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-967/ieu-a-967.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-967/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 18:56:17 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-967/ieu-a-967.vcf.gz ...
Read summary statistics for 8775687 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, 1236964 SNPs remain.
After merging with regression SNP LD, 1236964 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0465 (0.0335)
Lambda GC: 1.1112
Mean Chi^2: 1.1255
Intercept: 1.1424 (0.0078)
Ratio: 1.1348 (0.0619)
Analysis finished at Tue Feb  4 18:57:43 2020
Total time elapsed: 1.0m:26.29s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9504,
    "inflation_factor": 1.0159,
    "mean_EFFECT": 0.0067,
    "n": 18313,
    "n_snps": 8775687,
    "n_clumped_hits": 4,
    "n_p_sig": 258,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 409,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 172131,
    "n_est": 18099.8964,
    "ratio_se_n": 0.9942,
    "mean_diff": -0.0133,
    "ratio_diff": 1.4514,
    "sd_y_est1": 2.6403,
    "sd_y_est2": 2.6249,
    "r2_sum1": 0.0868,
    "r2_sum2": 0.0124,
    "r2_sum3": 0.0126,
    "r2_sum4": 0.0076,
    "ldsc_nsnp_merge_refpanel_ld": 1236964,
    "ldsc_nsnp_merge_regression_ld": 1236964,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.1424,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.1112,
    "ldsc_mean_chisq": 1.1255,
    "ldsc_ratio": 1.1347
}

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 58 0 8775687 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 8.544374e+00 5.697573e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.949664e+07 5.584689e+07 1.31330e+04 3.366794e+07 7.067523e+07 1.147770e+08 2.492183e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 6.665300e-03 1.536247e-01 -5.32113e+00 -3.613200e-02 9.945000e-04 3.938700e-02 1.281370e+01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.151854e-01 6.476411e+01 2.35900e-02 3.196700e-02 4.730500e-02 9.936300e-02 1.835820e+05 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.973861e-01 2.895923e-01 0.00000e+00 2.458221e-01 4.966083e-01 7.482935e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.731158e-01 2.941671e-01 0.00000e+00 2.160738e-01 4.616326e-01 7.266275e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 2.208137e-01 2.592539e-01 6.29000e-05 2.017750e-02 1.061130e-01 3.399760e-01 9.998680e-01 ▇▂▁▁▁
numeric AF_reference 172131 0.9803855 NA NA NA NA NA 2.246995e-01 2.517108e-01 0.00000e+00 2.396170e-02 1.236020e-01 3.470450e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.831300e+04 0.000000e+00 1.83130e+04 1.831300e+04 1.831300e+04 1.831300e+04 1.831300e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 996248 rs28479311 C T 0.0229711 0.045037 0.6177603 0.6100168 0.155587 0.106629 18313
1 998501 rs3813193 G C 0.0244175 0.041068 0.5585679 0.5521358 0.171090 0.206669 18313
1 1002387 rs74048003 A G 0.0111803 0.039293 0.7820653 0.7759991 0.233826 0.244609 18313
1 1002539 rs60442576 G A 0.0065902 0.039056 0.8702499 0.8660026 0.238603 0.343051 18313
1 1004957 rs4073176 G A 0.0072119 0.031263 0.8243860 0.8175587 0.572628 0.550319 18313
1 1004980 rs4073177 G A 0.0065313 0.031241 0.8405141 0.8344005 0.572223 0.550319 18313
1 1005806 rs3934834 C T 0.0061083 0.035815 0.8685020 0.8645763 0.164422 0.223442 18313
1 1006223 rs9442394 G A 0.0047884 0.030921 0.8812380 0.8769311 0.568617 0.547125 18313
1 1006990 rs4326571 G A 0.0213718 0.033634 0.5479867 0.5251529 0.716906 0.816294 18313
1 1007203 rs4633229 A G 0.0172784 0.039023 0.6759507 0.6579287 0.770599 0.841254 18313
