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/86a68996-12f5-43f8-bffa-e2b681f7cafe/call-ldsc/inputs/-261021448/ieu-b-5120.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5120/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Jan 20 16:43:00 2024
Reading summary statistics from /data/cromwell-executions/qc/86a68996-12f5-43f8-bffa-e2b681f7cafe/call-ldsc/inputs/-261021448/ieu-b-5120.vcf.gz ...
Read summary statistics for 0 SNPs.
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.
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
    sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
  File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
    raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.

Analysis finished at Sat Jan 20 16:44:16 2024
Total time elapsed: 1.0m:15.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9506,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0.0013,
    "n": "-Inf",
    "n_snps": 11469218,
    "n_clumped_hits": 4,
    "n_p_sig": 194,
    "n_mono": 0,
    "n_ns": 529292,
    "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": 693417,
    "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": 0,
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

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 NA
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 586 0.9999489 3 58 0 11443864 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 4 0 340 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 4 0 340 0 NA NA NA NA NA NA NA NA NA NA
logical N 11469218 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 8.630471e+00 5.755513e+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 7.864496e+07 5.630108e+07 302.0000000 3.246429e+07 6.907161e+07 1.143027e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.255000e-03 2.655216e-01 -4.2854100 -7.851240e-02 8.013000e-04 8.056630e-02 4.239160e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.906384e-01 1.836282e-01 0.0540247 6.578190e-02 1.075750e-01 2.489280e-01 2.850830e+00 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.927492e-01 2.902914e-01 0.0000000 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 4.927499e-01 2.902678e-01 0.0000000 2.396809e-01 4.902065e-01 7.438615e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.258798e-01 2.758327e-01 0.0004370 1.447300e-02 9.182500e-02 3.638730e-01 9.994900e-01 ▇▂▁▁▁
numeric AF_reference 693417 0.9395410 NA NA NA NA NA NA NA 2.098983e-01 2.494755e-01 0.0000000 1.178120e-02 1.028350e-01 3.296730e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs1264289758 AC A -0.0884710 0.0838036 0.2900000 0.2911078 0.599372 NA NA
1 10352 rs1557426776 TA T 0.0515122 0.0861089 0.5500004 0.5496921 0.605168 NA NA
1 11008 rs575272151 C G 0.0099795 0.1446500 0.9400001 0.9449972 0.085849 0.0880591 NA
1 11012 rs544419019 C G 0.0099795 0.1446500 0.9400001 0.9449972 0.085849 0.0880591 NA
1 13110 rs540538026 G A -0.0131814 0.1932380 0.9500000 0.9456158 0.057902 0.0267572 NA
1 13116 rs62635286 T G -0.0932537 0.1132970 0.4100001 0.4104565 0.188683 0.0970447 NA
1 13118 rs200579949 A G -0.0932537 0.1132970 0.4100001 0.4104565 0.188683 0.0970447 NA
1 13273 rs531730856 G C 0.0188337 0.1313450 0.8900000 0.8859813 0.134780 0.0950479 NA
1 14464 rs546169444 A T 0.0664099 0.1182890 0.5700002 0.5745107 0.158811 0.0958466 NA
1 14599 rs531646671 T A 0.1684410 0.1104720 0.1299999 0.1273241 0.189004 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233182 rs4040317 G A 0.0135107 0.0685722 0.8400000 0.8438050 0.319952 0.2633790 NA
22 51233300 rs9616839 C T 0.0691541 0.0685282 0.3100002 0.3129106 0.332137 0.3146960 NA
22 51233312 rs62240043 A G 0.0575636 0.0721922 0.4299995 0.4252385 0.271944 0.2134580 NA
22 51233347 rs62240044 T C 0.0575636 0.0721922 0.4299995 0.4252385 0.271944 0.2134580 NA
22 51234799 rs191117135 G A -0.0078713 0.2516130 0.9800000 0.9750436 0.015907 0.0059904 NA
22 51235959 rs200189535 T C 0.0330833 0.0842720 0.6899999 0.6946315 0.193482 0.1996810 NA
22 51235979 rs62240045 G A -0.2114070 0.0933089 0.0230001 0.0234717 0.262466 0.2400160 NA
22 51236013 rs200507571 AT A 0.1292510 0.0715456 0.0710003 0.0708318 0.746643 NA NA
22 51237063 rs3896457 T C 0.0076064 0.0663393 0.9100000 0.9087155 0.296915 0.2050720 NA
