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-14640/UKB-b-14640_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14640/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:45 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14640/UKB-b-14640_data.vcf.gz ...
Read summary statistics for 3754254 SNPs.
Dropped 653 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, 905935 SNPs remain.
After merging with regression SNP LD, 905935 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0002 (0.0082)
Lambda GC: 1.0003
Mean Chi^2: 0.9999
Intercept: 1.0002 (0.0086)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Thu Oct 17 14:44:35 2019
Total time elapsed: 49.98s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8648,
    "inflation_factor": 1,
    "mean_EFFECT": 3.8735e-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": 30384,
    "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": 905935,
    "ldsc_nsnp_merge_regression_ld": 905935,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0002,
    "ldsc_intercept_se": 0.0086,
    "ldsc_lambda_gc": 1.0003,
    "ldsc_mean_chisq": 0.9999,
    "ldsc_ratio": -2
}
 

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 3753604 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 3754254 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 8.662791e+00 5.769723e+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 7.855490e+07 5.675299e+07 828.0000000 3.159549e+07 6.889988e+07 1.147179e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.900000e-06 1.258400e-03 -0.0074013 -8.305000e-04 4.900000e-06 8.395000e-04 7.719400e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.252000e-03 1.504000e-04 0.0010533 1.121200e-03 1.203600e-03 1.356400e-03 3.871200e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.001346e-01 2.885486e-01 0.0000046 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 5.001346e-01 2.885246e-01 0.0000046 2.502309e-01 5.005677e-01 7.498738e-01 9.999990e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.045292e-01 2.046606e-01 0.1337410 2.256580e-01 3.611795e-01 5.582610e-01 8.662590e-01 ▇▅▃▃▂
numeric AF_reference 30384 0.9919068 NA NA NA NA NA NA NA 3.922715e-01 2.112541e-01 0.0000000 2.188500e-01 3.560300e-01 5.457270e-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 -0.0028503 0.0019412 0.1400000 0.1420238 0.623812 0.782149 NA
1 54676 rs2462492 C T 0.0047878 0.0019356 0.0129999 0.0133773 0.399144 NA NA
1 91536 rs6702460 G T -0.0021727 0.0019038 0.2500000 0.2537728 0.455916 0.420727 NA
1 534192 rs6680723 C T -0.0019671 0.0021683 0.3599996 0.3642984 0.242057 NA NA
1 706368 rs55727773 A G -0.0004085 0.0013420 0.7600007 0.7608152 0.513304 0.275160 NA
1 729679 rs4951859 C G -0.0001585 0.0015636 0.9199999 0.9192710 0.841441 0.639976 NA
1 736289 rs79010578 T A 0.0013276 0.0016865 0.4299995 0.4311722 0.134139 0.139577 NA
1 752566 rs3094315 G A -0.0006068 0.0015126 0.6899999 0.6882978 0.837029 0.718251 NA
1 752721 rs3131972 A G -0.0006684 0.0015115 0.6600001 0.6583114 0.836733 0.653355 NA
1 754503 rs3115859 G A -0.0005325 0.0015071 0.7199992 0.7238140 0.836159 0.663938 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51186143 rs2879914 T C 0.0006512 0.0011751 0.5800000 0.5794643 0.380077 0.2733630 NA
22 51186228 rs3865766 C T 0.0009998 0.0011446 0.3800004 0.3823608 0.449547 0.4532750 NA
22 51192586 rs5771006 G A 0.0012323 0.0015430 0.4199997 0.4244945 0.167396 0.0848642 NA
22 51193227 rs34608236 T G 0.0008892 0.0015736 0.5700002 0.5720258 0.168560 0.0692891 NA
22 51197266 rs61290853 A G 0.0018429 0.0011795 0.1199999 0.1181857 0.386693 0.4229230 NA
22 51198027 rs34939255 A G -0.0001526 0.0013377 0.9100000 0.9091897 0.254586 0.0984425 NA
22 51211106 rs9628250 T C 0.0003649 0.0013270 0.7800007 0.7833452 0.271468 0.1671330 NA
22 51212875 rs2238837 A C 0.0013871 0.0012614 0.2700001 0.2714658 0.331351 0.3724040 NA
22 51219006 rs28729663 G A 0.0013520 0.0016323 0.4100001 0.4075049 0.136315 0.2052720 NA
22 51237063 rs3896457 T C 0.0007444 0.0012886 0.5600000 0.5634857 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.00285033:0.00194125:0.853872:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  0.00478783:0.0019356:1.88606:0.399144:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.00217268:0.0019038:0.60206:0.455916:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.00196712:0.00216833:0.443698:0.242057:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  -0.000408531:0.00134204:0.119186:0.513304:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  -0.000158474:0.0015636:0.0362122:0.841441:rs4951859
