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-3663/UKB-b-3663_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3663/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-3663/UKB-b-3663_data.vcf.gz ...
Read summary statistics for 3780268 SNPs.
Dropped 660 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, 910990 SNPs remain.
After merging with regression SNP LD, 910990 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.006 (0.0013)
Lambda GC: 1.0389
Mean Chi^2: 1.0506
Intercept: 0.9933 (0.009)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:44:33 2019
Total time elapsed: 48.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8658,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -1.4633e-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": 30638,
    "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": 910990,
    "ldsc_nsnp_merge_regression_ld": 910990,
    "ldsc_observed_scale_h2_beta": 0.006,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 0.9933,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.0389,
    "ldsc_mean_chisq": 1.0506,
    "ldsc_ratio": -0.1324
}

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 3779611 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 3780268 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 8.663152e+00 5.769609e+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 7.855941e+07 5.675459e+07 828.0000000 3.160823e+07 6.889477e+07 1.147156e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.500000e-06 1.941000e-04 -0.0011297 -1.298000e-04 -2.100000e-06 1.267000e-04 1.306000e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.880000e-04 2.290000e-05 0.0001578 1.681000e-04 1.806000e-04 2.039000e-04 5.769000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.924471e-01 2.907837e-01 0.0000001 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.924485e-01 2.907570e-01 0.0000001 2.386195e-01 4.902298e-01 7.442813e-01 9.999990e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.033665e-01 2.055390e-01 0.1319760 2.239130e-01 3.595040e-01 5.574510e-01 8.680240e-01 ▇▅▃▃▂
numeric AF_reference 30638 0.9918953 NA NA NA NA NA NA NA 3.912518e-01 2.118420e-01 0.0000000 2.174520e-01 3.546330e-01 5.451280e-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 -0.0001690 0.0002903 0.5600000 0.5603862 0.623749 0.782149 NA
1 54676 rs2462492 C T -0.0001737 0.0002876 0.5500004 0.5458912 0.400421 NA NA
1 91536 rs6702460 G T -0.0003874 0.0002831 0.1700000 0.1712135 0.456855 0.420727 NA
1 534192 rs6680723 C T 0.0005130 0.0003235 0.1100001 0.1127742 0.240907 NA NA
1 706368 rs55727773 A G 0.0002006 0.0002008 0.3200000 0.3179013 0.515736 0.275160 NA
1 729679 rs4951859 C G 0.0002204 0.0002350 0.3500000 0.3482378 0.843141 0.639976 NA
1 736289 rs79010578 T A -0.0003061 0.0002535 0.2300001 0.2273795 0.132400 0.139577 NA
1 752566 rs3094315 G A 0.0003023 0.0002275 0.1800002 0.1839267 0.838834 0.718251 NA
1 752721 rs3131972 A G 0.0003181 0.0002272 0.1600000 0.1615750 0.838455 0.653355 NA
1 754503 rs3115859 G A 0.0003157 0.0002266 0.1600000 0.1636089 0.837906 0.663938 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51186228 rs3865766 C T -0.0002213 0.0001714 0.2000000 0.1966098 0.451288 0.4532750 NA
22 51192586 rs5771006 G A -0.0001260 0.0002307 0.5900000 0.5851200 0.167724 0.0848642 NA
22 51193227 rs34608236 T G 0.0007199 0.0002360 0.0023000 0.0022824 0.168355 0.0692891 NA
22 51197266 rs61290853 A G -0.0001690 0.0001769 0.3400001 0.3394949 0.386529 0.4229230 NA
22 51198027 rs34939255 A G 0.0004902 0.0002003 0.0140001 0.0143790 0.254390 0.0984425 NA
22 51211106 rs9628250 T C 0.0004080 0.0001986 0.0400000 0.0398839 0.271382 0.1671330 NA
22 51211392 rs3888396 T C -0.0001391 0.0002643 0.5999997 0.5987760 0.132616 0.1641370 NA
22 51212875 rs2238837 A C -0.0000584 0.0001886 0.7600007 0.7569778 0.331628 0.3724040 NA
22 51219006 rs28729663 G A -0.0002202 0.0002422 0.3599996 0.3632282 0.138003 0.2052720 NA
22 51237063 rs3896457 T C -0.0001148 0.0001931 0.5500004 0.5521703 0.298171 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623749 ES:SE:LP:AF:ID  -0.000169012:0.000290265:0.251812:0.623749:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400421 ES:SE:LP:AF:ID  -0.000173685:0.000287592:0.259637:0.400421:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456855 ES:SE:LP:AF:ID  -0.000387396:0.000283119:0.769551:0.456855:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240907 ES:SE:LP:AF:ID  0.00051298:0.000323474:0.958607:0.240907:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515736 ES:SE:LP:AF:ID  0.000200574:0.000200819:0.49485:0.515736:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843141 ES:SE:LP:AF:ID  0.000220388:0.000234952:0.455932:0.843141:rs4951859
