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/public/UKB-b-10098/UKB-b-10098_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10098/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10098/UKB-b-10098_data.vcf.gz ...
Read summary statistics for 3723287 SNPs.
Dropped 642 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 899785 SNPs remain.
After merging with regression SNP LD, 899785 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0015 (0.0012)
Lambda GC: 1.0256
Mean Chi^2: 1.023
Intercept: 1.0077 (0.0088)
Ratio: 0.3332 (0.3843)
Analysis finished at Thu Oct 17 14:41:06 2019
Total time elapsed: 48.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8631,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -1.6249e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 30100,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 899785,
    "ldsc_nsnp_merge_regression_ld": 899785,
    "ldsc_observed_scale_h2_beta": 0.0015,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0077,
    "ldsc_intercept_se": 0.0088,
    "ldsc_lambda_gc": 1.0256,
    "ldsc_mean_chisq": 1.023,
    "ldsc_ratio": 0.3348
}
 

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 3722648 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 3723287 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.663039e+00 5.770507e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.855705e+07 5.675749e+07 828.0000000 3.159339e+07 6.890383e+07 1.147212e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.600000e-06 1.807000e-04 -0.0010404 -1.214000e-04 -2.500000e-06 1.182000e-04 1.323500e-03 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.770000e-04 2.090000e-05 0.0001491 1.588000e-04 1.703000e-04 1.915000e-04 5.454000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.953738e-01 2.898730e-01 0.0000008 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.953749e-01 2.898480e-01 0.0000008 2.432449e-01 4.940718e-01 7.466852e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.058670e-01 2.036216e-01 0.1358170 2.276965e-01 3.629900e-01 5.590430e-01 8.641830e-01 ▇▅▃▃▂
numeric AF_reference 30100 0.9919157 NA NA NA NA NA NA NA 3.934074e-01 2.105739e-01 0.0000000 2.206470e-01 3.578270e-01 5.465260e-01 1.000000e+00 ▅▇▆▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0003404 0.0002744 0.2099999 0.2148108 0.623763 0.782149 NA
1 54676 rs2462492 C T 0.0003039 0.0002719 0.2599998 0.2636918 0.400401 NA NA
1 91536 rs6702460 G T -0.0006638 0.0002677 0.0129999 0.0131509 0.456851 0.420727 NA
1 534192 rs6680723 C T -0.0000129 0.0003058 0.9699999 0.9664263 0.240960 NA NA
1 706368 rs55727773 A G -0.0000840 0.0001898 0.6600001 0.6580172 0.515650 0.275160 NA
1 729679 rs4951859 C G -0.0000270 0.0002221 0.9000000 0.9031680 0.843212 0.639976 NA
1 752566 rs3094315 G A -0.0000375 0.0002151 0.8600001 0.8615371 0.838951 0.718251 NA
1 752721 rs3131972 A G -0.0000251 0.0002148 0.9100000 0.9069842 0.838580 0.653355 NA
1 754503 rs3115859 G A -0.0000716 0.0002142 0.7400005 0.7383565 0.838033 0.663938 NA
1 754964 rs3131966 C T -0.0000724 0.0002149 0.7400005 0.7361684 0.838664 0.663339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51186143 rs2879914 T C -0.0001860 0.0001662 0.2599998 0.2631671 0.381826 0.2733630 NA
22 51186228 rs3865766 C T -0.0001982 0.0001620 0.2200002 0.2210386 0.451063 0.4532750 NA
22 51192586 rs5771006 G A -0.0000865 0.0002182 0.6899999 0.6917588 0.167620 0.0848642 NA
22 51193227 rs34608236 T G 0.0001644 0.0002231 0.4600002 0.4611225 0.168489 0.0692891 NA
22 51197266 rs61290853 A G -0.0001795 0.0001672 0.2800000 0.2831397 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0002033 0.0001893 0.2800000 0.2828823 0.254557 0.0984425 NA
22 51211106 rs9628250 T C 0.0002572 0.0001877 0.1700000 0.1706138 0.271547 0.1671330 NA
22 51212875 rs2238837 A C -0.0001349 0.0001783 0.4500005 0.4493141 0.331455 0.3724040 NA
22 51219006 rs28729663 G A -0.0001064 0.0002290 0.6400000 0.6422655 0.137953 0.2052720 NA
22 51237063 rs3896457 T C -0.0001564 0.0001826 0.3900004 0.3916838 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000340429:0.000274441:0.677781:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000303888:0.000271885:0.585027:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -0.000663824:0.000267708:1.88606:0.456851:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -1.28709e-05:0.000305789:0.0132283:0.24096:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -8.40287e-05:0.00018983:0.180456:0.51565:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  -2.70193e-05:0.000222088:0.0457575:0.843212:rs4951859
