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/ieu-a-import/processed/ieu-a-1024/ieu-a-1024.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/ieu-a-import/processed/ieu-a-1024/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 12:43:08 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1024/ieu-a-1024.vcf.gz ...
Read summary statistics for 464939 SNPs.
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, 454156 SNPs remain.
After merging with regression SNP LD, 454156 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0496 (0.0262)
Lambda GC: 1.0367
Mean Chi^2: 1.084
Intercept: 1.0598 (0.0085)
Ratio: 0.712 (0.101)
Analysis finished at Tue Feb  4 12:43:21 2020
Total time elapsed: 12.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9112,
    "inflation_factor": 1.0446,
    "mean_EFFECT": -0.0004,
    "n": 27098,
    "n_snps": 464939,
    "n_clumped_hits": 26,
    "n_p_sig": 496,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 4,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 1,
    "n_miss_AF_reference": 2678,
    "n_est": 26625.7696,
    "ratio_se_n": 0.9912,
    "mean_diff": 0.0002,
    "ratio_diff": 14.1396,
    "sd_y_est1": 2.1156,
    "sd_y_est2": 2.0971,
    "r2_sum1": 0.3108,
    "r2_sum2": 0.0694,
    "r2_sum3": 0.0707,
    "r2_sum4": 0.0807,
    "ldsc_nsnp_merge_refpanel_ld": 454156,
    "ldsc_nsnp_merge_regression_ld": 454156,
    "ldsc_observed_scale_h2_beta": 0.0496,
    "ldsc_observed_scale_h2_se": 0.0262,
    "ldsc_intercept_beta": 1.0598,
    "ldsc_intercept_se": 0.0085,
    "ldsc_lambda_gc": 1.0367,
    "ldsc_mean_chisq": 1.084,
    "ldsc_ratio": 0.7119
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
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 30 0 464939 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.838297e+00 5.804750e+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 7.793116e+07 5.676715e+07 3.3012e+04 3.088170e+07 6.859557e+07 1.145533e+08 2.492026e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.228000e-04 3.029770e-02 -1.3150e+00 -1.592000e-02 -1.388000e-04 1.555000e-02 9.851000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.467630e-02 1.249880e-02 1.6320e-02 1.912000e-02 2.126000e-02 2.640000e-02 7.757000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.919875e-01 2.919297e-01 0.0000e+00 2.375002e-01 4.906005e-01 7.451007e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.919873e-01 2.919296e-01 0.0000e+00 2.374601e-01 4.905786e-01 7.451217e-01 9.999992e-01 ▇▇▇▇▇
numeric AF 1 0.9999978 NA NA NA NA NA 3.742757e-01 2.557038e-01 1.0000e-04 1.548000e-01 3.195500e-01 5.628375e-01 9.999000e-01 ▇▆▅▃▂
numeric AF_reference 2678 0.9942401 NA NA NA NA NA 3.756917e-01 2.424312e-01 1.9970e-04 1.727240e-01 3.236820e-01 5.527160e-01 9.974040e-01 ▇▇▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 2.709800e+04 0.000000e+00 2.7098e+04 2.709800e+04 2.709800e+04 2.709800e+04 2.709800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 768448 rs12562034 G A -0.024010 0.02807 0.3922997 0.3923510 0.10330 0.191893 27098
1 1005806 rs3934834 C T 0.003846 0.02360 0.8706001 0.8705451 0.13890 0.223442 27098
1 1018704 rs9442372 A G 0.012120 0.01777 0.4954000 0.4952083 0.57150 0.611022 27098
1 1021415 rs3737728 A G 0.027630 0.01929 0.1520999 0.1520441 0.71330 0.812700 27098
1 1030565 rs6687776 C T 0.004449 0.02384 0.8520000 0.8519593 0.15290 0.306709 27098
1 1031540 rs9651273 A G -0.012380 0.01968 0.5294001 0.5293065 0.72000 0.881989 27098
1 1048955 rs4970405 A G -0.031690 0.02897 0.2741000 0.2740031 0.10245 0.110623 27098
1 1049950 rs12726255 A G -0.011760 0.02564 0.6463995 0.6464795 0.13415 0.289736 27098