1   736289  rs79010578  T   A   .   PASS    AF=0.1324   ES:SE:LP:AF:ID  -0.000306055:0.000253538:0.638272:0.1324:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838834 ES:SE:LP:AF:ID  0.000302268:0.000227481:0.744727:0.838834:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838455 ES:SE:LP:AF:ID  0.000318071:0.000227227:0.79588:0.838455:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.837906 ES:SE:LP:AF:ID  0.000315655:0.000226595:0.79588:0.837906:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838538 ES:SE:LP:AF:ID  0.000325103:0.000227234:0.823909:0.838538:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839658 ES:SE:LP:AF:ID  0.000328566:0.000230319:0.823909:0.839658:rs3131965
1   757640  rs3115853   G   A   .   PASS    AF=0.867839 ES:SE:LP:AF:ID  0.000315946:0.000242004:0.721246:0.867839:rs3115853
1   760912  rs1048488   C   T   .   PASS    AF=0.838191 ES:SE:LP:AF:ID  0.000302127:0.000226176:0.744727:0.838191:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838311 ES:SE:LP:AF:ID  0.000299425:0.000226336:0.721246:0.838311:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862193 ES:SE:LP:AF:ID  0.000297268:0.000241832:0.657577:0.862193:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706669 ES:SE:LP:AF:ID  0.000139579:0.000235429:0.259637:0.706669:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761347 ES:SE:LP:AF:ID  0.000277559:0.000192235:0.823909:0.761347:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265297 ES:SE:LP:AF:ID  0.000240358:0.000214683:0.585027:0.265297:rs12124819
1   787399  rs2905055   G   T   .   PASS    AF=0.860737 ES:SE:LP:AF:ID  0.000315215:0.000242688:0.721246:0.860737:rs2905055
1   787685  rs2905054   G   T   .   PASS    AF=0.861468 ES:SE:LP:AF:ID  0.000282219:0.000242866:0.60206:0.861468:rs2905054
1   795988  rs59380221  C   T   .   PASS    AF=0.143059 ES:SE:LP:AF:ID  -0.000116656:0.000251749:0.19382:0.143059:rs59380221
1   798400  rs10900604  A   G   .   PASS    AF=0.206566 ES:SE:LP:AF:ID  -0.000217347:0.000205041:0.537602:0.206566:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206394 ES:SE:LP:AF:ID  -0.00022644:0.000205128:0.568636:0.206394:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772658 ES:SE:LP:AF:ID  0.000156974:0.000195157:0.376751:0.772658:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.77289  ES:SE:LP:AF:ID  0.000151125:0.000195486:0.356547:0.77289:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340422 ES:SE:LP:AF:ID  0.000420243:0.000275369:0.886057:0.340422:rs74461805
1   824398  rs7538305   A   C   .   PASS    AF=0.138734 ES:SE:LP:AF:ID  5.13316e-05:0.000243224:0.0809219:0.138734:rs7538305
1   830181  rs28444699  A   G   .   PASS    AF=0.69722  ES:SE:LP:AF:ID  0.000195456:0.000184186:0.537602:0.69722:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705385 ES:SE:LP:AF:ID  0.000121696:0.000180847:0.30103:0.705385:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705429 ES:SE:LP:AF:ID  0.000125986:0.000180841:0.309804:0.705429:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705616 ES:SE:LP:AF:ID  0.000124039:0.000180847:0.309804:0.705616:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705643 ES:SE:LP:AF:ID  0.000122809:0.000180867:0.30103:0.705643:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730087 ES:SE:LP:AF:ID  0.000165432:0.000185803:0.431798:0.730087:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.29439  ES:SE:LP:AF:ID  -0.000123939:0.000180858:0.309804:0.29439:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236718 ES:SE:LP:AF:ID  -0.000104849:0.000192594:0.229148:0.236718:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236707 ES:SE:LP:AF:ID  -0.00010449:0.000192593:0.229148:0.236707:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239774 ES:SE:LP:AF:ID  -0.000121363:0.000191975:0.275724:0.239774:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.23671  ES:SE:LP:AF:ID  -0.000104483:0.000192591:0.229148:0.23671:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212468 ES:SE:LP:AF:ID  -0.000154311:0.00020018:0.356547:0.212468:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212364 ES:SE:LP:AF:ID  -0.000150134:0.000200217:0.346787:0.212364:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237195 ES:SE:LP:AF:ID  -0.000113417:0.000192445:0.251812:0.237195:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.213008 ES:SE:LP:AF:ID  -0.000164951:0.000199932:0.387216:0.213008:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212969 ES:SE:LP:AF:ID  -0.000167223:0.000199972:0.39794:0.212969:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241171 ES:SE:LP:AF:ID  -6.12254e-05:0.000191097:0.124939:0.241171:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213588 ES:SE:LP:AF:ID  -0.000172559:0.00019968:0.408935:0.213588:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269524 ES:SE:LP:AF:ID  -0.000131064:0.000184396:0.318759:0.269524:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213557 ES:SE:LP:AF:ID  -0.000164717:0.000199704:0.387216:0.213557:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214623 ES:SE:LP:AF:ID  -0.000167598:0.000199331:0.39794:0.214623:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246259 ES:SE:LP:AF:ID  -0.00018876:0.000189792:0.49485:0.246259:rs4970383