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-15083/UKB-b-15083_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15083/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:56 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15083/UKB-b-15083_data.vcf.gz ...
Read summary statistics for 3715037 SNPs.
Dropped 636 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, 898186 SNPs remain.
After merging with regression SNP LD, 898186 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0023 (0.0012)
Lambda GC: 1.0546
Mean Chi^2: 1.0586
Intercept: 1.0362 (0.0094)
Ratio: 0.6181 (0.1596)
Analysis finished at Thu Oct 17 14:44:41 2019
Total time elapsed: 44.32s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8627,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 8.8606e-07,
    "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": 30028,
    "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": 898186,
    "ldsc_nsnp_merge_regression_ld": 898186,
    "ldsc_observed_scale_h2_beta": 0.0023,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0362,
    "ldsc_intercept_se": 0.0094,
    "ldsc_lambda_gc": 1.0546,
    "ldsc_mean_chisq": 1.0586,
    "ldsc_ratio": 0.6177
}

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 TRUE
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 3714404 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 3715037 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 8.662931e+00 5.770739e+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 7.855324e+07 5.675933e+07 828.0000000 3.158878e+07 6.889728e+07 1.147173e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.000000e-07 1.905000e-04 -0.0011126 -1.252000e-04 5.000000e-07 1.269000e-04 1.086800e-03 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.840000e-04 2.160000e-05 0.0001551 1.652000e-04 1.770000e-04 1.990000e-04 5.672000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.919008e-01 2.914808e-01 0.0000005 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 4.919021e-01 2.914545e-01 0.0000005 2.370797e-01 4.890800e-01 7.450415e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.062251e-01 2.033389e-01 0.1364000 2.282890e-01 3.634490e-01 5.592690e-01 8.636000e-01 ▇▅▃▃▂
numeric AF_reference 30028 0.9919172 NA NA NA NA NA NA NA 3.937223e-01 2.103794e-01 0.0000000 2.210460e-01 3.582270e-01 5.467250e-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 -0.0001354 0.0002854 0.6400000 0.6351718 0.623741 0.782149 NA
1 54676 rs2462492 C T 0.0001711 0.0002828 0.5500004 0.5451415 0.400433 NA NA
1 91536 rs6702460 G T -0.0000226 0.0002784 0.9400001 0.9351978 0.456866 0.420727 NA
1 534192 rs6680723 C T -0.0000514 0.0003181 0.8700001 0.8715638 0.240909 NA NA
1 706368 rs55727773 A G -0.0000407 0.0001975 0.8400000 0.8365325 0.515740 0.275160 NA
1 729679 rs4951859 C G -0.0001176 0.0002310 0.6100002 0.6105989 0.843125 0.639976 NA
1 752566 rs3094315 G A -0.0000939 0.0002237 0.6700003 0.6747074 0.838820 0.718251 NA
1 752721 rs3131972 A G -0.0000881 0.0002234 0.6899999 0.6932694 0.838442 0.653355 NA
1 754503 rs3115859 G A -0.0000871 0.0002228 0.6999999 0.6957964 0.837892 0.663938 NA
1 754964 rs3131966 C T -0.0000906 0.0002234 0.6800001 0.6849408 0.838523 0.663339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51186143 rs2879914 T C 0.0003969 0.0001729 0.0219999 0.0216628 0.382059 0.2733630 NA
22 51186228 rs3865766 C T 0.0002540 0.0001685 0.1299999 0.1317398 0.451318 0.4532750 NA
22 51192586 rs5771006 G A 0.0004847 0.0002269 0.0329997 0.0326564 0.167754 0.0848642 NA
22 51193227 rs34608236 T G -0.0002446 0.0002320 0.2900000 0.2918473 0.168324 0.0692891 NA
22 51197266 rs61290853 A G 0.0000564 0.0001739 0.7499995 0.7458851 0.386542 0.4229230 NA
22 51198027 rs34939255 A G -0.0002799 0.0001969 0.1600000 0.1552910 0.254389 0.0984425 NA
22 51211106 rs9628250 T C -0.0002189 0.0001952 0.2599998 0.2622010 0.271372 0.1671330 NA
22 51212875 rs2238837 A C 0.0004190 0.0001855 0.0239999 0.0238911 0.331646 0.3724040 NA
22 51219006 rs28729663 G A -0.0001980 0.0002381 0.4100001 0.4057358 0.138010 0.2052720 NA
22 51237063 rs3896457 T C 0.0003541 0.0001899 0.0619998 0.0621585 0.298185 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623741 ES:SE:LP:AF:ID  -0.00013541:0.000285398:0.19382:0.623741:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400433 ES:SE:LP:AF:ID  0.00017109:0.000282767:0.259637:0.400433:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456866 ES:SE:LP:AF:ID  -2.26322e-05:0.000278355:0.0268721:0.456866:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240909 ES:SE:LP:AF:ID  -5.14209e-05:0.000318056:0.0604807:0.240909:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.51574  ES:SE:LP:AF:ID  -4.07427e-05:0.000197463:0.0757207:0.51574:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843125 ES:SE:LP:AF:ID  -0.000117628:0.000230997:0.21467:0.843125:rs4951859
