Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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 /data/cromwell-executions/qc/51a78191-9487-491f-bad1-ae9e123740e7/call-ldsc/inputs/562856125/ieu-b-10.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-10/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Jun 26 15:25:34 2020
Reading summary statistics from /data/cromwell-executions/qc/51a78191-9487-491f-bad1-ae9e123740e7/call-ldsc/inputs/562856125/ieu-b-10.vcf.gz ...
Read summary statistics for 4862769 SNPs.
Dropped 11434 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/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 /data/ref/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 930582 SNPs remain.
After merging with regression SNP LD, 930582 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0314 (0.0173)
Lambda GC: 1.194
Mean Chi^2: 1.1913
Intercept: 1.1639 (0.0101)
Ratio: 0.8568 (0.0528)
Analysis finished at Fri Jun 26 15:28:10 2020
Total time elapsed: 2.0m:36.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9402,
    "inflation_factor": 1.1909,
    "mean_EFFECT": 0.0007,
    "n": "-Inf",
    "n_snps": 4862782,
    "n_clumped_hits": 1,
    "n_p_sig": 4,
    "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": 28996,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NA",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 930582,
    "ldsc_nsnp_merge_regression_ld": 930582,
    "ldsc_observed_scale_h2_beta": 0.0314,
    "ldsc_observed_scale_h2_se": 0.0173,
    "ldsc_intercept_beta": 1.1639,
    "ldsc_intercept_se": 0.0101,
    "ldsc_lambda_gc": 1.194,
    "ldsc_mean_chisq": 1.1913,
    "ldsc_ratio": 0.8568
}
 

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 1 0.9999998 3 35 0 4862779 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 4862782 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 8.638433e+00 5.865020e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.980983e+07 5.499637e+07 3.30120e+04 3.481541e+07 7.129924e+07 1.144377e+08 2.49219e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 6.963000e-04 1.619080e-02 -1.51322e-01 -8.257000e-03 4.211000e-04 9.229200e-03 1.92876e-01 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.348290e-02 6.379600e-03 8.38360e-03 9.049900e-03 1.092100e-02 1.542740e-02 8.75774e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.730882e-01 2.956290e-01 0.00000e+00 2.099999e-01 4.617001e-01 7.300002e-01 1.00000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.730932e-01 2.956302e-01 0.00000e+00 2.098431e-01 4.617308e-01 7.300942e-01 1.00000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.062228e-01 2.567318e-01 2.60000e-03 9.060000e-02 2.251000e-01 4.741000e-01 9.90000e-01 ▇▃▂▂▁
numeric AF_reference 28996 0.9940372 NA NA NA NA NA NA NA 3.074937e-01 2.470186e-01 1.99700e-04 1.034350e-01 2.360220e-01 4.676520e-01 1.00000e+00 ▇▅▃▂▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1029805 rs6689308 A G -0.0050973 0.0113023 0.6520997 0.6519907 0.1685 0.3156950 NA
1 1030565 rs6687776 C T -0.0023476 0.0112865 0.8352000 0.8352284 0.1684 0.3067090 NA
1 1030633 rs6678318 G A -0.0022920 0.0112907 0.8395000 0.8391359 0.1683 0.3065100 NA
1 1031973 rs9651270 C T -0.0015743 0.0116615 0.8923000 0.8926114 0.1611 0.3107030 NA
1 1033596 rs6604964 T C -0.0014353 0.0116692 0.9022000 0.9021065 0.1609 0.3117010 NA
1 1033670 rs6604966 T C -0.0024406 0.0116777 0.8342000 0.8344482 0.1608 0.3158950 NA
1 1033680 rs6604967 T A -0.0025221 0.0116765 0.8292000 0.8289873 0.1608 0.3117010 NA
