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-1088/ieu-a-1088.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-1088/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 08:45:14 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1088/ieu-a-1088.vcf.gz ...
Read summary statistics for 15347572 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, 1265487 SNPs remain.
After merging with regression SNP LD, 1265487 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0561 (0.005)
Lambda GC: 1.1369
Mean Chi^2: 1.1565
Intercept: 1.0174 (0.0074)
Ratio: 0.1114 (0.0472)
Analysis finished at Wed Feb  5 08:47:47 2020
Total time elapsed: 2.0m:33.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9577,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0,
    "n": 128266,
    "n_snps": 15347572,
    "n_clumped_hits": 3,
    "n_p_sig": 125,
    "n_mono": 0,
    "n_ns": 897774,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 276681,
    "n_est": 129391.7313,
    "ratio_se_n": 1.0044,
    "mean_diff": 5.9697e-07,
    "ratio_diff": 0.4811,
    "sd_y_est1": 1.0362,
    "sd_y_est2": 1.0407,
    "r2_sum1": 0.0011,
    "r2_sum2": 0.001,
    "r2_sum3": 0.001,
    "r2_sum4": 0.0011,
    "ldsc_nsnp_merge_refpanel_ld": 1265487,
    "ldsc_nsnp_merge_regression_ld": 1265487,
    "ldsc_observed_scale_h2_beta": 0.0561,
    "ldsc_observed_scale_h2_se": 0.005,
    "ldsc_intercept_beta": 1.0174,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.1369,
    "ldsc_mean_chisq": 1.1565,
    "ldsc_ratio": 0.1112
}

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 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 58 0 15347571 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 52 0 54202 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 51 0 23779 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.670732e+00 5.794802e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.885565e+07 5.646551e+07 5.60000e+01 3.237004e+07 6.949990e+07 1.146461e+08 2.492397e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.700000e-05 3.403510e-02 -3.92363e-01 -8.634900e-03 -3.790000e-05 8.562300e-03 4.335120e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.470730e-02 2.302450e-02 3.91840e-03 5.378300e-03 1.395020e-02 4.110280e-02 1.050370e-01 ▇▂▂▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.877307e-01 2.922355e-01 0.00000e+00 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.877300e-01 2.922088e-01 0.00000e+00 2.313979e-01 4.836468e-01 7.408492e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.569087e-01 2.444403e-01 1.00000e-03 3.104000e-03 2.360400e-02 2.145052e-01 9.990000e-01 ▇▁▁▁▁
numeric AF_reference 276681 0.9819723 NA NA NA NA NA 1.546682e-01 2.328050e-01 0.00000e+00 1.397800e-03 2.915340e-02 2.204470e-01 1.000000e+00 ▇▁▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.282660e+05 0.000000e+00 1.28266e+05 1.282660e+05 1.282660e+05 1.282660e+05 1.282660e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs367896724 A AC -0.0012131 0.0057533 0.8300000 0.8330013 0.399332 0.4253190 128266
1 10352 rs555500075 T TA 0.0069548 0.0059753 0.2399999 0.2444533 0.388550 0.4375000 128266
1 10511 rs534229142 G A -0.0741494 0.0839495 0.3800004 0.3770948 0.001397 0.0001997 128266
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C -0.0042964 0.0414097 0.9199999 0.9173642 0.995359 0.9930110 128266
1 11008 rs575272151 C G -0.0035179 0.0099355 0.7199992 0.7232836 0.085479 0.0880591 128266
1 11012 rs544419019 C G -0.0035179 0.0099355 0.7199992 0.7232836 0.085479 0.0880591 128266
1 13110 rs540538026 G A -0.0024660 0.0128005 0.8499999 0.8472329 0.060317 0.0267572 128266
1 13116 rs62635286 T G 0.0192638 0.0078154 0.0140001 0.0137074 0.190314 0.0970447 128266
1 13273 rs531730856 G C 0.0001800 0.0089813 0.9800000 0.9840103 0.134857 0.0950479 128266
