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-8136/UKB-b-8136_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8136/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8136/UKB-b-8136_data.vcf.gz ...
Read summary statistics for 3763111 SNPs.
Dropped 656 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, 907685 SNPs remain.
After merging with regression SNP LD, 907685 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0041 (0.0012)
Lambda GC: 1.0519
Mean Chi^2: 1.059
Intercept: 1.0165 (0.0087)
Ratio: 0.2803 (0.1476)
Analysis finished at Thu Oct 17 14:42:11 2019
Total time elapsed: 48.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.865,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.1271e-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": 30483,
    "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": 907685,
    "ldsc_nsnp_merge_regression_ld": 907685,
    "ldsc_observed_scale_h2_beta": 0.0041,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0165,
    "ldsc_intercept_se": 0.0087,
    "ldsc_lambda_gc": 1.0519,
    "ldsc_mean_chisq": 1.059,
    "ldsc_ratio": 0.2797
}

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 3762458 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 3763111 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 8.663026e+00 5.770307e+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 7.855856e+07 5.676080e+07 828.0000000 3.159456e+07 6.889943e+07 1.147249e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.100000e-06 1.864000e-04 -0.0010622 -1.221000e-04 2.000000e-07 1.240000e-04 1.107100e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.794000e-04 2.170000e-05 0.0001507 1.606000e-04 1.724000e-04 1.945000e-04 5.513000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.914252e-01 2.918109e-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 4.914275e-01 2.917841e-01 0.0000001 2.356611e-01 4.889628e-01 7.442862e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.041282e-01 2.049699e-01 0.1330800 2.249900e-01 3.605980e-01 5.579620e-01 8.669190e-01 ▇▅▃▃▂
numeric AF_reference 30483 0.9918995 NA NA NA NA NA NA NA 3.919008e-01 2.114637e-01 0.0000000 2.184500e-01 3.556310e-01 5.455270e-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 -0.0002739 0.0002774 0.3200000 0.3235257 0.623765 0.782149 NA
1 54676 rs2462492 C T 0.0001857 0.0002748 0.5000000 0.4991483 0.400401 NA NA
1 91536 rs6702460 G T -0.0001867 0.0002706 0.4899999 0.4902556 0.456846 0.420727 NA
1 534192 rs6680723 C T 0.0005038 0.0003091 0.1000000 0.1031203 0.240959 NA NA
1 706368 rs55727773 A G -0.0004408 0.0001919 0.0219999 0.0216022 0.515645 0.275160 NA
1 729679 rs4951859 C G -0.0003586 0.0002245 0.1100001 0.1102013 0.843204 0.639976 NA
1 752566 rs3094315 G A -0.0003800 0.0002174 0.0810009 0.0805012 0.838945 0.718251 NA
1 752721 rs3131972 A G -0.0004088 0.0002172 0.0599998 0.0597901 0.838573 0.653355 NA
1 754503 rs3115859 G A -0.0003927 0.0002166 0.0700003 0.0697673 0.838026 0.663938 NA
1 754964 rs3131966 C T -0.0003877 0.0002172 0.0739997 0.0742338 0.838657 0.663339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51186143 rs2879914 T C -0.0001349 0.0001680 0.4199997 0.4218933 0.381825 0.2733630 NA
22 51186228 rs3865766 C T -0.0000319 0.0001637 0.8499999 0.8454116 0.451061 0.4532750 NA
22 51192586 rs5771006 G A -0.0002615 0.0002206 0.2399999 0.2358787 0.167627 0.0848642 NA
22 51193227 rs34608236 T G 0.0001191 0.0002255 0.5999997 0.5973107 0.168490 0.0692891 NA
22 51197266 rs61290853 A G -0.0003382 0.0001690 0.0449997 0.0454122 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0000947 0.0001913 0.6200004 0.6207973 0.254562 0.0984425 NA
22 51211106 rs9628250 T C 0.0001168 0.0001897 0.5400003 0.5381241 0.271547 0.1671330 NA
22 51212875 rs2238837 A C -0.0003285 0.0001803 0.0680002 0.0684248 0.331457 0.3724040 NA
22 51219006 rs28729663 G A 0.0002493 0.0002315 0.2800000 0.2814094 0.137950 0.2052720 NA
22 51237063 rs3896457 T C -0.0003564 0.0001845 0.0530005 0.0534724 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -0.000273858:0.000277398:0.49485:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000185729:0.000274816:0.30103:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.00018668:0.000270589:0.309804:0.456846:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  0.000503781:0.000309085:1:0.240959:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000440788:0.000191873:1.65758:0.515645:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  -0.000358553:0.000224476:0.958607:0.843204:rs4951859
