP:AF:SS:ID   0.00046695:0.00108493:0.175934:0.12951:89866:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0357365    ES:SE:LP:AF:SS:ID   0.00218373:0.00198487:0.566622:0.0357365:89866:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869574 ES:SE:LP:AF:SS:ID   -0.000523142:0.00108067:0.201818:0.869574:89866:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869652 ES:SE:LP:AF:SS:ID   -0.000541184:0.00108115:0.209941:0.869652:89866:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   -0.000523991:0.00108062:0.202213:0.86957:89866:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869566 ES:SE:LP:AF:SS:ID   -0.000532522:0.00107848:0.20658:0.869566:89866:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   0.000332285:0.00110096:0.117592:0.126879:89866:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869094 ES:SE:LP:AF:SS:ID   -0.000612228:0.00107569:0.244694:0.869094:89866:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868498 ES:SE:LP:AF:SS:ID   -0.000607568:0.00107503:0.242632:0.868498:89866:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869245 ES:SE:LP:AF:SS:ID   -0.00060178:0.00107667:0.239418:0.869245:89866:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869251 ES:SE:LP:AF:SS:ID   -0.000601411:0.00107674:0.239222:0.869251:89866:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869252 ES:SE:LP:AF:SS:ID   -0.000596946:0.00107675:0.23709:0.869252:89866:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869724 ES:SE:LP:AF:SS:ID   -0.000541001:0.00107961:0.21021:0.869724:89866:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991203    ES:SE:LP:AF:SS:ID   0.00068579:0.00125685:0.232613:0.0991203:89866:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00649047   ES:SE:LP:AF:SS:ID   -0.00279077:0.00485068:0.247902:0.00649047:89866:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873732 ES:SE:LP:AF:SS:ID   -0.000367476:0.00109565:0.132339:0.873732:89866:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863116 ES:SE:LP:AF:SS:ID   -0.00052935:0.00107467:0.205989:0.863116:89866:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868511 ES:SE:LP:AF:SS:ID   -0.000585248:0.0010854:0.229332:0.868511:89866:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86539  ES:SE:LP:AF:SS:ID   -0.000232681:0.00108556:0.0807749:0.86539:89866:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994301    ES:SE:LP:AF:SS:ID   0.000440366:0.00129996:0.133833:0.0994301:89866:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870696 ES:SE:LP:AF:SS:ID   -0.00030966:0.00109805:0.109056:0.870696:89866:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870695 ES:SE:LP:AF:SS:ID   -0.000309644:0.00109805:0.109049:0.870695:89866:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870693 ES:SE:LP:AF:SS:ID   -0.000309436:0.00109805:0.108968:0.870693:89866:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871061 ES:SE:LP:AF:SS:ID   -0.000347925:0.00109857:0.12409:0.871061:89866:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126484 ES:SE:LP:AF:SS:ID   0.000299096:0.00109968:0.10478:0.126484:89866:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106022 ES:SE:LP:AF:SS:ID   0.000309885:0.00119544:0.0993795:0.106022:89866:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854451 ES:SE:LP:AF:SS:ID   -0.000183636:0.00107441:0.063341:0.854451:89866:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839008 ES:SE:LP:AF:SS:ID   -0.000536348:0.0010614:0.212302:0.839008:89866:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.76317  ES:SE:LP:AF:SS:ID   -0.000829287:0.000853359:0.479966:0.76317:89866:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10519  ES:SE:LP:AF:SS:ID   0.000948192:0.00117606:0.376642:0.10519:89866:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00773441   ES:SE:LP:AF:SS:ID   -0.00193314:0.0043571:0.182252:0.00773441:89866:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129876 ES:SE:LP:AF:SS:ID   0.000445456:0.00108428:0.166728:0.129876:89866:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129602 ES:SE:LP:AF:SS:ID   0.000433831:0.00108286:0.161976:0.129602:89866:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104469 ES:SE:LP:AF:SS:ID   0.000974714:0.00118513:0.386346:0.104469:89866:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00900456   ES:SE:LP:AF:SS:ID   0.00246745:0.00418213:0.255556:0.00900456:89866:rs146076599