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-1009/ieu-a-1009.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-1009/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 11:09:28 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1009/ieu-a-1009.vcf.gz ...
Read summary statistics for 2268424 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, 1107672 SNPs remain.
After merging with regression SNP LD, 1107672 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0352 (0.0022)
Lambda GC: 1.2365
Mean Chi^2: 1.2286
Intercept: 1.0188 (0.0076)
Ratio: 0.0821 (0.0334)
Analysis finished at Wed Feb  5 11:09:56 2020
Total time elapsed: 27.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9179,
    "inflation_factor": 1.1396,
    "mean_EFFECT": -0,
    "n": 298420,
    "n_snps": 2268424,
    "n_clumped_hits": 1,
    "n_p_sig": 8,
    "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": 15076,
    "n_est": 241311.6928,
    "ratio_se_n": 0.8992,
    "mean_diff": 3.9441e-06,
    "ratio_diff": 18.0092,
    "sd_y_est1": 1.3068,
    "sd_y_est2": 1.1751,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0001,
    "r2_sum3": 0.0001,
    "r2_sum4": 0.0001,
    "ldsc_nsnp_merge_refpanel_ld": 1107672,
    "ldsc_nsnp_merge_regression_ld": 1107672,
    "ldsc_observed_scale_h2_beta": 0.0352,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0188,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.2365,
    "ldsc_mean_chisq": 1.2286,
    "ldsc_ratio": 0.0822
}

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 1.000000 3 34 0 2268424 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 8.625020e+00 5.659207e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.883314e+07 5.560844e+07 1.1523e+04 3.279621e+07 7.041106e+07 1.144197e+08 2.492107e+08 ▇▇▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA -2.790000e-05 4.999700e-03 -4.7000e-02 -3.000000e-03 0.000000e+00 3.000000e-03 4.700000e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 4.356700e-03 1.664200e-03 3.0000e-03 3.000000e-03 4.000000e-03 5.000000e-03 1.300000e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.783831e-01 2.944220e-01 0.0000e+00 2.183001e-01 4.715003e-01 7.327992e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.740005e-01 3.026047e-01 0.0000e+00 1.985428e-01 4.532547e-01 7.388827e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.000000 NA NA NA NA NA 3.719535e-01 2.605213e-01 1.1190e-02 1.455000e-01 3.134000e-01 5.653000e-01 9.869400e-01 ▇▆▃▃▂
numeric AF_reference 15076 0.993354 NA NA NA NA NA 3.726519e-01 2.481597e-01 1.9970e-04 1.643370e-01 3.164940e-01 5.537140e-01 9.956070e-01 ▇▇▅▃▂
numeric N 0 1.000000 NA NA NA NA NA 2.984200e+05 0.000000e+00 2.9842e+05 2.984200e+05 2.984200e+05 2.984200e+05 2.984200e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A -0.001 0.005 0.7953000 0.8414806 0.84510 0.7182510 298420
1 754192 rs3131968 A G -0.006 0.005 0.2709000 0.2301393 0.87870 0.6785140 298420
1 777122 rs2980319 A T 0.004 0.006 0.4657995 0.5049851 0.88060 0.7472040 298420
1 779322 rs4040617 A G -0.005 0.006 0.4334999 0.4046568 0.11750 0.2264380 298420
1 780785 rs2977612 T A 0.003 0.006 0.6085006 0.6170751 0.87870 0.6693290 298420
1 785989 rs2980300 T C 0.004 0.006 0.4369000 0.5049851 0.86750 0.6269970 298420
1 798801 rs12132517 G A 0.018 0.008 0.0208598 0.0244489 0.07649 0.0740815 298420
1 798959 rs11240777 G A 0.014 0.005 0.0046990 0.0051103 0.20150 0.4099440 298420