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51178607 rs6010067 G C -0.0408824 0.098940 0.7225385 0.6794572 0.0237183 0.0814696 18313
22 51178756 rs141844965 A T -0.1470980 0.134249 0.4278071 0.2732056 0.0078513 0.0059904 18313
22 51179000 rs2283675 C A -0.0358707 0.035054 0.3412518 0.3061668 0.3126320 0.5127800 18313
22 51179770 rs2283676 G A -0.0120594 0.040476 0.7776461 0.7657493 0.2456510 0.3945690 18313
22 51180501 rs5770999 T C 0.0478634 0.036288 0.2263221 0.1871735 0.6890560 0.6369810 18313
22 51180878 rs6010069 A G -0.0034610 0.051525 0.9493560 0.9464457 0.1381390 0.1589460 18313
22 51180934 rs9616824 C T -0.0411554 0.050413 0.4578645 0.4142915 0.1269140 0.1689300 18313
22 51180959 rs6010070 A G -0.0176814 0.052110 0.7522237 0.7343768 0.1342680 0.2056710 18313
22 51182399 rs56238942 A G -0.0346297 0.058600 0.5918546 0.5545536 0.0769605 0.0992412 18313
23 51866774 rs150899468 C A 0.5521320 0.151703 0.1363920 0.0002731 0.9977490 0.9965560 18313

bcf preview

1   996248  rs28479311  C   T   .   PASS    AF=0.155587 ES:SE:LP:AF:SS:ID   0.0229711:0.045037:0.20918:0.155587:18313:rs28479311
1   998501  rs3813193   G   C   .   PASS    AF=0.17109  ES:SE:LP:AF:SS:ID   0.0244175:0.041068:0.252924:0.17109:18313:rs3813193
1   1002387 rs74048003  A   G   .   PASS    AF=0.233826 ES:SE:LP:AF:SS:ID   0.0111803:0.039293:0.106757:0.233826:18313:rs74048003
1   1002539 rs60442576  G   A   .   PASS    AF=0.238603 ES:SE:LP:AF:SS:ID   0.00659024:0.039056:0.060356:0.238603:18313:rs60442576
1   1004957 rs4073176   G   A   .   PASS    AF=0.572628 ES:SE:LP:AF:SS:ID   0.00721194:0.031263:0.0838694:0.572628:18313:rs4073176
1   1004980 rs4073177   G   A   .   PASS    AF=0.572223 ES:SE:LP:AF:SS:ID   0.00653128:0.031241:0.075455:0.572223:18313:rs4073177
1   1005806 rs3934834   C   T   .   PASS    AF=0.164422 ES:SE:LP:AF:SS:ID   0.00610831:0.035815:0.0612292:0.164422:18313:rs3934834
1   1006223 rs9442394   G   A   .   PASS    AF=0.568617 ES:SE:LP:AF:SS:ID   0.00478845:0.030921:0.0549068:0.568617:18313:rs9442394
1   1006990 rs4326571   G   A   .   PASS    AF=0.716906 ES:SE:LP:AF:SS:ID   0.0213718:0.033634:0.26123:0.716906:18313:rs4326571
1   1007203 rs4633229   A   G   .   PASS    AF=0.770599 ES:SE:LP:AF:SS:ID   0.0172784:0.039023:0.170085:0.770599:18313:rs4633229
1   1007222 rs71628928  G   T   .   PASS    AF=0.173925 ES:SE:LP:AF:SS:ID   0.0246926:0.03808:0.28225:0.173925:18313:rs71628928
1   1007432 rs4333796   G   A   .   PASS    AF=0.549815 ES:SE:LP:AF:SS:ID   0.0151989:0.030031:0.201483:0.549815:18313:rs4333796
1   1009234 rs9442366   T   C   .   PASS    AF=0.549519 ES:SE:LP:AF:SS:ID   0.012026:0.029884:0.155071:0.549519:18313:rs9442366
1   1009478 rs9442367   G   C   .   PASS    AF=0.717398 ES:SE:LP:AF:SS:ID   0.0221986:0.033545:0.274205:0.717398:18313:rs9442367
1   1009823 rs12752391  G   A   .   PASS    AF=0.168465 ES:SE:LP:AF:SS:ID   0.00878728:0.036533:0.0888269:0.168465:18313:rs12752391
1   1010717 rs9442368   C   T   .   PASS    AF=0.554936 ES:SE:LP:AF:SS:ID   0.00729958:0.030119:0.0885947:0.554936:18313:rs9442368
1   1012706 rs78632925  T   C   .   PASS    AF=0.446375 ES:SE:LP:AF:SS:ID   0.0196585:0.036752:0.222643:0.446375:18313:rs78632925
1   1014836 rs12401605  A   G   .   PASS    AF=0.523111 ES:SE:LP:AF:SS:ID   0.00522161:0.029877:0.0624711:0.523111:18313:rs12401605
1   1015126 rs36027499  A   G   .   PASS    AF=0.542396 ES:SE:LP:AF:SS:ID   0.0107708:0.029097:0.14135:0.542396:18313:rs36027499
1   1015257 rs9442369   A   G   .   PASS    AF=0.539918 ES:SE:LP:AF:SS:ID   0.0148142:0.029231:0.202088:0.539918:18313:rs9442369
1   1015551 rs9442370   C   T   .   PASS    AF=0.531638 ES:SE:LP:AF:SS:ID   0.00594162:0.029967:0.0714331:0.531638:18313:rs9442370