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  -3.75131e-05:0.000215076:0.0655015:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  -2.51032e-05:0.000214845:0.0409586:0.83858:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  -7.15657e-05:0.000214249:0.130768:0.838033:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  -7.23901e-05:0.000214851:0.130768:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -6.8817e-05:0.000217756:0.124939:0.839777:rs3131965
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  -9.81695e-05:0.000213842:0.187087:0.838313:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  -0.000103656:0.000213993:0.200659:0.838434:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862261 ES:SE:LP:AF:ID  -0.000141844:0.000228618:0.275724:0.862261:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.000264714:0.000222557:0.638272:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  -0.000123445:0.000181647:0.30103:0.761304:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  6.82874e-05:0.000202902:0.130768:0.26539:rs12124819
1   787399  rs2905055   G   T   .   PASS    AF=0.86078  ES:SE:LP:AF:ID  -0.00015551:0.000229429:0.30103:0.86078:rs2905055
1   787685  rs2905054   G   T   .   PASS    AF=0.861493 ES:SE:LP:AF:ID  -0.00016866:0.000229581:0.337242:0.861493:rs2905054
1   795988  rs59380221  C   T   .   PASS    AF=0.143051 ES:SE:LP:AF:ID  -7.55445e-05:0.000237968:0.124939:0.143051:rs59380221
1   798400  rs10900604  A   G   .   PASS    AF=0.20658  ES:SE:LP:AF:ID  2.19783e-06:0.000193783:0.00436481:0.20658:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206409 ES:SE:LP:AF:ID  2.50654e-06:0.000193866:0.00436481:0.206409:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772626 ES:SE:LP:AF:ID  7.49102e-05:0.000184418:0.167491:0.772626:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772854 ES:SE:LP:AF:ID  5.97255e-05:0.000184729:0.124939:0.772854:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340397 ES:SE:LP:AF:ID  -6.0148e-05:0.000260294:0.0861861:0.340397:rs74461805
1   824398  rs7538305   A   C   .   PASS    AF=0.138697 ES:SE:LP:AF:ID  0.000299497:0.000229865:0.721246:0.138697:rs7538305
1   830181  rs28444699  A   G   .   PASS    AF=0.697259 ES:SE:LP:AF:ID  -5.92878e-06:0.000174144:0.0132283:0.697259:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  -3.88854e-05:0.000170994:0.0861861:0.705403:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705448 ES:SE:LP:AF:ID  -3.96393e-05:0.000170988:0.0861861:0.705448:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705634 ES:SE:LP:AF:ID  -3.8922e-05:0.000170996:0.0861861:0.705634:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705662 ES:SE:LP:AF:ID  -4.49087e-05:0.000171014:0.102373:0.705662:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730134 ES:SE:LP:AF:ID  -1.82767e-05:0.000175674:0.0362122:0.730134:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294371 ES:SE:LP:AF:ID  3.85403e-05:0.000171006:0.0861861:0.294371:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236696 ES:SE:LP:AF:ID  7.33497e-05:0.000182063:0.161151:0.236696:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236684 ES:SE:LP:AF:ID  7.38809e-05:0.000182065:0.167491:0.236684:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239743 ES:SE:LP:AF:ID  9.35216e-05:0.000181481:0.21467:0.239743:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236686 ES:SE:LP:AF:ID  7.36618e-05:0.000182063:0.161151:0.236686:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212416 ES:SE:LP:AF:ID  4.66659e-05:0.00018923:0.091515:0.212416:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212311 ES:SE:LP:AF:ID  4.189e-05:0.000189263:0.0861861:0.212311:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237171 ES:SE:LP:AF:ID  9.01305e-05:0.000181924:0.207608:0.237171:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212956 ES:SE:LP:AF:ID  7.58198e-05:0.000188994:0.161151:0.212956:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212918 ES:SE:LP:AF:ID  7.78688e-05:0.000189033:0.167491:0.212918:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241155 ES:SE:LP:AF:ID  0.000103724:0.000180654:0.244125:0.241155:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213538 ES:SE:LP:AF:ID  7.10282e-05:0.000188754:0.148742:0.213538:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269503 ES:SE:LP:AF:ID  2.6024e-05:0.000174317:0.0555173:0.269503:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213508 ES:SE:LP:AF:ID  7.56076e-05:0.000188777:0.161151:0.213508:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214583 ES:SE:LP:AF:ID  7.66364e-05:0.000188414:0.167491:0.214583:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246197 ES:SE:LP:AF:ID  3.11331e-05:0.000179412:0.0655015:0.246197:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.27001  ES:SE:LP:AF:ID  5.32209e-06:0.000174441:0.00877392:0.27001:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400106 ES:SE:LP:AF:ID  0.000216184:0.000157728:0.769551:0.400106:rs4970382