1   752566  rs3094315   G   A   .   PASS    AF=0.83882  ES:SE:LP:AF:ID  -9.38663e-05:0.000223653:0.173925:0.83882:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838442 ES:SE:LP:AF:ID  -8.81151e-05:0.000223403:0.161151:0.838442:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.837892 ES:SE:LP:AF:ID  -8.7108e-05:0.000222782:0.154902:0.837892:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838523 ES:SE:LP:AF:ID  -9.06434e-05:0.000223408:0.167491:0.838523:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839643 ES:SE:LP:AF:ID  -0.000124221:0.000226444:0.236572:0.839643:rs3131965
1   760912  rs1048488   C   T   .   PASS    AF=0.838177 ES:SE:LP:AF:ID  -0.000113355:0.000222368:0.21467:0.838177:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838297 ES:SE:LP:AF:ID  -0.000107588:0.000222526:0.200659:0.838297:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862177 ES:SE:LP:AF:ID  -0.000209361:0.000237755:0.420216:0.862177:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706661 ES:SE:LP:AF:ID  -6.60063e-05:0.000231465:0.107905:0.706661:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761334 ES:SE:LP:AF:ID  -0.000207175:0.000189019:0.568636:0.761334:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265269 ES:SE:LP:AF:ID  -5.96491e-05:0.000211085:0.107905:0.265269:rs12124819
1   787399  rs2905055   G   T   .   PASS    AF=0.860716 ES:SE:LP:AF:ID  -0.000326396:0.000238597:0.769551:0.860716:rs2905055
1   787685  rs2905054   G   T   .   PASS    AF=0.861443 ES:SE:LP:AF:ID  -0.000342431:0.000238769:0.823909:0.861443:rs2905054
1   795988  rs59380221  C   T   .   PASS    AF=0.14306  ES:SE:LP:AF:ID  0.000322131:0.000247522:0.721246:0.14306:rs59380221
1   798400  rs10900604  A   G   .   PASS    AF=0.20658  ES:SE:LP:AF:ID  0.000295552:0.000201609:0.853872:0.20658:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206409 ES:SE:LP:AF:ID  0.000295973:0.000201695:0.853872:0.206409:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772644 ES:SE:LP:AF:ID  -0.000273484:0.000191893:0.823909:0.772644:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772874 ES:SE:LP:AF:ID  -0.000291785:0.000192215:0.886057:0.772874:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340412 ES:SE:LP:AF:ID  0.000147534:0.000270759:0.229148:0.340412:rs74461805
1   824398  rs7538305   A   C   .   PASS    AF=0.138738 ES:SE:LP:AF:ID  0.000165834:0.000239137:0.309804:0.138738:rs7538305
1   830181  rs28444699  A   G   .   PASS    AF=0.697225 ES:SE:LP:AF:ID  0.000202906:0.000181103:0.585027:0.697225:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705402 ES:SE:LP:AF:ID  0.000210774:0.000177821:0.619789:0.705402:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705445 ES:SE:LP:AF:ID  0.000208404:0.000177814:0.619789:0.705445:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705632 ES:SE:LP:AF:ID  0.000213689:0.000177821:0.638272:0.705632:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.70566  ES:SE:LP:AF:ID  0.00021601:0.00017784:0.657577:0.70566:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730095 ES:SE:LP:AF:ID  0.000230381:0.000182693:0.677781:0.730095:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294374 ES:SE:LP:AF:ID  -0.000211463:0.000177831:0.638272:0.294374:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.2367   ES:SE:LP:AF:ID  -0.000439554:0.000189372:1.69897:0.2367:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236689 ES:SE:LP:AF:ID  -0.000436402:0.000189372:1.67778:0.236689:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239758 ES:SE:LP:AF:ID  -0.000415745:0.000188765:1.55284:0.239758:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236692 ES:SE:LP:AF:ID  -0.000436529:0.00018937:1.67778:0.236692:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212458 ES:SE:LP:AF:ID  -0.000467839:0.000196831:1.76955:0.212458:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212354 ES:SE:LP:AF:ID  -0.000472238:0.000196867:1.79588:0.212354:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237178 ES:SE:LP:AF:ID  -0.000435845:0.000189226:1.67778:0.237178:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212999 ES:SE:LP:AF:ID  -0.000467842:0.000196587:1.76955:0.212999:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.21296  ES:SE:LP:AF:ID  -0.000464828:0.000196626:1.74473:0.21296:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241153 ES:SE:LP:AF:ID  -0.000414763:0.000187898:1.56864:0.241153:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213579 ES:SE:LP:AF:ID  -0.000464928:0.000196339:1.74473:0.213579:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269507 ES:SE:LP:AF:ID  -0.000346432:0.000181306:1.25181:0.269507:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213548 ES:SE:LP:AF:ID  -0.000470508:0.000196363:1.76955:0.213548:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214613 ES:SE:LP:AF:ID  -0.000474304:0.000195996:1.79588:0.214613:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246248 ES:SE:LP:AF:ID  -0.000376294:0.000186612:1.35655:0.246248:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270008 ES:SE:LP:AF:ID  -0.000357344:0.000181431:1.3098:0.270008:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400287 ES:SE:LP:AF:ID  -0.000117655:0.000164044:0.327902:0.400287:rs4970382