1 1061166 rs11807848 T C 0.001567 0.01833 0.9319000 0.9318732 0.40825 0.329673 27098
1 1062638 rs9442373 C A -0.004163 0.01816 0.8187000 0.8186823 0.55715 0.574281 27098
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51105556 rs9616812 C T -0.0054860 0.01846 0.7663003 0.7663267 0.47605 0.3628190 27098
22 51109992 rs9628185 T C 0.0003403 0.01844 0.9853000 0.9852763 0.47755 0.4053510 27098
22 51121521 rs7284093 C T 0.0351500 0.02399 0.1428999 0.1428680 0.15965 0.0485224 27098
22 51150473 rs5770820 G A 0.0195900 0.02058 0.3412000 0.3411502 0.22630 0.2462060 27098
22 51151724 rs6010061 C T 0.0085810 0.01812 0.6359003 0.6358101 0.38995 0.6098240 27098
22 51163138 rs715586 C T -0.0030030 0.02469 0.9031999 0.9031935 0.14860 0.0902556 27098
22 51165664 rs8137951 G A 0.0158800 0.01926 0.4095001 0.4096517 0.29905 0.4063500 27098
22 51171693 rs756638 G A -0.0019670 0.01958 0.9199999 0.9199794 0.28930 0.3049120 27098
22 51175626 rs3810648 A G -0.0501000 0.03590 0.1629000 0.1628521 0.06100 0.1084270 27098
23 51666786 rs14115 A G 0.0183300 0.03706 0.6209005 0.6208801 0.04875 NA 27098

bcf preview

1   768448  rs12562034  G   A   .   PASS    AF=0.1033   ES:SE:LP:AF:SS:ID   -0.02401:0.02807:0.406382:0.1033:27098:rs12562034
1   1005806 rs3934834   C   T   .   PASS    AF=0.1389   ES:SE:LP:AF:SS:ID   0.003846:0.0236:0.0601813:0.1389:27098:rs3934834
1   1018704 rs9442372   A   G   .   PASS    AF=0.5715   ES:SE:LP:AF:SS:ID   0.01212:0.01777:0.305044:0.5715:27098:rs9442372
1   1021415 rs3737728   A   G   .   PASS    AF=0.7133   ES:SE:LP:AF:SS:ID   0.02763:0.01929:0.817871:0.7133:27098:rs3737728
1   1030565 rs6687776   C   T   .   PASS    AF=0.1529   ES:SE:LP:AF:SS:ID   0.004449:0.02384:0.0695604:0.1529:27098:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   -0.01238:0.01968:0.276216:0.72:27098:rs9651273
1   1048955 rs4970405   A   G   .   PASS    AF=0.10245  ES:SE:LP:AF:SS:ID   -0.03169:0.02897:0.562091:0.10245:27098:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.13415  ES:SE:LP:AF:SS:ID   -0.01176:0.02564:0.189499:0.13415:27098:rs12726255
1   1061166 rs11807848  T   C   .   PASS    AF=0.40825  ES:SE:LP:AF:SS:ID   0.001567:0.01833:0.0306307:0.40825:27098:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.55715  ES:SE:LP:AF:SS:ID   -0.004163:0.01816:0.0868752:0.55715:27098:rs9442373
1   1064979 rs2298217   C   T   .   PASS    AF=0.1456   ES:SE:LP:AF:SS:ID   -0.01441:0.02474:0.251657:0.1456:27098:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.0714   ES:SE:LP:AF:SS:ID   0.02522:0.03255:0.358129:0.0714:27098:rs12145826
1   1087683 rs9442380   T   C   .   PASS    AF=0.9323   ES:SE:LP:AF:SS:ID   0.06926:0.03399:1.3808:0.9323:27098:rs9442380
1   1090557 rs7553429   A   C   .   PASS    AF=0.026    ES:SE:LP:AF:SS:ID   0.04694:0.04974:0.461678:0.026:27098:rs7553429
1   1094738 rs4970362   A   G   .   PASS    AF=0.6419   ES:SE:LP:AF:SS:ID   0.03031:0.01817:1.02072:0.6419:27098:rs4970362
1   1099342 rs9660710   A   C   .   PASS    AF=0.93475  ES:SE:LP:AF:SS:ID   0.08096:0.03454:1.71919:0.93475:27098:rs9660710
1   1106473 rs4970420   G   A   .   PASS    AF=0.18115  ES:SE:LP:AF:SS:ID   0.001675:0.02203:0.0271494:0.18115:27098:rs4970420
1   1119858 rs1320565   C   T   .   PASS    AF=0.0742   ES:SE:LP:AF:SS:ID   0.01151:0.03189:0.143815:0.0742:27098:rs1320565
1   1135242 rs9729550   A   C   .   PASS    AF=0.26105  ES:SE:LP:AF:SS:ID   0.01675:0.01997:0.396206:0.26105:27098:rs9729550
1   1156131 rs2887286   T   C   .   PASS    AF=0.1725   ES:SE:LP:AF:SS:ID   0.005611:0.02363:0.0902836:0.1725:27098:rs2887286
1   1172907 rs715643    C   T   .   PASS    AF=0.05495  ES:SE:LP:AF:SS:ID   0.03231:0.03696:0.417937:0.05495:27098:rs715643
