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-20471/ukb-d-20471.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-20471/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 17:10:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20471/ukb-d-20471.vcf.gz ...
Read summary statistics for 11546759 SNPs.
Dropped 9845 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, 1282674 SNPs remain.
After merging with regression SNP LD, 1282674 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0113 (0.0037)
Lambda GC: 1.0427
Mean Chi^2: 1.0317
Intercept: 1.0053 (0.0061)
Ratio: 0.1677 (0.1908)
Analysis finished at Mon Nov 25 17:12:05 2019
Total time elapsed: 1.0m:54.21s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9477,
    "inflation_factor": 1.0243,
    "mean_EFFECT": -6.1163e-06,
    "n": 116787,
    "n_snps": 11546759,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1164048,
    "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": 246571,
    "n_est": 116985.2732,
    "ratio_se_n": 1.0008,
    "mean_diff": -0,
    "ratio_diff": 11.453,
    "sd_y_est1": 0.1772,
    "sd_y_est2": 0.1774,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282674,
    "ldsc_nsnp_merge_regression_ld": 1282674,
    "ldsc_observed_scale_h2_beta": 0.0113,
    "ldsc_observed_scale_h2_se": 0.0037,
    "ldsc_intercept_beta": 1.0053,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0427,
    "ldsc_mean_chisq": 1.0317,
    "ldsc_ratio": 0.1672
}
 

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 11537519 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 52362 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31763 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.073320e+00 6.184081e+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 7.885383e+07 5.599495e+07 3.02000e+02 3.264686e+07 6.986522e+07 1.147303e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -6.100000e-06 2.568300e-03 -2.65201e-02 -9.622000e-04 -1.030000e-05 9.303000e-04 3.445220e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.025100e-03 1.581900e-03 6.07600e-04 8.344000e-04 1.274400e-03 2.756000e-03 9.183800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.963502e-01 2.891310e-01 0.00000e+00 2.452590e-01 4.948402e-01 7.465416e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.963488e-01 2.891318e-01 0.00000e+00 2.452570e-01 4.948382e-01 7.465407e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.226644e-01 2.606033e-01 3.31740e-03 1.893680e-02 1.038040e-01 3.554245e-01 9.966820e-01 ▇▂▁▁▁
numeric AF_reference 246571 0.9786459 NA NA NA NA NA 2.233978e-01 2.518837e-01 0.00000e+00 1.597440e-02 1.224040e-01 3.556310e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.167870e+05 0.000000e+00 1.16787e+05 1.167870e+05 1.167870e+05 1.167870e+05 1.167870e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0012708 0.0012782 0.3201312 0.3201318 0.1116900 0.1894970 116787
1 693731 rs12238997 A G -0.0011478 0.0012102 0.3429130 0.3429137 0.1167280 0.1417730 116787
1 707522 rs371890604 G C -0.0010389 0.0013581 0.4443130 0.4443097 0.0983160 0.1293930 116787
1 717587 rs144155419 G A -0.0042436 0.0032528 0.1920269 0.1920253 0.0157713 0.0045926 116787
1 730087 rs148120343 T C -0.0006709 0.0016839 0.6903336 0.6903344 0.0569164 0.0127796 116787
1 731718 rs142557973 T C -0.0012031 0.0011482 0.2947569 0.2947572 0.1226600 0.1543530 116787
1 732032 rs61770163 A C -0.0014300 0.0012241 0.2427471 0.2427454 0.1222150 0.1555510 116787
1 734349 rs141242758 T C -0.0011160 0.0011488 0.3313248 0.3313246 0.1219150 0.1525560 116787
1 740284 rs61770167 C T 0.0016060 0.0052457 0.7594881 0.7594895 0.0058564 0.0023962 116787
1 749963 rs529266287 T TAA 0.0012837 0.0011323 0.2569082 0.2569045 0.8690410 0.7641770 116787
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0010670 0.0013506 0.4294929 0.4294924 0.0554582 0.0309934 116787
23 154923374 rs111332691 T A 0.0013816 0.0014721 0.3479621 0.3479586 0.0447610 0.0116556 116787
23 154925045 rs509981 C T -0.0010154 0.0007087 0.1519480 0.1519460 0.2447260 0.3634440 116787
23 154925895 rs538470 C T -0.0009362 0.0007247 0.1964260 0.1964235 0.2411510 0.3634440 116787
23 154927581 rs644138 G A -0.0006371 0.0006669 0.3394126 0.3394111 0.3005500 0.4635760 116787
23 154929412 rs557132 C T -0.0010037 0.0007089 0.1568011 0.1567996 0.2446080 0.3568210 116787
23 154929637 rs35185538 CT C -0.0006518 0.0007407 0.3788602 0.3788581 0.2287410 0.3011920 116787
23 154929952 rs4012982 CAA C -0.0011592 0.0007460 0.1202021 0.1202001 0.2387400 0.3165560 116787
23 154930230 rs781880 A G -0.0010552 0.0007087 0.1365161 0.1365125 0.2450350 0.3618540 116787
23 154930487 rs781879 T A -0.0007940 0.0024113 0.7419233 0.7419240 0.0196427 0.1263580 116787

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11169  ES:SE:LP:AF:SS:ID   -0.00127077:0.0012782:0.494672:0.11169:116787:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116728 ES:SE:LP:AF:SS:ID   -0.00114783:0.00121025:0.464816:0.116728:116787:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098316 ES:SE:LP:AF:SS:ID   -0.00103889:0.00135814:0.352311:0.098316:116787:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157713    ES:SE:LP:AF:SS:ID   -0.0042436:0.00325277:0.716638:0.0157713:116787:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569164    ES:SE:LP:AF:SS:ID   -0.000670876:0.00168392:0.160941:0.0569164:116787:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12266  ES:SE:LP:AF:SS:ID   -0.00120306:0.00114824:0.530536:0.12266:116787:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122215 ES:SE:LP:AF:SS:ID   -0.00142997:0.00122413:0.614846:0.122215:116787:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121915 ES:SE:LP:AF:SS:ID   -0.00111603:0.00114883:0.479746:0.121915:116787:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0058564    ES:SE:LP:AF:SS:ID   0.00160599:0.00524574:0.119479:0.0058564:116787:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869041 ES:SE:LP:AF:SS:ID   0.00128372:0.00113229:0.590222:0.869041:116787:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123676 ES:SE:LP:AF:SS:ID   -0.00126333:0.00112166:0.58496:0.123676:116787:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143339 ES:SE:LP:AF:SS:ID   -0.00104774:0.00110927:0.462306:0.143339:116787:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123798 ES:SE:LP:AF:SS:ID   -0.00120326:0.0011201:0.548651:0.123798:116787:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.86978  ES:SE:LP:AF:SS:ID   0.00122897:0.00109071:0.585284:0.86978:116787:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874574 ES:SE:LP:AF:SS:ID   0.00102645:0.00110911:0.450114:0.874574:116787:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12969  ES:SE:LP:AF:SS:ID   -0.00104642:0.00109374:0.470184:0.12969:116787:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365452    ES:SE:LP:AF:SS:ID   0.00199763:0.0019861:0.502363:0.0365452:116787:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869371 ES:SE:LP:AF:SS:ID   0.00107612:0.00108966:0.490307:0.869371:116787:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869439 ES:SE:LP:AF:SS:ID   0.00113436:0.00109002:0.525743:0.869439:116787:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869371 ES:SE:LP:AF:SS:ID   0.00106957:0.00108964:0.486374:0.869371:116787:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00511276   ES:SE:LP:AF:SS:ID   -0.000202236:0.00557767:0.0127463:0.00511276:116787:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00508172   ES:SE:LP:AF:SS:ID   -0.000135444:0.00559002:0.00847711:0.00508172:116787:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00572442   ES:SE:LP:AF:SS:ID   0.00876571:0.00535307:0.993423:0.00572442:116787:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869445 ES:SE:LP:AF:SS:ID   0.00121093:0.00108764:0.575847:0.869445:116787:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126951 ES:SE:LP:AF:SS:ID   -0.00119064:0.00111033:0.547337:0.126951:116787:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868971 ES:SE:LP:AF:SS:ID   0.00125177:0.00108478:0.604625:0.868971:116787:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868367 ES:SE:LP:AF:SS:ID   0.00106511:0.00108437:0.486806:0.868367:116787:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869162 ES:SE:LP:AF:SS:ID   0.00122018:0.00108587:0.583115:0.869162:116787:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869169 ES:SE:LP:AF:SS:ID   0.00121975:0.00108595:0.582778:0.869169:116787:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869171 ES:SE:LP:AF:SS:ID   0.00121993:0.00108595:0.582889:0.869171:116787:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8696   ES:SE:LP:AF:SS:ID   0.00119263:0.00108873:0.563313:0.8696:116787:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0995445    ES:SE:LP:AF:SS:ID   -0.0010488:0.001266:0.389953:0.0995445:116787:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00659065   ES:SE:LP:AF:SS:ID   0.0124109:0.00485927:1.97271:0.00659065:116787:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873677 ES:SE:LP:AF:SS:ID   0.00117302:0.00110548:0.53963:0.873677:116787:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862954 ES:SE:LP:AF:SS:ID   0.00075535:0.00108412:0.313392:0.862954:116787:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868354 ES:SE:LP:AF:SS:ID   0.00117474:0.00109452:0.547999:0.868354:116787:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865363 ES:SE:LP:AF:SS:ID   0.00122779:0.00109468:0.581632:0.865363:116787:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997419    ES:SE:LP:AF:SS:ID   -0.00104559:0.00130814:0.372511:0.0997419:116787:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870669 ES:SE:LP:AF:SS:ID   0.00104202:0.00110768:0.459858:0.870669:116787:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870669 ES:SE:LP:AF:SS:ID   0.00104203:0.00110768:0.459866:0.870669:116787:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870668 ES:SE:LP:AF:SS:ID   0.00104131:0.00110769:0.459448:0.870668:116787:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870992 ES:SE:LP:AF:SS:ID   0.0010935:0.00110816:0.489781:0.870992:116787:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126545 ES:SE:LP:AF:SS:ID   -0.00122745:0.00110907:0.571205:0.126545:116787:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106326 ES:SE:LP:AF:SS:ID   -0.000738212:0.00120533:0.267416:0.106326:116787:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854426 ES:SE:LP:AF:SS:ID   0.00114802:0.00108388:0.538323:0.854426:116787:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838936 ES:SE:LP:AF:SS:ID   -0.00018087:0.00107354:0.0623788:0.838936:116787:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762923 ES:SE:LP:AF:SS:ID   0.000185208:0.000860592:0.0811292:0.762923:116787:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105363 ES:SE:LP:AF:SS:ID   0.000930879:0.00119016:0.362379:0.105363:116787:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00774411   ES:SE:LP:AF:SS:ID   -0.00282273:0.00439422:0.283469:0.00774411:116787:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129962 ES:SE:LP:AF:SS:ID   -0.00108978:0.00109321:0.496435:0.129962:116787:rs762168062