1 13453 rs568927457 T C 0.0032250 0.0347879 0.9299999 0.9261389 0.006610 0.0007987 128266
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51238318 rs541098394 A T 0.0366397 0.0402953 0.3599996 0.3632025 0.003814 0.0019968 128266
22 51238328 rs553081191 A C -0.0740063 0.0535747 0.1700000 0.1671663 0.001959 0.0005990 128266
22 51238364 rs564490465 C G 0.0635502 0.0402925 0.1100001 0.1147446 0.005514 0.0005990 128266
22 51238394 rs149712012 C T 0.0780992 0.0446863 0.0810009 0.0805123 0.003340 0.0033946 128266
22 51239281 rs8138215 G C 0.0189335 0.0654631 0.7700005 0.7724100 0.001438 0.0111821 128266
22 51239296 rs8137179 T C 0.0189335 0.0654631 0.7700005 0.7724100 0.001438 0.0111821 128266
22 51239304 rs8142977 C T 0.0189335 0.0654631 0.7700005 0.7724100 0.001438 0.0111821 128266
22 51239586 rs535432390 T G 0.0315207 0.0613614 0.6100002 0.6074692 0.001768 0.0001997 128266
22 51239794 rs561893765 C A 0.0285678 0.0681500 0.6800001 0.6750773 0.001586 0.0299521 128266
22 51244237 rs575160859 C T 0.0072881 0.0244709 0.7700005 0.7658357 0.013177 0.0037939 128266

bcf preview

1   10177   rs367896724 A   AC  .   PASS    AF=0.399332 ES:SE:LP:AF:SS:ID   -0.00121311:0.00575332:0.0809219:0.399332:128266:rs367896724
1   10352   rs555500075 T   TA  .   PASS    AF=0.38855  ES:SE:LP:AF:SS:ID   0.00695484:0.00597532:0.619789:0.38855:128266:rs555500075
1   10511   rs534229142 G   A   .   PASS    AF=0.001397 ES:SE:LP:AF:SS:ID   -0.0741494:0.0839495:0.420216:0.001397:128266:rs534229142
1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.995359 ES:SE:LP:AF:SS:ID   -0.00429644:0.0414097:0.0362122:0.995359:128266:rs376342519
1   11008   rs575272151 C   G   .   PASS    AF=0.085479 ES:SE:LP:AF:SS:ID   -0.0035179:0.0099355:0.142668:0.085479:128266:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.085479 ES:SE:LP:AF:SS:ID   -0.0035179:0.0099355:0.142668:0.085479:128266:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.060317 ES:SE:LP:AF:SS:ID   -0.00246602:0.0128005:0.0705811:0.060317:128266:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.190314 ES:SE:LP:AF:SS:ID   0.0192638:0.00781543:1.85387:0.190314:128266:rs62635286
1   13273   rs531730856 G   C   .   PASS    AF=0.134857 ES:SE:LP:AF:SS:ID   0.000179999:0.00898131:0.00877392:0.134857:128266:rs531730856
1   13453   rs568927457 T   C   .   PASS    AF=0.00661  ES:SE:LP:AF:SS:ID   0.00322497:0.0347879:0.0315171:0.00661:128266:rs568927457
1   13483   rs554760071 G   C   .   PASS    AF=0.005165 ES:SE:LP:AF:SS:ID   0.00970762:0.0394163:0.091515:0.005165:128266:rs554760071
1   14464   rs546169444 A   T   .   PASS    AF=0.15676  ES:SE:LP:AF:SS:ID   -0.00565505:0.00817964:0.309804:0.15676:128266:rs546169444
1   14604   rs541940975 A   G   .   PASS    AF=0.192766 ES:SE:LP:AF:SS:ID   0.0126957:0.00750722:1.04096:0.192766:128266:rs541940975
1   14933   rs199856693 G   A   .   PASS    AF=0.047703 ES:SE:LP:AF:SS:ID   0.00150225:0.0138769:0.0409586:0.047703:128266:rs199856693
1   15245   rs576044687 C   T   .   PASS    AF=0.001253 ES:SE:LP:AF:SS:ID   0.0298254:0.0768437:0.154902:0.001253:128266:rs576044687
1   15644   rs564003018 G   A   .   PASS    AF=0.003492 ES:SE:LP:AF:SS:ID   -0.0390967:0.0514119:0.346787:0.003492:128266:rs564003018
1   15820   rs2691315   G   T   .   PASS    AF=0.269827 ES:SE:LP:AF:SS:ID   0.00434363:0.00685471:0.275724:0.269827:128266:rs2691315
1   15903   rs557514207 G   GC  .   PASS    AF=0.407312 ES:SE:LP:AF:SS:ID   -0.0130988:0.00571192:1.65758:0.407312:128266:rs557514207
1   16142   rs548165136 G   A   .   PASS    AF=0.002874 ES:SE:LP:AF:SS:ID   0.0534068:0.0552884:0.481486:0.002874:128266:rs548165136
1   16949   rs199745162 A   C   .   PASS    AF=0.02072  ES:SE:LP:AF:SS:ID   -0.00240505:0.0204146:0.0409586:0.02072:128266:rs199745162
1   18643   rs564023708 G   A   .   PASS    AF=0.006362 ES:SE:LP:AF:SS:ID   0.00620082:0.0376476:0.0604807:0.006362:128266:rs564023708