1   1176597 rs6675798   T   C   .   PASS    AF=0.0969   ES:SE:LP:AF:SS:ID   0.02254:0.02949:0.352031:0.0969:27098:rs6675798
1   1192515 rs7524470   A   G   .   PASS    AF=0.03895  ES:SE:LP:AF:SS:ID   0.03354:0.04728:0.32039:0.03895:27098:rs7524470
1   1194804 rs11804831  T   C   .   PASS    AF=0.1816   ES:SE:LP:AF:SS:ID   0.03146:0.02213:0.809108:0.1816:27098:rs11804831
1   1211292 rs6685064   C   T   .   PASS    AF=0.06485  ES:SE:LP:AF:SS:ID   0.01129:0.03437:0.129304:0.06485:27098:rs6685064
1   1314015 rs2649588   C   T   .   PASS    AF=0.93435  ES:SE:LP:AF:SS:ID   -0.02728:0.03298:0.389233:0.93435:27098:rs2649588
1   1425700 rs819980    T   C   .   PASS    AF=0.0753   ES:SE:LP:AF:SS:ID   -0.005013:0.02981:0.0622816:0.0753:27098:rs819980
1   1462766 rs9439462   C   T   .   PASS    AF=0.0332   ES:SE:LP:AF:SS:ID   -0.0228:0.04204:0.230844:0.0332:27098:rs9439462
1   1478180 rs3766178   T   C   .   PASS    AF=0.285    ES:SE:LP:AF:SS:ID   0.0008849:0.01952:0.0160131:0.285:27098:rs3766178
1   1485984 rs2031709   C   A   .   PASS    AF=0.0192   ES:SE:LP:AF:SS:ID   0.05961:0.06072:0.486383:0.0192:27098:rs2031709
1   1486834 rs3128342   C   A   .   PASS    AF=0.43305  ES:SE:LP:AF:SS:ID   -0.005414:0.01745:0.121248:0.43305:27098:rs3128342
1   1493727 rs880051    G   A   .   PASS    AF=0.24005  ES:SE:LP:AF:SS:ID   -0.0003967:0.02056:0.00674017:0.24005:27098:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.12135  ES:SE:LP:AF:SS:ID   0.004194:0.02616:0.059135:0.12135:27098:rs2296716
1   1505255 rs6603793   C   T   .   PASS    AF=0.32015  ES:SE:LP:AF:SS:ID   0.01471:0.01894:0.359121:0.32015:27098:rs6603793
1   1509034 rs7520996   T   C   .   PASS    AF=0.29855  ES:SE:LP:AF:SS:ID   0.01117:0.0193:0.249569:0.29855:27098:rs7520996
1   1706160 rs7531583   A   G   .   PASS    AF=0.7761   ES:SE:LP:AF:SS:ID   -0.03384:0.02058:0.999566:0.7761:27098:rs7531583
1   1745726 rs16825336  G   A   .   PASS    AF=0.09145  ES:SE:LP:AF:SS:ID   0.04283:0.02796:0.901356:0.09145:27098:rs16825336
1   1748734 rs2180311   T   C   .   PASS    AF=0.5043   ES:SE:LP:AF:SS:ID   -0.02126:0.01739:0.654626:0.5043:27098:rs2180311
1   1781220 rs6681938   T   C   .   PASS    AF=0.31085  ES:SE:LP:AF:SS:ID   -0.03053:0.01884:0.978397:0.31085:27098:rs6681938
1   1793111 rs10907192  A   G   .   PASS    AF=0.95105  ES:SE:LP:AF:SS:ID   -0.0113:0.03807:0.115488:0.95105:27098:rs10907192
1   1801034 rs4648592   G   A   .   PASS    AF=0.27185  ES:SE:LP:AF:SS:ID   -0.001318:0.02005:0.0233749:0.27185:27098:rs4648592
1   1810090 rs7525092   C   T   .   PASS    AF=0.2732   ES:SE:LP:AF:SS:ID   -0.002082:0.02001:0.0375833:0.2732:27098:rs7525092
1   1844046 rs2474460   C   T   .   PASS    AF=0.4962   ES:SE:LP:AF:SS:ID   -0.02742:0.01735:0.943095:0.4962:27098:rs2474460
1   1873625 rs12758705  G   A   .   PASS    AF=0.26505  ES:SE:LP:AF:SS:ID   0.007691:0.02015:0.15323:0.26505:27098:rs12758705
1   1874581 rs2803329   A   G   .   PASS    AF=0.80375  ES:SE:LP:AF:SS:ID   -0.02301:0.02184:0.534617:0.80375:27098:rs2803329
1   1888193 rs3820011   C   A   .   PASS    AF=0.27525  ES:SE:LP:AF:SS:ID   -0.01159:0.01995:0.250805:0.27525:27098:rs3820011
1   1892325 rs2803291   T   C   .   PASS    AF=0.8061   ES:SE:LP:AF:SS:ID   -0.00731:0.02282:0.125634:0.8061:27098:rs2803291
1   2024064 rs2459994   C   T   .   PASS    AF=0.1641   ES:SE:LP:AF:SS:ID   0.003037:0.02277:0.0487111:0.1641:27098:rs2459994
1   2026361 rs12755035  G   A   .   PASS    AF=0.13345  ES:SE:LP:AF:SS:ID   0.00839:0.02636:0.124765:0.13345:27098:rs12755035
1   2026749 rs884080    A   G   .   PASS    AF=0.4517   ES:SE:LP:AF:SS:ID   -0.005972:0.01763:0.13389:0.4517:27098:rs884080