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-966/ieu-a-966.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-966/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 16:05:45 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-966/ieu-a-966.vcf.gz ...
Read summary statistics for 8827545 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, 1237082 SNPs remain.
After merging with regression SNP LD, 1237082 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0715 (0.0274)
Lambda GC: 1.1136
Mean Chi^2: 1.1333
Intercept: 1.0945 (0.008)
Ratio: 0.7087 (0.0602)
Analysis finished at Tue Feb  4 16:07:13 2020
Total time elapsed: 1.0m:27.96s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9506,
    "inflation_factor": 1.0433,
    "mean_EFFECT": 0.002,
    "n": 27209,
    "n_snps": 8827545,
    "n_clumped_hits": 5,
    "n_p_sig": 668,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 53,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 174026,
    "n_est": 26786.2123,
    "ratio_se_n": 0.9922,
    "mean_diff": -0.006,
    "ratio_diff": 1.2156,
    "sd_y_est1": 2.1107,
    "sd_y_est2": 2.0942,
    "r2_sum1": 0.0854,
    "r2_sum2": 0.0192,
    "r2_sum3": 0.0195,
    "r2_sum4": 0.015,
    "ldsc_nsnp_merge_refpanel_ld": 1237082,
    "ldsc_nsnp_merge_regression_ld": 1237082,
    "ldsc_observed_scale_h2_beta": 0.0715,
    "ldsc_observed_scale_h2_se": 0.0274,
    "ldsc_intercept_beta": 1.0945,
    "ldsc_intercept_se": 0.008,
    "ldsc_lambda_gc": 1.1136,
    "ldsc_mean_chisq": 1.1333,
    "ldsc_ratio": 0.7089
}

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 1.000000 3 58 0 8827545 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 8.542993e+00 5.696804e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.950493e+07 5.583567e+07 1.31330e+04 3.368842e+07 7.068938e+07 1.147806e+08 2.492183e+08 ▇▇▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 2.021400e-03 1.005592e-01 -2.51766e+00 -2.433350e-02 3.829000e-04 2.534610e-02 3.764280e+00 ▁▆▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 5.715970e-02 7.171410e-02 1.54490e-02 2.087300e-02 3.122500e-02 6.786800e-02 2.051760e+01 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.928142e-01 2.909463e-01 0.00000e+00 2.383828e-01 4.908649e-01 7.451694e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.756948e-01 2.945654e-01 0.00000e+00 2.163852e-01 4.665978e-01 7.304438e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.000000 NA NA NA NA NA 2.196449e-01 2.591293e-01 6.26000e-05 1.952250e-02 1.045440e-01 3.380880e-01 9.998750e-01 ▇▂▁▁▁
numeric AF_reference 174026 0.980286 NA NA NA NA NA 2.236081e-01 2.515816e-01 0.00000e+00 2.336260e-02 1.222040e-01 3.452480e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 2.720900e+04 0.000000e+00 2.72090e+04 2.720900e+04 2.720900e+04 2.720900e+04 2.720900e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 996248 rs28479311 C T -0.0421927 0.027652 0.1552891 0.1270482 0.153315 0.106629 27209
1 998501 rs3813193 G C -0.0397028 0.025365 0.1428749 0.1175221 0.168632 0.206669 27209
1 1002387 rs74048003 A G -0.0402524 0.024547 0.1246979 0.1010448 0.231683 0.244609 27209
1 1002539 rs60442576 G A -0.0429827 0.024427 0.1003571 0.0784690 0.236591 0.343051 27209
1 1004957 rs4073176 G A 0.0515323 0.019370 0.0133079 0.0078044 0.575145 0.550319 27209
1 1004980 rs4073177 G A 0.0509523 0.019375 0.0143489 0.0085436 0.574737 0.550319 27209
1 1005806 rs3934834 C T -0.0356137 0.022663 0.1385109 0.1160789 0.162134 0.223442 27209
1 1006223 rs9442394 G A 0.0484038 0.019249 0.0188951 0.0119163 0.571111 0.547125 27209
1 1006990 rs4326571 G A 0.0369275 0.021452 0.1046779 0.0851780 0.717331 0.816294 27209
1 1007203 rs4633229 A G 0.0436970 0.024533 0.0965562 0.0748876 0.771093 0.841254 27209