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  -0.000379951:0.00021739:1.09151:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838573 ES:SE:LP:AF:ID  -0.000408761:0.000217156:1.22185:0.838573:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  -0.000392703:0.000216554:1.1549:0.838026:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838657 ES:SE:LP:AF:ID  -0.000387671:0.000217162:1.13077:0.838657:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83977  ES:SE:LP:AF:ID  -0.00036787:0.000220099:1.02228:0.83977:rs3131965
1   760912  rs1048488   C   T   .   PASS    AF=0.838306 ES:SE:LP:AF:ID  -0.000370045:0.000216143:1.06048:0.838306:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838427 ES:SE:LP:AF:ID  -0.000367463:0.000216295:1.05061:0.838427:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862254 ES:SE:LP:AF:ID  -0.000416056:0.000231076:1.14267:0.862254:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -8.55784e-05:0.000224953:0.154902:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  -0.000241727:0.000183601:0.721246:0.761297:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  -5.78389e-05:0.000205089:0.107905:0.265385:rs12124819
1   787399  rs2905055   G   T   .   PASS    AF=0.860776 ES:SE:LP:AF:ID  -0.000416441:0.000231897:1.13668:0.860776:rs2905055
1   787685  rs2905054   G   T   .   PASS    AF=0.861487 ES:SE:LP:AF:ID  -0.000353406:0.000232048:0.886057:0.861487:rs2905054
1   795988  rs59380221  C   T   .   PASS    AF=0.143053 ES:SE:LP:AF:ID  0.000354621:0.000240527:0.853872:0.143053:rs59380221
1   798400  rs10900604  A   G   .   PASS    AF=0.206591 ES:SE:LP:AF:ID  0.000314977:0.000195865:0.958607:0.206591:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.20642  ES:SE:LP:AF:ID  0.000319523:0.000195949:1:0.20642:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772619 ES:SE:LP:AF:ID  -0.000340717:0.000186402:1.16749:0.772619:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772847 ES:SE:LP:AF:ID  -0.000333805:0.000186716:1.13077:0.772847:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  -0.000200324:0.000263092:0.346787:0.340396:rs74461805
1   824398  rs7538305   A   C   .   PASS    AF=0.138699 ES:SE:LP:AF:ID  3.02804e-05:0.000232338:0.0457575:0.138699:rs7538305
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  -5.61899e-05:0.000176022:0.124939:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  -0.000151514:0.000172836:0.420216:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  -0.000146189:0.000172831:0.39794:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  -0.000150152:0.000172839:0.420216:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  -0.000151268:0.000172857:0.420216:0.705655:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730129 ES:SE:LP:AF:ID  -0.000219552:0.000177567:0.657577:0.730129:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  0.000150108:0.000172849:0.408935:0.294377:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236703 ES:SE:LP:AF:ID  6.8568e-05:0.000184024:0.148742:0.236703:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236691 ES:SE:LP:AF:ID  6.91064e-05:0.000184026:0.148742:0.236691:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.23975  ES:SE:LP:AF:ID  6.08754e-05:0.000183436:0.130768:0.23975:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236693 ES:SE:LP:AF:ID  7.50865e-05:0.000184025:0.167491:0.236693:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212421 ES:SE:LP:AF:ID  0.000151265:0.000191269:0.366532:0.212421:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212316 ES:SE:LP:AF:ID  0.00014839:0.000191302:0.356547:0.212316:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237178 ES:SE:LP:AF:ID  7.07643e-05:0.000183884:0.154902:0.237178:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212962 ES:SE:LP:AF:ID  0.000140362:0.00019103:0.337242:0.212962:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212924 ES:SE:LP:AF:ID  0.00014862:0.000191069:0.356547:0.212924:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  0.000138004:0.0001826:0.346787:0.241162:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213543 ES:SE:LP:AF:ID  0.000154538:0.000190788:0.376751:0.213543:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269511 ES:SE:LP:AF:ID  -1.69125e-05:0.000176195:0.0362122:0.269511:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213513 ES:SE:LP:AF:ID  0.000148201:0.000190811:0.356547:0.213513:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214587 ES:SE:LP:AF:ID  0.000156975:0.000190443:0.387216:0.214587:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  5.0259e-05:0.000181344:0.107905:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  -2.5132e-05:0.00017632:0.05061:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -3.10704e-06:0.000159427:0.00877392:0.400124:rs4970382