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-30000_irnt/ukb-d-30000_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-30000_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 14:50:48 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30000_irnt/ukb-d-30000_irnt.vcf.gz ...
Read summary statistics for 13586281 SNPs.
Dropped 12710 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: 0.1661 (0.0094)
Lambda GC: 1.7005
Mean Chi^2: 2.3979
Intercept: 1.1871 (0.0202)
Ratio: 0.1339 (0.0145)
Analysis finished at Mon Nov 25 14:52:40 2019
Total time elapsed: 1.0m:51.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.4333,
    "mean_EFFECT": 0.0001,
    "n": 350470,
    "n_snps": 13586281,
    "n_clumped_hits": 340,
    "n_p_sig": 78437,
    "n_mono": 0,
    "n_ns": 1251793,
    "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": 569192,
    "n_est": 351806.07,
    "ratio_se_n": 1.0019,
    "mean_diff": 4.9029e-07,
    "ratio_diff": 0.757,
    "sd_y_est1": 0.9996,
    "sd_y_est2": 1.0015,
    "r2_sum1": 0.0811,
    "r2_sum2": 0.0811,
    "r2_sum3": 0.0808,
    "r2_sum4": 0.0806,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1661,
    "ldsc_observed_scale_h2_se": 0.0094,
    "ldsc_intercept_beta": 1.1871,
    "ldsc_intercept_se": 0.0202,
    "ldsc_lambda_gc": 1.7005,
    "ldsc_mean_chisq": 2.3979,
    "ldsc_ratio": 0.1338
}

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 13574235 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 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 9.051337e+00 6.184982e+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 7.902521e+07 5.591483e+07 3.02000e+02 3.293108e+07 7.013883e+07 1.148590e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.043000e-04 1.513960e-02 -4.06143e-01 -4.600000e-03 4.960000e-05 4.769400e-03 3.473290e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.003320e-02 9.678400e-03 1.96240e-03 2.856500e-03 5.263800e-03 1.441880e-02 4.906680e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.404808e-01 3.058732e-01 0.00000e+00 1.596129e-01 4.193706e-01 7.062915e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.404803e-01 3.058734e-01 0.00000e+00 1.596123e-01 4.193707e-01 7.062921e-01 9.999999e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908061e-01 2.544034e-01 1.00000e-03 7.430500e-03 6.003410e-02 2.953170e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569192 0.9581054 NA NA NA NA NA 1.963357e-01 2.471015e-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 3.504700e+05 0.000000e+00 3.50470e+05 3.504700e+05 3.504700e+05 3.504700e+05 3.504700e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0055375 0.0041799 0.1852371 0.1852360 0.1106760 0.1894970 350470
1 693731 rs12238997 A G -0.0009142 0.0039495 0.8169489 0.8169491 0.1158570 0.1417730 350470
1 707522 rs371890604 G C -0.0027448 0.0044415 0.5365794 0.5365790 0.0972836 0.1293930 350470
1 717587 rs144155419 G A 0.0021720 0.0105860 0.8374340 0.8374334 0.0157162 0.0045926 350470
1 723329 rs189787166 A T 0.0026016 0.0313711 0.9339069 0.9339066 0.0017251 0.0003994 350470
1 730087 rs148120343 T C -0.0027130 0.0055005 0.6218577 0.6218560 0.0564931 0.0127796 350470
1 731718 rs142557973 T C -0.0010863 0.0037456 0.7717933 0.7717934 0.1217790 0.1543530 350470
1 732032 rs61770163 A C -0.0019736 0.0039960 0.6213882 0.6213882 0.1211750 0.1555510 350470
1 734349 rs141242758 T C -0.0012569 0.0037476 0.7373234 0.7373230 0.1210090 0.1525560 350470
1 740284 rs61770167 C T -0.0067488 0.0171456 0.6938634 0.6938634 0.0057872 0.0023962 350470
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0121034 0.0043265 0.0051500 0.0051497 0.0561510 0.0309934 350470
23 154923374 rs111332691 T A -0.0002784 0.0047559 0.9533149 0.9533147 0.0447913 0.0116556 350470
23 154925045 rs509981 C T -0.0077464 0.0022887 0.0007126 0.0007125 0.2454590 0.3634440 350470
23 154925895 rs538470 C T -0.0074127 0.0023410 0.0015432 0.0015431 0.2418070 0.3634440 350470
23 154927581 rs644138 G A -0.0037898 0.0021521 0.0782492 0.0782493 0.3020060 0.4635760 350470
23 154929412 rs557132 C T -0.0076738 0.0022893 0.0008025 0.0008024 0.2453140 0.3568210 350470
23 154929637 rs35185538 CT C -0.0055217 0.0023896 0.0208478 0.0208473 0.2295360 0.3011920 350470
23 154929952 rs4012982 CAA C -0.0074941 0.0024079 0.0018563 0.0018561 0.2392700 0.3165560 350470
23 154930230 rs781880 A G -0.0076516 0.0022889 0.0008292 0.0008291 0.2457250 0.3618540 350470
23 154930487 rs781879 T A -0.0087754 0.0078550 0.2639229 0.2639228 0.0195300 0.1263580 350470

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110676 ES:SE:LP:AF:SS:ID   -0.00553751:0.00417987:0.732272:0.110676:350470:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115857 ES:SE:LP:AF:SS:ID   -0.000914194:0.0039495:0.0878051:0.115857:350470:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972836    ES:SE:LP:AF:SS:ID   -0.00274481:0.00444148:0.270366:0.0972836:350470:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157162    ES:SE:LP:AF:SS:ID   0.00217201:0.010586:0.0770494:0.0157162:350470:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172511   ES:SE:LP:AF:SS:ID   0.00260163:0.0313711:0.0296964:0.00172511:350470:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564931    ES:SE:LP:AF:SS:ID   -0.00271298:0.00550053:0.206309:0.0564931:350470:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121779 ES:SE:LP:AF:SS:ID   -0.00108633:0.00374558:0.112499:0.121779:350470:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121175 