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51178607 rs6010067 G C -0.0127996 0.068332 0.8633570 0.8514138 0.0239328 0.0814696 27209
22 51178756 rs141844965 A T 0.1718570 0.122002 0.1341090 0.1589414 0.0083250 0.0059904 27209
22 51179000 rs2283675 C A 0.0002940 0.023614 0.9902770 0.9900679 0.3125400 0.5127800 27209
22 51179770 rs2283676 G A 0.0071752 0.026653 0.7917389 0.7877696 0.2455510 0.3945690 27209
22 51180501 rs5770999 T C 0.0130407 0.024177 0.6034176 0.5896215 0.6887920 0.6369810 27209
22 51180878 rs6010069 A G 0.0325679 0.034858 0.3508431 0.3501481 0.1389130 0.1589460 27209
22 51180934 rs9616824 C T -0.0266346 0.033118 0.4492499 0.4212622 0.1269510 0.1689300 27209
22 51180959 rs6010070 A G 0.0090836 0.035104 0.8009371 0.7958180 0.1346950 0.2056710 27209
22 51182399 rs56238942 A G -0.0095706 0.039872 0.8194550 0.8103036 0.0768871 0.0992412 27209
23 51866774 rs150899468 C A 0.1269550 0.158170 0.5662810 0.4221776 0.9975970 0.9965560 27209

bcf preview

1   996248  rs28479311  C   T   .   PASS    AF=0.153315 ES:SE:LP:AF:SS:ID   -0.0421927:0.027652:0.808859:0.153315:27209:rs28479311
1   998501  rs3813193   G   C   .   PASS    AF=0.168632 ES:SE:LP:AF:SS:ID   -0.0397028:0.025365:0.845044:0.168632:27209:rs3813193
1   1002387 rs74048003  A   G   .   PASS    AF=0.231683 ES:SE:LP:AF:SS:ID   -0.0402524:0.024547:0.904141:0.231683:27209:rs74048003
1   1002539 rs60442576  G   A   .   PASS    AF=0.236591 ES:SE:LP:AF:SS:ID   -0.0429827:0.024427:0.998452:0.236591:27209:rs60442576
1   1004957 rs4073176   G   A   .   PASS    AF=0.575145 ES:SE:LP:AF:SS:ID   0.0515323:0.01937:1.87589:0.575145:27209:rs4073176
1   1004980 rs4073177   G   A   .   PASS    AF=0.574737 ES:SE:LP:AF:SS:ID   0.0509523:0.019375:1.84318:0.574737:27209:rs4073177
1   1005806 rs3934834   C   T   .   PASS    AF=0.162134 ES:SE:LP:AF:SS:ID   -0.0356137:0.022663:0.858516:0.162134:27209:rs3934834
1   1006223 rs9442394   G   A   .   PASS    AF=0.571111 ES:SE:LP:AF:SS:ID   0.0484038:0.019249:1.72365:0.571111:27209:rs9442394
1   1006990 rs4326571   G   A   .   PASS    AF=0.717331 ES:SE:LP:AF:SS:ID   0.0369275:0.021452:0.980145:0.717331:27209:rs4326571
1   1007203 rs4633229   A   G   .   PASS    AF=0.771093 ES:SE:LP:AF:SS:ID   0.043697:0.024533:1.01522:0.771093:27209:rs4633229
1   1007222 rs71628928  G   T   .   PASS    AF=0.171881 ES:SE:LP:AF:SS:ID   -0.0241114:0.023978:0.470866:0.171881:27209:rs71628928
1   1007432 rs4333796   G   A   .   PASS    AF=0.552182 ES:SE:LP:AF:SS:ID   0.0553732:0.018722:2.21531:0.552182:27209:rs4333796
1   1009234 rs9442366   T   C   .   PASS    AF=0.552086 ES:SE:LP:AF:SS:ID   0.0510502:0.01864:1.96944:0.552086:27209:rs9442366
1   1009478 rs9442367   G   C   .   PASS    AF=0.717736 ES:SE:LP:AF:SS:ID   0.0365841:0.021441:0.96803:0.717736:27209:rs9442367
1   1009823 rs12752391  G   A   .   PASS    AF=0.166319 ES:SE:LP:AF:SS:ID   -0.0309872:0.023163:0.687499:0.166319:27209:rs12752391
1   1010717 rs9442368   C   T   .   PASS    AF=0.557687 ES:SE:LP:AF:SS:ID   0.0501256:0.018721:1.9017:0.557687:27209:rs9442368
1   1012706 rs78632925  T   C   .   PASS    AF=0.444176 ES:SE:LP:AF:SS:ID   -0.0358676:0.022517:0.875346:0.444176:27209:rs78632925
1   1014836 rs12401605  A   G   .   PASS    AF=0.525769 ES:SE:LP:AF:SS:ID   0.0419664:0.018631:1.46657:0.525769:27209:rs12401605
1   1015126 rs36027499  A   G   .   PASS    AF=0.545    ES:SE:LP:AF:SS:ID   0.0477239:0.018219:1.84485:0.545:27209:rs36027499
1   1015257 rs9442369   A   G   .   PASS    AF=0.54227  ES:SE:LP:AF:SS:ID   0.0478466:0.018322:1.83505:0.54227:27209:rs9442369
1   1015551 rs9442370   C   T   .   PASS    AF=0.534143 ES:SE:LP:AF:SS:ID   0.0428198:0.018691:1.50358:0.534143:27209:rs9442370
