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/6952ac16-a2b7-474a-9b39-a8a059dfb92e/call-ldsc/inputs/-261021473/ieu-b-5116.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5116/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Feb 15 20:41:59 2024
Reading summary statistics from /data/cromwell-executions/qc/6952ac16-a2b7-474a-9b39-a8a059dfb92e/call-ldsc/inputs/-261021473/ieu-b-5116.vcf.gz ...
Read summary statistics for 8553452 SNPs.
Dropped 93162 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
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] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1212321 SNPs remain.
After merging with regression SNP LD, 1212321 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0737 (0.0329)
Lambda GC: 1.1613
Mean Chi^2: 1.2003
Intercept: 1.161 (0.0086)
Ratio: 0.804 (0.0427)
Analysis finished at Thu Feb 15 20:43:42 2024
Total time elapsed: 1.0m:43.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9409,
    "inflation_factor": 1.0528,
    "mean_EFFECT": 0.0027,
    "n": "-Inf",
    "n_snps": 8553715,
    "n_clumped_hits": 18,
    "n_p_sig": 11276,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 94200,
    "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": 1212321,
    "ldsc_nsnp_merge_regression_ld": 1212321,
    "ldsc_observed_scale_h2_beta": 0.0737,
    "ldsc_observed_scale_h2_se": 0.0329,
    "ldsc_intercept_beta": 1.161,
    "ldsc_intercept_se": 0.0086,
    "ldsc_lambda_gc": 1.1613,
    "ldsc_mean_chisq": 1.2003,
    "ldsc_ratio": 0.8038
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig TRUE
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 12 0.9999986 3 58 0 8551367 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 8553715 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 8.671355e+00 5.769538e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.836698e+07 5.650017e+07 828.000000 3.195369e+07 6.860901e+07 1.141774e+08 2.492331e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.685100e-03 7.737070e-02 -1.709810 -3.114910e-02 3.070000e-04 3.232780e-02 4.849570e+00 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.678080e-02 4.531420e-02 0.016707 2.818300e-02 4.140500e-02 7.044900e-02 4.151240e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.910069e-01 2.920999e-01 0.000000 2.357350e-01 4.888932e-01 7.445159e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.738370e-01 2.953835e-01 0.000000 2.125578e-01 4.645605e-01 7.293926e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.567790e-01 2.614372e-01 0.009516 4.220200e-02 1.524600e-01 4.079100e-01 9.903350e-01 ▇▂▂▁▁
numeric AF_reference 94200 0.9889872 NA NA NA NA NA NA NA 2.565000e-01 2.528700e-01 0.000000 4.732430e-02 1.683310e-01 4.035540e-01 1.000000e+00 ▇▃▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 125271 rs377100675 C T 0.1712360 0.202339 0.4092663 0.3973950 0.960103 0.7767570 NA
1 536095 rs189259765 C T -0.0821878 0.078731 0.3796496 0.2965287 0.270993 0.3981630 NA
1 546697 rs12025928 A G 0.1144010 0.137462 0.4145816 0.4052750 0.912822 NA NA
1 567807 rs2853819 T C -0.0829741 0.084234 0.4107296 0.3246030 0.200555 0.1998800 NA
1 618386 rs202025951 T C -0.0705823 0.129329 0.6630450 0.5852325 0.069142 0.1890970 NA
1 636285 rs545945172 T C -0.2803030 0.076827 0.0134651 0.0002638 0.101139 0.0956470 NA
1 649192 rs201942322 A T -0.2385730 0.073022 0.0197188 0.0010864 0.123277 0.1369810 NA
1 662414 rs371628865 C T -0.2170420 0.072909 0.0295427 0.0029119 0.141412 0.1745210 NA