1 1033994 rs6698368 C T -0.0025916 0.0116739 0.8243000 0.8243143 0.1609 0.3115020 NA
1 1034200 rs77977351 T C -0.0021481 0.0116742 0.8540001 0.8540130 0.1609 0.3115020 NA
1 1036601 rs72910156 C T 0.0654638 0.0285868 0.0219999 0.0220213 0.0242 0.0399361 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 139314056 rs5955415 C G 0.0065677 0.0149265 0.6600001 0.6599371 0.0969 0.125033 NA
23 139314798 rs62609008 C A 0.0076393 0.0149791 0.6100002 0.6100515 0.0961 0.106755 NA
23 139315107 rs62609010 T A 0.0082786 0.0149703 0.5800000 0.5802637 0.0962 0.107020 NA
23 139316769 rs73230748 T C 0.0096035 0.0149354 0.5199996 0.5202229 0.0967 0.121060 NA
23 139317055 rs62609011 C A 0.0096027 0.0149343 0.5199996 0.5202247 0.0967 0.116026 NA
23 139317165 rs28877369 C G 0.0078335 0.0149495 0.5999997 0.6002789 0.0965 0.116291 NA
23 139317337 rs55757628 A G 0.0072163 0.0149717 0.6300007 0.6298069 0.0962 0.107285 NA
23 139319949 rs140616281 A G 0.0082804 0.0149735 0.5800000 0.5802623 0.0962 0.116291 NA
23 139320136 rs76621315 C G 0.0082547 0.0149272 0.5800000 0.5802644 0.0968 0.114437 NA
23 139325995 rs62609013 G A 0.0080563 0.0149467 0.5900000 0.5898869 0.0965 0.101987 NA

bcf preview

1   1029805 rs891281851 A   G   .   PASS    AF=0.1685   ES:SE:LP:AF:ID  -0.00509732:0.0113023:0.185686:0.1685:rs891281851
1   1030565 rs6687776   C   T   .   PASS    AF=0.1684   ES:SE:LP:AF:ID  -0.0023476:0.0112865:0.0782095:0.1684:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.1683   ES:SE:LP:AF:ID  -0.002292:0.0112907:0.0759793:0.1683:rs6678318
1   1031973 rs9651270   C   T   .   PASS    AF=0.1611   ES:SE:LP:AF:ID  -0.00157431:0.0116615:0.0494891:0.1611:rs9651270
1   1033596 rs6604964   T   C   .   PASS    AF=0.1609   ES:SE:LP:AF:ID  -0.00143532:0.0116692:0.0446972:0.1609:rs6604964
1   1033670 rs1370950991    T   C   .   PASS    AF=0.1608   ES:SE:LP:AF:ID  -0.00244064:0.0116777:0.0787298:0.1608:rs1370950991
1   1033680 rs1370950991    T   A   .   PASS    AF=0.1608   ES:SE:LP:AF:ID  -0.00252213:0.0116765:0.0813407:0.1608:rs1370950991
1   1033994 rs6698368   C   T   .   PASS    AF=0.1609   ES:SE:LP:AF:ID  -0.0025916:0.0116739:0.0839147:0.1609:rs6698368
1   1034200 rs77977351  T   C   .   PASS    AF=0.1609   ES:SE:LP:AF:ID  -0.00214806:0.0116742:0.0685421:0.1609:rs77977351
1   1036601 rs72910156  C   T   .   PASS    AF=0.0242   ES:SE:LP:AF:ID  0.0654638:0.0285868:1.65758:0.0242:rs72910156
1   1036860 rs11579922  A   C   .   PASS    AF=0.1304   ES:SE:LP:AF:ID  -0.017295:0.0126796:0.762959:0.1304:rs11579922
1   1036959 rs1162868282    T   C   .   PASS    AF=0.1169   ES:SE:LP:AF:ID  -0.026296:0.0131546:1.34046:0.1169:rs1162868282
1   1037303 rs11260592  T   C   .   PASS    AF=0.1432   ES:SE:LP:AF:ID  -0.00978826:0.0120545:0.37976:0.1432:rs11260592
1   1037313 rs11260593  A   G   .   PASS    AF=0.1474   ES:SE:LP:AF:ID  -0.00804109:0.0118426:0.303818:0.1474:rs11260593
1   1037367 rs11260594  G   A   .   PASS    AF=0.1432   ES:SE:LP:AF:ID  -0.00977758:0.0120562:0.37976:0.1432:rs11260594
1   1038088 rs66622470  G   C   .   PASS    AF=0.1433   ES:SE:LP:AF:ID  -0.0101104:0.0120506:0.396314:0.1433:rs66622470
1   1039098 rs11260595  C   A   .   PASS    AF=0.0246   ES:SE:LP:AF:ID  0.0622853:0.0283502:1.55284:0.0246:rs11260595
1   1039268 rs9329410   T   C   .   PASS    AF=0.1434   ES:SE:LP:AF:ID  -0.0106113:0.0120446:0.421934:0.1434:rs9329410
1   1039817 rs1205065516    A   G   .   PASS    AF=0.1433   ES:SE:LP:AF:ID  -0.0111339:0.0120497:0.449283:0.1433:rs1205065516
1   1040026 rs6671356   T   C   .   PASS    AF=0.1437   ES:SE:LP:AF:ID  -0.0108017:0.0120287:0.433091:0.1437:rs6671356