1 846864 rs950122 G C -0.006 0.006 0.2432999 0.3173105 0.18470 0.2228430 298420
1 882033 rs2272756 G A -0.006 0.005 0.2495003 0.2301393 0.24250 0.1367810 298420
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51162059 rs10451 G A -0.001 0.004 0.7337008 0.8025873 0.27800 0.3865810 298420
22 51163138 rs715586 C T -0.006 0.005 0.2270999 0.2301393 0.12500 0.0902556 298420
22 51165664 rs8137951 G A -0.002 0.004 0.5707002 0.6170751 0.27610 0.4063500 298420
22 51171497 rs2301584 G A -0.012 0.005 0.0091369 0.0163951 0.16040 0.2533950 298420
22 51171693 rs756638 G A 0.002 0.004 0.5764000 0.6170751 0.27050 0.3049120 298420
22 51173542 rs4824147 T C -0.002 0.009 0.8278000 0.8241409 0.95896 0.9812300 298420
22 51175626 rs3810648 A G 0.007 0.007 0.3442001 0.3173105 0.05037 0.1084270 298420
22 51178090 rs2285395 G A 0.011 0.008 0.1590000 0.1691314 0.04851 0.0666933 298420
22 51196164 rs8136603 A T 0.008 0.008 0.3044002 0.3173105 0.05410 0.1427720 298420
22 51212875 rs2238837 A C -0.004 0.004 0.3078003 0.3173105 0.20150 0.3724040 298420

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.8451   ES:SE:LP:AF:SS:ID   -0.001:0.005:0.099469:0.8451:298420:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   -0.006:0.005:0.567191:0.8787:298420:rs3131968
1   777122  rs2980319   A   T   .   PASS    AF=0.8806   ES:SE:LP:AF:SS:ID   0.004:0.006:0.331801:0.8806:298420:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.1175   ES:SE:LP:AF:SS:ID   -0.005:0.006:0.363011:0.1175:298420:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   0.003:0.006:0.215739:0.8787:298420:rs2977612
1   785989  rs2980300   T   C   .   PASS    AF=0.8675   ES:SE:LP:AF:SS:ID   0.004:0.006:0.359618:0.8675:298420:rs2980300
1   798801  rs12132517  G   A   .   PASS    AF=0.07649  ES:SE:LP:AF:SS:ID   0.018:0.008:1.68069:0.07649:298420:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.2015   ES:SE:LP:AF:SS:ID   0.014:0.005:2.32799:0.2015:298420:rs11240777
1   846864  rs950122    G   C   .   PASS    AF=0.1847   ES:SE:LP:AF:SS:ID   -0.006:0.006:0.613858:0.1847:298420:rs950122
1   882033  rs2272756   G   A   .   PASS    AF=0.2425   ES:SE:LP:AF:SS:ID   -0.006:0.005:0.602929:0.2425:298420:rs2272756
1   962210  rs3128126   A   G   .   PASS    AF=0.375    ES:SE:LP:AF:SS:ID   -0.003:0.004:0.313185:0.375:298420:rs3128126
1   990380  rs3121561   C   T   .   PASS    AF=0.2817   ES:SE:LP:AF:SS:ID   -0.004:0.004:0.540155:0.2817:298420:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.153    ES:SE:LP:AF:SS:ID   0.004:0.005:0.34785:0.153:298420:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7313   ES:SE:LP:AF:SS:ID   0.002:0.004:0.286593:0.7313:298420:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1511   ES:SE:LP:AF:SS:ID   0.001:0.005:0.0433994:0.1511:298420:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.5466   ES:SE:LP:AF:SS:ID   0.004:0.003:0.617083:0.5466:298420:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5448   ES:SE:LP:AF:SS:ID   0.003:0.004:0.430392:0.5448:298420:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.1399   ES:SE:LP:AF:SS:ID   0:0.005:0.0009565:0.1399:298420:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.5634   ES:SE:LP:AF:SS:ID   0.003:0.003:0.521578:0.5634:298420:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.5634   ES:SE:LP:AF:SS:ID   0.004:0.003:0.54485:0.5634:298420:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1549   ES:SE:LP:AF:SS:ID   0:0.005:0.0197239:0.1549:298420:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.722    ES:SE:LP:AF:SS:ID   0.002:0.004:0.290645:0.722:298420:rs3737728