1 662622 rs61769339 G A -0.2412320 0.072724 0.0182079 0.0009096 0.116353 0.1475640 NA
1 665266 rs539032812 T C 0.0051517 0.197307 0.9834050 0.9791695 0.021077 0.0065895 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233312 rs62240043 A G 0.1007840 0.075306 0.1678421 0.1807901 0.273052 0.2134580 NA
22 51233347 rs62240044 T C 0.1007840 0.075306 0.1678421 0.1807901 0.273052 0.2134580 NA
22 51233666 rs11091014 C T -0.0445498 0.199569 0.8681131 0.8233565 0.019671 0.0970447 NA
22 51234343 rs374867791 G T -0.0636269 0.194717 0.8112040 0.7438449 0.019980 0.1002400 NA
22 51234799 rs191117135 G A -0.0530949 0.178300 0.8208971 0.7658680 0.019853 0.0059904 NA
22 51235959 rs200189535 T C -0.0364628 0.077272 0.6758013 0.6370153 0.191746 0.1996810 NA
22 51237063 rs3896457 T C 0.0842860 0.068407 0.2090730 0.2179023 0.297892 0.2050720 NA
22 51237364 rs200607599 A G 0.3425910 0.333691 0.2820369 0.3045752 0.016184 0.0187700 NA
22 51237712 rs370652263 G A 0.0204759 0.124758 0.8834741 0.8696328 0.054650 0.0690895 NA
22 51240820 rs202228854 C T -0.1713380 0.159157 0.4677190 0.2816883 0.027384 0.1267970 NA

bcf preview

1   125271  rs3871807   C   T   .   PASS    AF=0.960103 ES:SE:LP:AF:ID  0.171236:0.202339:0.387994:0.960103:rs3871807
1   536095  rs189259765 C   T   .   PASS    AF=0.270993 ES:SE:LP:AF:ID  -0.0821878:0.078731:0.420617:0.270993:rs189259765
1   546697  rs12025928  A   G   .   PASS    AF=0.912822 ES:SE:LP:AF:ID  0.114401:0.137462:0.38239:0.912822:rs12025928
1   567807  rs2853819   T   C   .   PASS    AF=0.200555 ES:SE:LP:AF:ID  -0.0829741:0.084234:0.386444:0.200555:rs2853819
1   618386  rs202025951 T   C   .   PASS    AF=0.069142 ES:SE:LP:AF:ID  -0.0705823:0.129329:0.178457:0.069142:rs202025951
1   636285  rs545945172 T   C   .   PASS    AF=0.101139 ES:SE:LP:AF:ID  -0.280303:0.076827:1.87079:0.101139:rs545945172
1   649192  rs201942322 A   T   .   PASS    AF=0.123277 ES:SE:LP:AF:ID  -0.238573:0.073022:1.70512:0.123277:rs201942322
1   662414  rs371628865 C   T   .   PASS    AF=0.141412 ES:SE:LP:AF:ID  -0.217042:0.072909:1.52955:0.141412:rs371628865
1   662622  rs61769339  G   A   .   PASS    AF=0.116353 ES:SE:LP:AF:ID  -0.241232:0.072724:1.73974:0.116353:rs61769339
1   665266  rs539032812 T   C   .   PASS    AF=0.021077 ES:SE:LP:AF:ID  0.00515171:0.197307:0.00726759:0.021077:rs539032812
1   691544  rs201222573 T   A   .   PASS    AF=0.628719 ES:SE:LP:AF:ID  0.204668:0.09166:1.94727:0.628719:rs201222573
1   693731  rs12238997  A   G   .   PASS    AF=0.123697 ES:SE:LP:AF:ID  -0.21268:0.069109:1.63746:0.123697:rs12238997
1   693823  rs61769351  G   C   .   PASS    AF=0.118169 ES:SE:LP:AF:ID  -0.23199:0.072915:1.65447:0.118169:rs61769351
1   701835  rs189800799 T   C   .   PASS    AF=0.030585 ES:SE:LP:AF:ID  -0.148802:0.14667:0.32569:0.030585:rs189800799
1   705882  rs72631875  G   A   .   PASS    AF=0.066858 ES:SE:LP:AF:ID  0.0835348:0.135427:0.252865:0.066858:rs72631875
1   706368  rs963699400 A   G   .   PASS    AF=0.512427 ES:SE:LP:AF:ID  0.0682323:0.07196:0.463722:0.512427:rs963699400
1   706778  rs1201760444    G   A   .   PASS    AF=0.739313 ES:SE:LP:AF:ID  0.198667:0.090206:1.88887:0.739313:rs1201760444
1   707522  rs371890604 G   C   .   PASS    AF=0.104914 ES:SE:LP:AF:ID  -0.219247:0.076736:1.41737:0.104914:rs371890604
1   711310  rs200531508 G   A   .   PASS    AF=0.045897 ES:SE:LP:AF:ID  -0.207831:0.111482:0.713229:0.045897:rs200531508
1   712547  rs373285923 G   C   .   PASS    AF=0.025899 ES:SE:LP:AF:ID  -0.107932:0.168736:0.190252:0.025899:rs373285923