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  0.00132756:0.00168646:0.366532:0.134139:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  -0.000606804:0.0015126:0.161151:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  -0.00066845:0.00151149:0.180456:0.836733:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  -0.000532544:0.00150706:0.142668:0.836159:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  -0.000591573:0.00151119:0.154902:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  -0.000548394:0.00153247:0.142668:0.838109:rs3131965
1   760912  rs1048488   C   T   .   PASS    AF=0.836369 ES:SE:LP:AF:ID  -0.000382035:0.00150331:0.09691:0.836369:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836495 ES:SE:LP:AF:ID  -0.000405311:0.00150433:0.102373:0.836495:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860851 ES:SE:LP:AF:ID  -0.00118503:0.00161122:0.337242:0.860851:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  -0.00201479:0.00157227:0.69897:0.705804:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.758252 ES:SE:LP:AF:ID  0.000324529:0.00127433:0.09691:0.758252:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  -0.000728986:0.00143995:0.21467:0.263729:rs12124819
1   787399  rs2905055   G   T   .   PASS    AF=0.859749 ES:SE:LP:AF:ID  -0.00101632:0.0016193:0.275724:0.859749:rs2905055
1   787685  rs2905054   G   T   .   PASS    AF=0.860334 ES:SE:LP:AF:ID  -0.00107516:0.00162021:0.29243:0.860334:rs2905054
1   795988  rs59380221  C   T   .   PASS    AF=0.144405 ES:SE:LP:AF:ID  0.00126733:0.00167486:0.346787:0.144405:rs59380221
1   798400  rs10900604  A   G   .   PASS    AF=0.209824 ES:SE:LP:AF:ID  -0.000214685:0.00135859:0.0604807:0.209824:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.209642 ES:SE:LP:AF:ID  -0.000223305:0.00135931:0.0604807:0.209642:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.76828  ES:SE:LP:AF:ID  0.000267245:0.00129191:0.0757207:0.76828:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.768417 ES:SE:LP:AF:ID  0.000215878:0.00129356:0.0604807:0.768417:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340108 ES:SE:LP:AF:ID  -0.00126501:0.00183778:0.309804:0.340108:rs74461805
1   824398  rs7538305   A   C   .   PASS    AF=0.14012  ES:SE:LP:AF:ID  -9.76394e-06:0.00162207:-0:0.14012:rs7538305
1   830181  rs28444699  A   G   .   PASS    AF=0.696612 ES:SE:LP:AF:ID  -0.000923408:0.00122952:0.346787:0.696612:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705031 ES:SE:LP:AF:ID  -0.00053852:0.00120725:0.180456:0.705031:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705083 ES:SE:LP:AF:ID  -0.000530258:0.00120725:0.180456:0.705083:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705261 ES:SE:LP:AF:ID  -0.000535553:0.00120719:0.180456:0.705261:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705286 ES:SE:LP:AF:ID  -0.000541753:0.00120736:0.187087:0.705286:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730154 ES:SE:LP:AF:ID  -0.000990327:0.00124067:0.376751:0.730154:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294729 ES:SE:LP:AF:ID  0.000540335:0.00120732:0.187087:0.294729:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.237157 ES:SE:LP:AF:ID  0.000527224:0.00128534:0.167491:0.237157:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.237168 ES:SE:LP:AF:ID  0.000481482:0.00128536:0.148742:0.237168:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.240204 ES:SE:LP:AF:ID  0.000707299:0.00128154:0.236572:0.240204:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.23716  ES:SE:LP:AF:ID  0.000484799:0.00128541:0.148742:0.23716:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212467 ES:SE:LP:AF:ID  0.00105532:0.00133618:0.366532:0.212467:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.21236  ES:SE:LP:AF:ID  0.00108477:0.00133651:0.376751:0.21236:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237633 ES:SE:LP:AF:ID  0.000498707:0.00128445:0.154902:0.237633:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.213048 ES:SE:LP:AF:ID  0.00111426:0.00133419:0.39794:0.213048:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.213007 ES:SE:LP:AF:ID  0.00118223:0.00133443:0.420216:0.213007:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241744 ES:SE:LP:AF:ID  0.000308441:0.00127484:0.091515:0.241744:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213504 ES:SE:LP:AF:ID  0.000984121:0.00133284:0.337242:0.213504:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269687 ES:SE:LP:AF:ID  0.000421614:0.00123184:0.136677:0.269687:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213501 ES:SE:LP:AF:ID  0.00102461:0.00133301:0.356547:0.213501:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214599 ES:SE:LP:AF:ID  0.00116535:0.00133043:0.420216:0.214599:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.245985 ES:SE:LP:AF:ID  0.00116191:0.00126818:0.443698:0.245985:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270067 ES:SE:LP:AF:ID  0.000324983:0.00123285:0.102373:0.270067:rs28562941