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-1004/ieu-a-1004.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-1004/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 11:33:51 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1004/ieu-a-1004.vcf.gz ...
Read summary statistics for 2415893 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, 1146515 SNPs remain.
After merging with regression SNP LD, 1146515 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1893 (0.0137)
Lambda GC: 0.977
Mean Chi^2: 1.2923
Intercept: 1.0368 (0.0096)
Ratio: 0.1259 (0.0329)
Analysis finished at Wed Feb  5 11:34:20 2020
Total time elapsed: 28.93s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9152,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": 69360,
    "n_snps": 2415893,
    "n_clumped_hits": 42,
    "n_p_sig": 1208,
    "n_mono": 0,
    "n_ns": 0,
    "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": 19654,
    "n_est": 44460.8974,
    "ratio_se_n": 0.8006,
    "mean_diff": -0,
    "ratio_diff": 44.6001,
    "sd_y_est1": 4.6286,
    "sd_y_est2": 3.7058,
    "r2_sum1": 0.637,
    "r2_sum2": 0.0297,
    "r2_sum3": 0.0464,
    "r2_sum4": 0.0469,
    "ldsc_nsnp_merge_refpanel_ld": 1146515,
    "ldsc_nsnp_merge_regression_ld": 1146515,
    "ldsc_observed_scale_h2_beta": 0.1893,
    "ldsc_observed_scale_h2_se": 0.0137,
    "ldsc_intercept_beta": 1.0368,
    "ldsc_intercept_se": 0.0096,
    "ldsc_lambda_gc": 0.977,
    "ldsc_mean_chisq": 1.2923,
    "ldsc_ratio": 0.1259
}
 

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 TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 TRUE
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 42 0 2415893 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 8.584573e+00 5.655200e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 23.00 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.884366e+07 5.565313e+07 1.1543e+04 3.268972e+07 7.025702e+07 1.143281e+08 249210707.00 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.020000e-05 3.794100e-02 -5.2000e-01 -2.000000e-02 0.000000e+00 2.000000e-02 0.88 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.174310e-02 1.682670e-02 2.0000e-02 2.000000e-02 3.000000e-02 4.000000e-02 0.21 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.856034e-01 2.933971e-01 0.0000e+00 2.300001e-01 4.799997e-01 7.400005e-01 1.00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.815687e-01 3.094341e-01 0.0000e+00 1.824224e-01 5.049851e-01 7.388827e-01 1.00 ▇▆▃▇▆
numeric AF 0 1.0000000 NA NA NA NA NA 3.616448e-01 2.720218e-01 1.0000e-02 1.200000e-01 3.000000e-01 5.600000e-01 0.99 ▇▅▃▃▂
numeric AF_reference 19654 0.9918647 NA NA NA NA NA 3.641544e-01 2.541254e-01 1.9970e-04 1.503590e-01 3.033150e-01 5.479230e-01 1.00 ▇▆▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 6.936000e+04 0.000000e+00 6.9360e+04 6.936000e+04 6.936000e+04 6.936000e+04 69360.00 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A 0.01 0.05 0.8300000 0.8414806 0.83 0.718251 69360
1 777122 rs2980319 A T 0.02 0.06 0.6700003 0.7388827 0.87 0.747204 69360
1 779322 rs4040617 A G -0.03 0.06 0.6300007 0.6170751 0.13 0.226438 69360
1 780785 rs2977612 T A 0.03 0.06 0.6600001 0.6170751 0.86 0.669329 69360
1 785050 rs2905062 G A 0.04 0.06 0.4899999 0.5049851 0.86 0.626997 69360
1 785989 rs2980300 T C 0.03 0.06 0.5900000 0.6170751 0.85 0.626997 69360
1 990380 rs3121561 C T -0.02 0.03 0.5400003 0.5049851 0.29 0.343450 69360
1 998501 rs3813193 G C -0.04 0.04 0.2599998 0.3173105 0.17 0.206669 69360
1 1003629 rs4075116 C T -0.01 0.03 0.6600001 0.7388827 0.73 0.720647 69360
1 1005806 rs3934834 C T -0.03 0.03 0.4199997 0.3173105 0.16 0.223442 69360
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51175626 rs3810648 A G -0.04 0.05 0.3800004 0.4237108 0.07 0.1084270 69360
22 51178090 rs2285395 G A -0.04 0.05 0.3800004 0.4237108 0.07 0.0666933 69360
22 51196164 rs8136603 A T -0.06 0.06 0.2700001 0.3173105 0.07 0.1427720 69360
22 51222100 rs114553188 G T -0.01 0.08 0.9000000 0.9005236 0.07 0.0880591 69360
22 51223637 rs375798137 G A -0.02 0.08 0.8300000 0.8025873 0.07 0.0788738 69360
23 35921591 rs2204667 C G -0.06 0.04 0.1400000 0.1336144 0.17 NA 69360
23 51666786 rs14115 A G 0.10 0.05 0.0500000 0.0455003 0.02 NA 69360
23 70163799 rs1626496 A C 0.03 0.05 0.5300002 0.5485062 0.07 NA 69360
23 91415872 rs6562597 G A 0.08 0.11 0.4500005 0.4670589 0.01 0.0021192 69360
23 118495837 rs12882977 G A 0.05 0.02 0.0460002 0.0124193 0.52 0.2307280 69360

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.83 ES:SE:LP:AF:SS:ID   0.01:0.05:0.0809219:0.83:69360:rs3094315