1   1040472 rs6664124   C   T   .   PASS    AF=0.1435   ES:SE:LP:AF:ID  -0.0116281:0.0120373:0.476384:0.1435:rs6664124
1   1040794 rs6687681   G   A   .   PASS    AF=0.1435   ES:SE:LP:AF:ID  -0.0119178:0.0120382:0.492144:0.1435:rs6687681
1   1040824 rs6656379   T   C   .   PASS    AF=0.1478   ES:SE:LP:AF:ID  -0.010013:0.0118217:0.4011:0.1478:rs6656379
1   1040985 rs6697379   C   G   .   PASS    AF=0.1435   ES:SE:LP:AF:ID  -0.0116768:0.0120379:0.478862:0.1435:rs6697379
1   1041700 rs6604968   A   G   .   PASS    AF=0.1436   ES:SE:LP:AF:ID  -0.0120871:0.012039:0.501001:0.1436:rs6604968
1   1041786 rs6604969   T   C   .   PASS    AF=0.1436   ES:SE:LP:AF:ID  -0.0130651:0.0120415:0.556268:0.1436:rs6604969
1   1042483 rs12733365  C   T   .   PASS    AF=0.1435   ES:SE:LP:AF:ID  -0.0125691:0.0120394:0.528122:0.1435:rs12733365
1   1042527 rs1486993720    G   C   .   PASS    AF=0.1158   ES:SE:LP:AF:ID  -0.0251581:0.0132202:1.24397:0.1158:rs1486993720
1   1042673 rs897825316 C   T   .   PASS    AF=0.1445   ES:SE:LP:AF:ID  -0.0130381:0.0120723:0.552687:0.1445:rs897825316
1   1042927 rs4970354   G   T   .   PASS    AF=0.1435   ES:SE:LP:AF:ID  -0.0125672:0.0120376:0.527975:0.1435:rs4970354
1   1043053 rs4970355   A   G   .   PASS    AF=0.1434   ES:SE:LP:AF:ID  -0.0122709:0.0120421:0.510886:0.1434:rs4970355
1   1045473 rs11586034  G   A   .   PASS    AF=0.1153   ES:SE:LP:AF:ID  -0.0260186:0.0132478:1.30487:0.1153:rs11586034
1   1046073 rs11590188  C   A   .   PASS    AF=0.1418   ES:SE:LP:AF:ID  -0.0128713:0.0121085:0.540758:0.1418:rs11590188
1   1046164 rs386627439 C   T   .   PASS    AF=0.1434   ES:SE:LP:AF:ID  -0.0125237:0.012042:0.525056:0.1434:rs386627439
1   1046717 rs34820586  G   C   .   PASS    AF=0.1162   ES:SE:LP:AF:ID  -0.0267244:0.0131972:1.36785:0.1162:rs34820586
1   1046861 rs12723165  G   A   .   PASS    AF=0.1162   ES:SE:LP:AF:ID  -0.0271588:0.0131967:1.4022:0.1162:rs12723165
1   1047374 rs12743678  T   A   .   PASS    AF=0.147    ES:SE:LP:AF:ID  -0.0109789:0.0118562:0.450506:0.147:rs12743678
1   1048501 rs7518814   G   A   .   PASS    AF=0.1418   ES:SE:LP:AF:ID  -0.0128105:0.0121082:0.537752:0.1418:rs7518814
1   1048955 rs4970405   A   G   .   PASS    AF=0.1057   ES:SE:LP:AF:ID  -0.034906:0.0137534:1.9535:0.1057:rs4970405
1   1048989 rs4970406   A   G   .   PASS    AF=0.1179   ES:SE:LP:AF:ID  -0.0226921:0.0132084:1.06697:0.1179:rs4970406
1   1049083 rs4970407   C   A   .   PASS    AF=0.117    ES:SE:LP:AF:ID  -0.0236713:0.013239:1.1323:0.117:rs4970407
1   1049950 rs12726255  A   G   .   PASS    AF=0.1468   ES:SE:LP:AF:ID  -0.005082:0.0118738:0.174899:0.1468:rs12726255
1   1052946 rs12755848  G   T   .   PASS    AF=0.1153   ES:SE:LP:AF:ID  -0.0239559:0.013272:1.14783:0.1153:rs12755848
1   1053452 rs4970409   G   A   .   PASS    AF=0.1152   ES:SE:LP:AF:ID  -0.024132:0.0132739:1.1604:0.1152:rs4970409
1   1053670 rs4970410   G   A   .   PASS    AF=0.1414   ES:SE:LP:AF:ID  -0.00462848:0.0121482:0.152859:0.1414:rs4970410
1   1053724 rs4970411   A   G   .   PASS    AF=0.141    ES:SE:LP:AF:ID  -0.00500123:0.0121685:0.166789:0.141:rs4970411
1   1054552 rs12567697  G   A   .   PASS    AF=0.1143   ES:SE:LP:AF:ID  -0.0237692:0.0133236:1.12808:0.1143:rs12567697
1   1054893 rs4970412   T   C   .   PASS    AF=0.1453   ES:SE:LP:AF:ID  -0.00432446:0.011946:0.14442:0.1453:rs4970412
1   1055653 rs34808604  C   G   .   PASS    AF=0.1145   ES:SE:LP:AF:ID  -0.0238627:0.0133163:1.13632:0.1145:rs34808604
1   1055797 rs76744376  A   G   .   PASS    AF=0.1157   ES:SE:LP:AF:ID  -0.0216763:0.0133393:0.982132:0.1157:rs76744376