1   712762  rs1320856380    T   G   .   PASS    AF=0.03485  ES:SE:LP:AF:ID  -0.0598275:0.152842:0.119557:0.03485:rs1320856380
1   713914  rs570631764 A   G   .   PASS    AF=0.034336 ES:SE:LP:AF:ID  -0.0572616:0.153804:0.113294:0.034336:rs570631764
1   714019  rs114983708 A   G   .   PASS    AF=0.036036 ES:SE:LP:AF:ID  -0.069453:0.147812:0.146107:0.036036:rs114983708
1   714310  rs141232927 C   G   .   PASS    AF=0.025792 ES:SE:LP:AF:ID  -0.114604:0.172451:0.195606:0.025792:rs141232927
1   714427  rs12028261  G   A   .   PASS    AF=0.960046 ES:SE:LP:AF:ID  0.0802058:0.171258:0.172896:0.960046:rs12028261
1   714596  rs149887893 T   C   .   PASS    AF=0.030504 ES:SE:LP:AF:ID  -0.0905836:0.141866:0.204258:0.030504:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.033234 ES:SE:LP:AF:ID  -0.046244:0.138298:0.104545:0.033234:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03327  ES:SE:LP:AF:ID  -0.0481897:0.137872:0.10958:0.03327:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.033267 ES:SE:LP:AF:ID  -0.0537658:0.137349:0.123489:0.033267:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016134 ES:SE:LP:AF:ID  -0.380356:0.132629:0.923749:0.016134:rs144155419
1   719914  rs187772768 C   G   .   PASS    AF=0.034826 ES:SE:LP:AF:ID  -0.0908442:0.142023:0.204552:0.034826:rs187772768
1   720381  rs116801199 G   T   .   PASS    AF=0.033548 ES:SE:LP:AF:ID  -0.0497398:0.137159:0.114039:0.033548:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.033603 ES:SE:LP:AF:ID  -0.0536255:0.13617:0.124571:0.033603:rs12565286
1   721757  rs756475475 T   A   .   PASS    AF=0.034662 ES:SE:LP:AF:ID  -0.0946239:0.141773:0.21403:0.034662:rs756475475
1   722670  rs116030099 T   C   .   PASS    AF=0.095174 ES:SE:LP:AF:ID  -0.00420583:0.108864:0.0120139:0.095174:rs116030099
1   723307  rs28659788  C   G   .   PASS    AF=0.034829 ES:SE:LP:AF:ID  -0.0905179:0.141978:0.203873:0.034829:rs28659788
1   723742  rs200325929 T   C   .   PASS    AF=0.034669 ES:SE:LP:AF:ID  -0.0823484:0.143315:0.182197:0.034669:rs200325929
1   723819  rs11804171  T   A   .   PASS    AF=0.038117 ES:SE:LP:AF:ID  -0.0595271:0.14256:0.130684:0.038117:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.962821 ES:SE:LP:AF:ID  0.0657381:0.149033:0.163168:0.962821:rs2977670
1   724324  rs753164112 G   A   .   PASS    AF=0.034995 ES:SE:LP:AF:ID  -0.0881986:0.141712:0.198922:0.034995:rs753164112
1   725196  rs1315843244    G   A   .   PASS    AF=0.034615 ES:SE:LP:AF:ID  -0.0847913:0.14251:0.189362:0.034615:rs1315843244
1   725389  rs375619475 C   T   .   PASS    AF=0.034441 ES:SE:LP:AF:ID  -0.105314:0.141162:0.240966:0.034441:rs375619475
1   726794  rs28454925  C   G   .   PASS    AF=0.032843 ES:SE:LP:AF:ID  -0.0780286:0.134494:0.188091:0.032843:rs28454925
1   726944  rs1557542741    C   G   .   PASS    AF=0.781119 ES:SE:LP:AF:ID  0.061555:0.09375:0.280032:0.781119:rs1557542741
1   727841  rs116587930 G   A   .   PASS    AF=0.05753  ES:SE:LP:AF:ID  -0.150134:0.106701:0.536825:0.05753:rs116587930
1   729632  rs116720794 C   T   .   PASS    AF=0.033205 ES:SE:LP:AF:ID  -0.0461036:0.137504:0.105004:0.033205:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.83995  ES:SE:LP:AF:ID  0.163449:0.089671:1.32326:0.83995:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.059971 ES:SE:LP:AF:ID  -0.115817:0.10434:0.41544:0.059971:rs148120343
1   731453  rs186002080 G   A   .   PASS    AF=0.017452 ES:SE:LP:AF:ID  0.516685:0.36713:1.14915:0.017452:rs186002080
1   731718  rs58276399  T   C   .   PASS    AF=0.129017 ES:SE:LP:AF:ID  -0.205047:0.067137:1.64656:0.129017:rs58276399