1   777122  rs2980319   A   T   .   PASS    AF=0.87 ES:SE:LP:AF:SS:ID   0.02:0.06:0.173925:0.87:69360:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.13 ES:SE:LP:AF:SS:ID   -0.03:0.06:0.200659:0.13:69360:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.86 ES:SE:LP:AF:SS:ID   0.03:0.06:0.180456:0.86:69360:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.86 ES:SE:LP:AF:SS:ID   0.04:0.06:0.309804:0.86:69360:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.85 ES:SE:LP:AF:SS:ID   0.03:0.06:0.229148:0.85:69360:rs2980300
1   990380  rs3121561   C   T   .   PASS    AF=0.29 ES:SE:LP:AF:SS:ID   -0.02:0.03:0.267606:0.29:69360:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.17 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.585027:0.17:69360:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.73 ES:SE:LP:AF:SS:ID   -0.01:0.03:0.180456:0.73:69360:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.376751:0.16:69360:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.55 ES:SE:LP:AF:SS:ID   0:0.02:0.05061:0.55:69360:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.55 ES:SE:LP:AF:SS:ID   0:0.02:0.05061:0.55:69360:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.522879:0.15:69360:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.56 ES:SE:LP:AF:SS:ID   0.01:0.02:0.091515:0.56:69360:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.57 ES:SE:LP:AF:SS:ID   0.01:0.02:0.113509:0.57:69360:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.431798:0.15:69360:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   0:0.03:0.0268721:0.72:69360:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.318759:0.15:69360:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   0:0.03:0.0705811:0.72:69360:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.56 ES:SE:LP:AF:SS:ID   0.01:0.02:0.251812:0.56:69360:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.6  ES:SE:LP:AF:SS:ID   0.04:0.03:0.823909:0.6:69360:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.02:0.03:0.21467:0.16:69360:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.04:0.05:0.337242:0.16:69360:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.73 ES:SE:LP:AF:SS:ID   0.03:0.04:0.431798:0.73:69360:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.02:0.04:0.283997:0.11:69360:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.443698:0.15:69360:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.14 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.49485:0.14:69360:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.552842:0.11:69360:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.468521:0.15:69360:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.387216:0.11:69360:rs4970409
1   1060608 rs17160824  G   A   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.443698:0.12:69360:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.468521:0.11:69360:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.420216:0.11:69360:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.42 ES:SE:LP:AF:SS:ID   -0.07:0.04:1.3279:0.42:69360:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.54 ES:SE:LP:AF:SS:ID   0.07:0.04:1.38722:0.54:69360:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   0.08:0.05:1.13668:0.72:69360:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.02:0.03:0.229148:0.15:69360:rs2298217
1   1077064 rs4970357   C   A   .   PASS    AF=0.91 ES:SE:LP:AF:SS:ID   0.01:0.04:0.0809219:0.91:69360:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.92 ES:SE:LP:AF:SS:ID   0.02:0.04:0.161151:0.92:69360:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.96 ES:SE:LP:AF:SS:ID   0.01:0.07:0.0861861:0.96:69360:rs4970358
1   1097335 rs9442385   T   G   .   PASS    AF=0.93 ES:SE:LP:AF:SS:ID   0.01:0.04:0.0555173:0.93:69360:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.93 ES:SE:LP:AF:SS:ID   0:0.04:0.0315171:0.93:69360:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.95 ES:SE:LP:AF:SS:ID   0.03:0.05:0.30103:0.95:69360:rs1891905
1   1120431 rs1320571   G   A   .   PASS    AF=0.04 ES:SE:LP:AF:SS:ID   -0.01:0.07:0.0655015:0.04:69360:rs1320571
1   1121014 rs3813204   G   A   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   -0.04:0.06:0.244125:0.12:69360:rs3813204
1   1121794 rs11260549  G   A   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   0:0.03:0.0555173:0.12:69360:rs11260549
1   1124663 rs6684820   G   A   .   PASS    AF=0.26 ES:SE:LP:AF:SS:ID   -0.01:0.02:0.200659:0.26:69360:rs6684820
1   1125553 rs10907174  A   T   .   PASS    AF=0.21 ES:SE:LP:AF:SS:ID   0:0.03:0.0362122:0.21:69360:rs10907174
1   1129672 rs11260554  G   T   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   0:0.03:0.0268721:0.12:69360:rs11260554
1   1130727 rs10907175  A   C   .   PASS    AF=0.09 ES:SE:LP:AF:SS:ID   0.02:0.04:0.167491:0.09:69360:rs10907175