1   1021695 rs9442398   A   G   .   PASS    AF=0.7146   ES:SE:LP:AF:SS:ID   0.003:0.004:0.44855:0.7146:298420:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5578   ES:SE:LP:AF:SS:ID   0.004:0.003:0.522589:0.5578:298420:rs6701114
1   1025301 rs9442400   T   C   .   PASS    AF=0.91791  ES:SE:LP:AF:SS:ID   0.002:0.007:0.120904:0.91791:298420:rs9442400
1   1026707 rs4074137   C   A   .   PASS    AF=0.5914   ES:SE:LP:AF:SS:ID   0.007:0.004:1.33847:0.5914:298420:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1474   ES:SE:LP:AF:SS:ID   -0.004:0.005:0.419759:0.1474:298420:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.1474   ES:SE:LP:AF:SS:ID   -0.005:0.005:0.502656:0.1474:298420:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.7164   ES:SE:LP:AF:SS:ID   -0.001:0.004:0.10133:0.7164:298420:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.1101   ES:SE:LP:AF:SS:ID   -0.01:0.005:1.17076:0.1101:298420:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.1306   ES:SE:LP:AF:SS:ID   -0.004:0.005:0.361311:0.1306:298420:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.1306   ES:SE:LP:AF:SS:ID   -0.004:0.005:0.388702:0.1306:298420:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.1063   ES:SE:LP:AF:SS:ID   -0.009:0.005:1.03348:0.1063:298420:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1306   ES:SE:LP:AF:SS:ID   -0.005:0.005:0.530473:0.1306:298420:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.1082   ES:SE:LP:AF:SS:ID   -0.01:0.005:1.31283:0.1082:298420:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.2761   ES:SE:LP:AF:SS:ID   0.002:0.004:0.260507:0.2761:298420:rs7548798
1   1060608 rs17160824  G   A   .   PASS    AF=0.1082   ES:SE:LP:AF:SS:ID   -0.011:0.005:1.48241:0.1082:298420:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.1063   ES:SE:LP:AF:SS:ID   -0.01:0.005:1.33059:0.1063:298420:rs17160826
1   1061166 rs11807848  T   C   .   PASS    AF=0.4067   ES:SE:LP:AF:SS:ID   -0.003:0.004:0.471598:0.4067:298420:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.556    ES:SE:LP:AF:SS:ID   0.003:0.004:0.453951:0.556:298420:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.7369   ES:SE:LP:AF:SS:ID   0.001:0.004:0.072373:0.7369:298420:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.1287   ES:SE:LP:AF:SS:ID   -0.008:0.005:1.04861:0.1287:298420:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.07649  ES:SE:LP:AF:SS:ID   -0.007:0.008:0.427012:0.07649:298420:rs12145826
1   1066403 rs10907182  T   C   .   PASS    AF=0.6101   ES:SE:LP:AF:SS:ID   0.005:0.004:0.77963:0.6101:298420:rs10907182
1   1071118 rs10907183  G   C   .   PASS    AF=0.6194   ES:SE:LP:AF:SS:ID   0.004:0.004:0.619789:0.6194:298420:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.92724  ES:SE:LP:AF:SS:ID   0.003:0.006:0.217241:0.92724:298420:rs4970357
1   1079198 rs11260603  T   C   .   PASS    AF=0.2593   ES:SE:LP:AF:SS:ID   0.001:0.005:0.0509029:0.2593:298420:rs11260603
1   1087683 rs9442380   T   C   .   PASS    AF=0.9403   ES:SE:LP:AF:SS:ID   0:0.007:0.0123337:0.9403:298420:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.97575  ES:SE:LP:AF:SS:ID   -0.013:0.011:0.679854:0.97575:298420:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.6381   ES:SE:LP:AF:SS:ID   0.001:0.004:0.138466:0.6381:298420:rs4970362