ES:SE:LP:AF:SS:ID   -0.00197355:0.00399598:0.206637:0.121175:350470:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121009 ES:SE:LP:AF:SS:ID   -0.00125694:0.00374758:0.132342:0.121009:350470:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578718   ES:SE:LP:AF:SS:ID   -0.00674881:0.0171456:0.158726:0.00578718:350470:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188411   ES:SE:LP:AF:SS:ID   -0.0479915:0.0323597:0.859935:0.00188411:350470:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869714 ES:SE:LP:AF:SS:ID   0.00183324:0.00369486:0.207761:0.869714:350470:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153229   ES:SE:LP:AF:SS:ID   0.00706708:0.0334251:0.0795886:0.00153229:350470:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122937 ES:SE:LP:AF:SS:ID   -0.0011343:0.00365906:0.121155:0.122937:350470:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142739 ES:SE:LP:AF:SS:ID   -0.00108776:0.00361701:0.117124:0.142739:350470:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123054 ES:SE:LP:AF:SS:ID   -0.00128593:0.00365394:0.139727:0.123054:350470:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87085  ES:SE:LP:AF:SS:ID   0.000441629:0.00356062:0.0451354:0.87085:350470:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87545  ES:SE:LP:AF:SS:ID   0.00174141:0.00361967:0.200351:0.87545:350470:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128671 ES:SE:LP:AF:SS:ID   -3.70574e-05:0.00356955:0.00361224:0.128671:350470:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363369    ES:SE:LP:AF:SS:ID   -0.00500292:0.00648087:0.356406:0.0363369:350470:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870444 ES:SE:LP:AF:SS:ID   0.000297677:0.00355688:0.0299773:0.870444:350470:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870545 ES:SE:LP:AF:SS:ID   0.000295625:0.00355845:0.0297508:0.870545:350470:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870439 ES:SE:LP:AF:SS:ID   0.000305542:0.00355674:0.0307976:0.870439:350470:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504302   ES:SE:LP:AF:SS:ID   0.0204121:0.0182714:0.578518:0.00504302:350470:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500989   ES:SE:LP:AF:SS:ID   0.0204374:0.0183201:0.5774:0.00500989:350470:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558062   ES:SE:LP:AF:SS:ID   0.00896457:0.0176971:0.212917:0.00558062:350470:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870523 ES:SE:LP:AF:SS:ID   0.00050619:0.0035505:0.0522571:0.870523:350470:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126014 ES:SE:LP:AF:SS:ID   -0.000697268:0.00362311:0.0719167:0.126014:350470:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870086 ES:SE:LP:AF:SS:ID   0.000798874:0.00354194:0.0853639:0.870086:350470:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869364 ES:SE:LP:AF:SS:ID   0.000335425:0.00353858:0.034102:0.869364:350470:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87024  ES:SE:LP:AF:SS:ID   0.000676733:0.00354501:0.0712939:0.87024:350470:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870246 ES:SE:LP:AF:SS:ID   0.000685089:0.00354526:0.072234:0.870246:350470:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870255 ES:SE:LP:AF:SS:ID   0.000679771:0.00354537:0.0716298:0.870255:350470:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870697 ES:SE:LP:AF:SS:ID   0.000636084:0.00355439:0.0665269:0.870697:350470:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988386    ES:SE:LP:AF:SS:ID   -0.00274495:0.00413144:0.295481:0.0988386:350470:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647163   ES:SE:LP:AF:SS:ID   0.000122281:0.0159883:0.00265818:0.00647163:350470:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874605 ES:SE:LP:AF:SS:ID   0.0014072:0.00360746:0.157093:0.874605:350470:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863994 ES:SE:LP:AF:SS:ID   0.0010512:0.00353762:0.115571:0.863994:350470:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869378 ES:SE:LP:AF:SS:ID   0.00104886:0.00357195:0.114054:0.869378:350470:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866336 ES:SE:LP:AF:SS:ID   0.000816053:0.00357278:0.0865417:0.866336:350470:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987496    ES:SE:LP:AF:SS:ID   0.000578028:0.00427853:0.0493757:0.0987496:350470:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87152  ES:SE:LP:AF:SS:ID   0.0012912:0.00361342:0.142161:0.87152:350470:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87152  ES:SE:LP:AF:SS:ID   0.00129151:0.00361342:0.142199:0.87152:350470:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871519 ES:SE:LP:AF:SS:ID   0.00129373:0.00361349:0.142473:0.871519:350470:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87189  ES:SE:LP:AF:SS:ID   0.00126202:0.00361553:0.138436:0.87189:350470:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125595 ES:SE:LP:AF:SS:ID   -0.00106501:0.00361841:0.114353:0.125595:350470:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105424 ES:SE:LP:AF:SS:ID   -0.00349562:0.00393978:0.426042:0.105424:350470:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855335 ES:SE:LP:AF:SS:ID   0.000236488:0.0035367:0.0237931:0.855335:350470:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164754   ES:SE:LP:AF:SS:ID   -0.0073259:0.0314254:0.0884866:0.00164754:350470:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838287 ES:SE:LP:AF:SS:ID   -0.00131614:0.00348372:0.151453:0.838287:350470:rs376645387