1   18849   rs533090414 C   G   .   PASS    AF=0.975399 ES:SE:LP:AF:SS:ID   -0.000564197:0.0173475:0.0132283:0.975399:128266:rs533090414
1   30923   rs806731    G   T   .   PASS    AF=0.904769 ES:SE:LP:AF:SS:ID   -0.0142214:0.0103027:0.769551:0.904769:128266:rs806731
1   46285   rs545414834 ATAT    A   .   PASS    AF=0.001688 ES:SE:LP:AF:SS:ID   -0.0087602:0.0646436:0.05061:0.001688:128266:rs545414834
1   47159   rs540662756 T   C   .   PASS    AF=0.065774 ES:SE:LP:AF:SS:ID   0.00385801:0.0122256:0.124939:0.065774:128266:rs540662756
1   49318   rs536836601 A   G   .   PASS    AF=0.001483 ES:SE:LP:AF:SS:ID   -0.0787348:0.0713266:0.568636:0.001483:128266:rs536836601
1   49343   rs553572247 T   C   .   PASS    AF=0.002075 ES:SE:LP:AF:SS:ID   0.0173639:0.0629753:0.107905:0.002075:128266:rs553572247
1   49554   rs539322794 A   G   .   PASS    AF=0.097732 ES:SE:LP:AF:SS:ID   0.00778519:0.0101237:0.356547:0.097732:128266:rs539322794
1   51047   rs559500163 A   T   .   PASS    AF=0.001657 ES:SE:LP:AF:SS:ID   -0.122172:0.0750829:1:0.001657:128266:rs559500163
1   51049   rs528344458 A   C   .   PASS    AF=0.001657 ES:SE:LP:AF:SS:ID   -0.122172:0.0750829:1:0.001657:128266:rs528344458
1   51050   rs551668143 A   T   .   PASS    AF=0.001657 ES:SE:LP:AF:SS:ID   -0.122172:0.0750829:1:0.001657:128266:rs551668143
1   51053   rs565211799 G   T   .   PASS    AF=0.001657 ES:SE:LP:AF:SS:ID   -0.122172:0.0750829:1:0.001657:128266:rs565211799
1   51479   rs116400033 T   A   .   PASS    AF=0.21227  ES:SE:LP:AF:SS:ID   -0.0124269:0.0072005:1.07572:0.21227:128266:rs116400033
1   51762   rs559190862 A   G   .   PASS    AF=0.008258 ES:SE:LP:AF:SS:ID   -0.0273484:0.0331712:0.387216:0.008258:128266:rs559190862
1   51765   rs575564077 C   G   .   PASS    AF=0.008077 ES:SE:LP:AF:SS:ID   -0.025999:0.0332489:0.366532:0.008077:128266:rs575564077
1   52238   rs2691277   T   G   .   PASS    AF=0.978086 ES:SE:LP:AF:SS:ID   0.00332681:0.0212261:0.0555173:0.978086:128266:rs2691277
1   54353   rs140052487 C   A   .   PASS    AF=0.001757 ES:SE:LP:AF:SS:ID   0.0557095:0.0597742:0.455932:0.001757:128266:rs140052487
1   54354   rs569165477 C   T   .   PASS    AF=0.002372 ES:SE:LP:AF:SS:ID   -0.0190674:0.0536911:0.142668:0.002372:128266:rs569165477
1   54490   rs141149254 G   A   .   PASS    AF=0.153509 ES:SE:LP:AF:SS:ID   -0.0253008:0.00807358:2.76955:0.153509:128266:rs141149254
1   54591   rs561234294 A   G   .   PASS    AF=0.002217 ES:SE:LP:AF:SS:ID   -0.0529507:0.0595244:0.431798:0.002217:128266:rs561234294
1   54716   rs569128616 C   T   .   PASS    AF=0.427168 ES:SE:LP:AF:SS:ID   0.00242313:0.00609542:0.161151:0.427168:128266:rs569128616
1   54945   rs569799965 C   A   .   PASS    AF=0.006245 ES:SE:LP:AF:SS:ID   -0.0121773:0.0370797:0.130768:0.006245:128266:rs569799965
1   55164   rs3091274   C   A   .   PASS    AF=0.982937 ES:SE:LP:AF:SS:ID   0.00335341:0.0233743:0.05061:0.982937:128266:rs3091274
1   55249   rs200769871 C   CTATGG  .   PASS    AF=0.009184 ES:SE:LP:AF:SS:ID   0.0370805:0.0292133:0.69897:0.009184:128266:rs200769871
1   55326   rs3107975   T   C   .   PASS    AF=0.015693 ES:SE:LP:AF:SS:ID   -0.0236057:0.0246687:0.468521:0.015693:128266:rs3107975
1   55405   rs372455836 C   T   .   PASS    AF=0.005248 ES:SE:LP:AF:SS:ID   0.0114979:0.0419509:0.107905:0.005248:128266:rs372455836
1   55545   rs28396308  C   T   .   PASS    AF=0.259817 ES:SE:LP:AF:SS:ID   0.00817719:0.00682014:0.638272:0.259817:128266:rs28396308
1   56586   rs541979596 G   A   .   PASS    AF=0.001126 ES:SE:LP:AF:SS:ID   -0.0688798:0.0864226:0.366532:0.001126:128266:rs541979596
1   56829   rs568967163 G   T   .   PASS    AF=0.003955 ES:SE:LP:AF:SS:ID   0.00949751:0.0483493:0.0757207:0.003955:128266:rs568967163
1   57292   rs201418760 C   T   .   PASS    AF=0.020773 ES:SE:LP:AF:SS:ID   -0.0284047:0.0215203:0.721246:0.020773:128266:rs201418760