1   1015716 rs61290587  G   A   .   PASS    AF=0.174792 ES:SE:LP:AF:SS:ID   -0.0193072:0.024365:0.348384:0.174792:27209:rs61290587
1   1015817 rs12746483  G   A   .   PASS    AF=0.707924 ES:SE:LP:AF:SS:ID   0.0349134:0.019975:1.00775:0.707924:27209:rs12746483
1   1017197 rs3766192   C   T   .   PASS    AF=0.534764 ES:SE:LP:AF:SS:ID   0.0440846:0.018003:1.66782:0.534764:27209:rs3766192
1   1017341 rs1133647   G   T   .   PASS    AF=0.70929  ES:SE:LP:AF:SS:ID   0.035161:0.019513:1.05452:0.70929:27209:rs1133647
1   1017587 rs3766191   C   T   .   PASS    AF=0.16163  ES:SE:LP:AF:SS:ID   -0.0256214:0.024179:0.503545:0.16163:27209:rs3766191
1   1018144 rs9442395   T   C   .   PASS    AF=0.54575  ES:SE:LP:AF:SS:ID   0.0442278:0.017749:1.71489:0.54575:27209:rs9442395
1   1018562 rs9442371   C   T   .   PASS    AF=0.5454   ES:SE:LP:AF:SS:ID   0.0440438:0.01775:1.70391:0.5454:27209:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.547002 ES:SE:LP:AF:SS:ID   0.0447746:0.017688:1.75681:0.547002:27209:rs9442372
1   1019175 rs2298215   C   G   .   PASS    AF=0.7062   ES:SE:LP:AF:SS:ID   0.0448342:0.019338:1.52522:0.7062:27209:rs2298215
1   1019180 rs9442396   T   C   .   PASS    AF=0.555473 ES:SE:LP:AF:SS:ID   0.0477113:0.017965:1.88686:0.555473:27209:rs9442396
1   1020406 rs9442397   T   C   .   PASS    AF=0.710077 ES:SE:LP:AF:SS:ID   0.046794:0.019192:1.64595:0.710077:27209:rs9442397
1   1021346 rs10907177  A   G   .   PASS    AF=0.169669 ES:SE:LP:AF:SS:ID   -0.0101453:0.025261:0.155913:0.169669:27209:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.713377 ES:SE:LP:AF:SS:ID   0.033745:0.018863:1.04656:0.713377:27209:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.163747 ES:SE:LP:AF:SS:ID   -0.0150862:0.025136:0.248371:0.163747:27209:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.707997 ES:SE:LP:AF:SS:ID   0.0464702:0.019193:1.62873:0.707997:27209:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.550963 ES:SE:LP:AF:SS:ID   0.0464294:0.018002:1.80405:0.550963:27209:rs6701114
1   1023145 rs3737727   G   A   .   PASS    AF=0.154294 ES:SE:LP:AF:SS:ID   -0.0188689:0.025415:0.320761:0.154294:27209:rs3737727
1   1023310 rs11260589  T   C   .   PASS    AF=0.160316 ES:SE:LP:AF:SS:ID   -0.011244:0.026477:0.165766:0.160316:27209:rs11260589
1   1023788 rs12132100  C   T   .   PASS    AF=0.15309  ES:SE:LP:AF:SS:ID   -0.0130619:0.026182:0.19955:0.15309:27209:rs12132100
1   1026707 rs4074137   C   A   .   PASS    AF=0.600511 ES:SE:LP:AF:SS:ID   0.0189504:0.019322:0.461768:0.600511:27209:rs4074137
1   1026801 rs4562563   T   A   .   PASS    AF=0.614106 ES:SE:LP:AF:SS:ID   0.0122578:0.019428:0.266706:0.614106:27209:rs4562563
1   1027070 rs11260590  G   A   .   PASS    AF=0.110149 ES:SE:LP:AF:SS:ID   0.0487111:0.03326:0.865272:0.110149:27209:rs11260590
1   1027845 rs74048006  T   G   .   PASS    AF=0.163537 ES:SE:LP:AF:SS:ID   0.00727348:0.024191:0.114929:0.163537:27209:rs74048006
1   1027846 rs76994018  T   C   .   PASS    AF=0.163537 ES:SE:LP:AF:SS:ID   0.00727249:0.024191:0.114917:0.163537:27209:rs76994018
1   1028259 rs12077244  C   T   .   PASS    AF=0.109835 ES:SE:LP:AF:SS:ID   0.0426887:0.032354:0.740053:0.109835:27209:rs12077244
1   1029805 rs6689308   A   G   .   PASS    AF=0.1656   ES:SE:LP:AF:SS:ID   0.00625738:0.023753:0.0992528:0.1656:27209:rs6689308
1   1030374 rs12731175  G   A   .   PASS    AF=0.054412 ES:SE:LP:AF:SS:ID   -0.0715948:0.040494:0.938061:0.054412:27209:rs12731175
1   1030565 rs6687776   C   T   .   PASS    AF=0.16565  ES:SE:LP:AF:SS:ID   0.00481837:0.023636:0.0749939:0.16565:27209:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.165562 ES:SE:LP:AF:SS:ID   0.00569177:0.023696:0.0896633:0.165562:27209:rs6678318