1   1015716 rs61290587  G   A   .   PASS    AF=0.176948 ES:SE:LP:AF:SS:ID   0.0251579:0.038691:0.28316:0.176948:18313:rs61290587
1   1015817 rs12746483  G   A   .   PASS    AF=0.707689 ES:SE:LP:AF:SS:ID   0.0225902:0.031107:0.30829:0.707689:18313:rs12746483
1   1017197 rs3766192   C   T   .   PASS    AF=0.532406 ES:SE:LP:AF:SS:ID   0.00745774:0.028819:0.0952882:0.532406:18313:rs3766192
1   1017341 rs1133647   G   T   .   PASS    AF=0.70898  ES:SE:LP:AF:SS:ID   0.0243993:0.030379:0.349223:0.70898:18313:rs1133647
1   1017587 rs3766191   C   T   .   PASS    AF=0.164144 ES:SE:LP:AF:SS:ID   0.0265971:0.038527:0.30548:0.164144:18313:rs3766191
1   1018144 rs9442395   T   C   .   PASS    AF=0.543021 ES:SE:LP:AF:SS:ID   0.00385241:0.028581:0.0476023:0.543021:18313:rs9442395
1   1018562 rs9442371   C   T   .   PASS    AF=0.542728 ES:SE:LP:AF:SS:ID   0.00454431:0.028561:0.0566588:0.542728:18313:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.544325 ES:SE:LP:AF:SS:ID   0.0059386:0.028465:0.0755796:0.544325:18313:rs9442372
1   1019175 rs2298215   C   G   .   PASS    AF=0.705959 ES:SE:LP:AF:SS:ID   0.0317219:0.030167:0.490131:0.705959:18313:rs2298215
1   1019180 rs9442396   T   C   .   PASS    AF=0.552759 ES:SE:LP:AF:SS:ID   0.00938793:0.028752:0.122976:0.552759:18313:rs9442396
1   1020406 rs9442397   T   C   .   PASS    AF=0.709566 ES:SE:LP:AF:SS:ID   0.0290149:0.029867:0.443431:0.709566:18313:rs9442397
1   1021346 rs10907177  A   G   .   PASS    AF=0.172145 ES:SE:LP:AF:SS:ID   0.0421127:0.040461:0.527884:0.172145:18313:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.712705 ES:SE:LP:AF:SS:ID   0.015004:0.029449:0.203253:0.712705:18313:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.166249 ES:SE:LP:AF:SS:ID   0.0395668:0.040263:0.487382:0.166249:18313:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.707362 ES:SE:LP:AF:SS:ID   0.0268328:0.030031:0.398942:0.707362:18313:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.547962 ES:SE:LP:AF:SS:ID   0.00212626:0.029009:0.0253253:0.547962:18313:rs6701114
1   1023145 rs3737727   G   A   .   PASS    AF=0.156735 ES:SE:LP:AF:SS:ID   0.0381827:0.040791:0.455929:0.156735:18313:rs3737727
1   1023310 rs11260589  T   C   .   PASS    AF=0.162713 ES:SE:LP:AF:SS:ID   0.0537995:0.042865:0.691013:0.162713:18313:rs11260589
1   1023788 rs12132100  C   T   .   PASS    AF=0.155518 ES:SE:LP:AF:SS:ID   0.0474674:0.042212:0.589032:0.155518:18313:rs12132100
1   1026707 rs4074137   C   A   .   PASS    AF=0.599622 ES:SE:LP:AF:SS:ID   0.00656853:0.030266:0.0786533:0.599622:18313:rs4074137
1   1026801 rs4562563   T   A   .   PASS    AF=0.613233 ES:SE:LP:AF:SS:ID   0.00156222:0.03043:0.0175813:0.613233:18313:rs4562563
1   1027070 rs11260590  G   A   .   PASS    AF=0.110718 ES:SE:LP:AF:SS:ID   0.084422:0.05311:1.00057:0.110718:18313:rs11260590
1   1027845 rs74048006  T   G   .   PASS    AF=0.165554 ES:SE:LP:AF:SS:ID   0.0579594:0.038813:0.895257:0.165554:18313:rs74048006
1   1027846 rs76994018  T   C   .   PASS    AF=0.165554 ES:SE:LP:AF:SS:ID   0.0579623:0.038813:0.895335:0.165554:18313:rs76994018
1   1028259 rs12077244  C   T   .   PASS    AF=0.110465 ES:SE:LP:AF:SS:ID   0.0802012:0.051539:0.965676:0.110465:18313:rs12077244
1   1029805 rs6689308   A   G   .   PASS    AF=0.167567 ES:SE:LP:AF:SS:ID   0.0541662:0.038019:0.832789:0.167567:18313:rs6689308
1   1030374 rs12731175  G   A   .   PASS    AF=0.0558117    ES:SE:LP:AF:SS:ID   0.028499:0.067021:0.165843:0.0558117:18313:rs12731175
1   1030565 rs6687776   C   T   .   PASS    AF=0.167682 ES:SE:LP:AF:SS:ID   0.0534573:0.037867:0.821201:0.167682:18313:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.167545 ES:SE:LP:AF:SS:ID   0.0535806:0.037946:0.821564:0.167545:18313:rs6678318