22 51237712 rs370652263 G A -0.0834275 0.1319120 0.5300002 0.5270941 0.055881 0.0690895 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.599372 ES:SE:LP:AF:SI:ID   -0.088471:0.0838036:0.537602:0.599372:0.466089:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.605168 ES:SE:LP:AF:SI:ID   0.0515122:0.0861089:0.259637:0.605168:0.44449:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.085849 ES:SE:LP:AF:SI:ID   0.00997948:0.14465:0.0268721:0.085849:0.486664:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.085849 ES:SE:LP:AF:SI:ID   0.00997948:0.14465:0.0268721:0.085849:0.486664:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.057902 ES:SE:LP:AF:SI:ID   -0.0131814:0.193238:0.0222764:0.057902:0.39209:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.188683 ES:SE:LP:AF:SI:ID   -0.0932537:0.113297:0.387216:0.188683:0.404681:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.188683 ES:SE:LP:AF:SI:ID   -0.0932537:0.113297:0.387216:0.188683:0.404681:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13478  ES:SE:LP:AF:SI:ID   0.0188337:0.131345:0.05061:0.13478:0.390731:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.158811 ES:SE:LP:AF:SI:ID   0.0664099:0.118289:0.244125:0.158811:0.410824:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.189004 ES:SE:LP:AF:SI:ID   0.168441:0.110472:0.886057:0.189004:0.424479:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.189004 ES:SE:LP:AF:SI:ID   0.168441:0.110472:0.886057:0.189004:0.424479:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473772 ES:SE:LP:AF:SI:ID   0.0288204:0.0851758:0.130768:0.473772:0.437191:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045604 ES:SE:LP:AF:SI:ID   -0.13417:0.207927:0.283997:0.045604:0.420325:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.740878 ES:SE:LP:AF:SI:ID   0.041232:0.0980204:0.173925:0.740878:0.425958:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275163 ES:SE:LP:AF:SI:ID   0.161285:0.100507:0.958607:0.275163:0.388846:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.582205 ES:SE:LP:AF:SI:ID   -0.0754426:0.083269:0.443698:0.582205:0.465698:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956378 ES:SE:LP:AF:SI:ID   -0.00110409:0.234828:-0:0.956378:0.339465:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.911649 ES:SE:LP:AF:SI:ID   -0.0095108:0.159818:0.0222764:0.911649:0.391908:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.063571 ES:SE:LP:AF:SI:ID   0.192476:0.176798:0.552842:0.063571:0.418452:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.624872 ES:SE:LP:AF:SI:ID   0.0889182:0.0997633:0.431798:0.624872:0.338912:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092998 ES:SE:LP:AF:SI:ID   -0.223144:0.151798:0.853872:0.092998:0.397311:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.215563 ES:SE:LP:AF:SI:ID   0.108013:0.105426:0.508638:0.215563:0.412646:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.156744 ES:SE:LP:AF:SI:ID   0.0808818:0.117923:0.309804:0.156744:0.420773:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.4006   ES:SE:LP:AF:SI:ID   0.0878328:0.0980529:0.431798:0.4006:0.337096:rs2462492
1   54712   rs573184866 TTTT    T   .   PASS    AF=0.414658 ES:SE:LP:AF:SI:ID   -0.072588:0.0780692:0.455932:0.414658:0.532876:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.416571 ES:SE:LP:AF:SI:ID   0.039097:0.0901376:0.180456:0.416571:0.39825:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253256 ES:SE:LP:AF:SI:ID   0.0181095:0.101265:0.0655015:0.253256:0.404049:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090329 ES:SE:LP:AF:SI:ID   -0.264126:0.153061:1.07572:0.090329:0.402912:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088868 ES:SE:LP:AF:SI:ID   -0.194698:0.15399:0.677781:0.088868:0.404541:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081044 ES:SE:LP:AF:SI:ID   -0.223832:0.159654:0.79588:0.081044:0.408796:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.441239 ES:SE:LP:AF:SI:ID   -0.0165898:0.0860566:0.0705811:0.441239:0.435397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381609 ES:SE:LP:AF:SI:ID   -0.0164503:0.0919905:0.0655015:0.381609:0.39221:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.1601   ES:SE:LP:AF:SI:ID   -0.0600905:0.116713:0.21467:0.1601:0.429054:rs80011619
1   64931   rs62639104  G   A   .   PASS    AF=0.07983  ES:SE:LP:AF:SI:ID   -0.256684:0.161012:0.958607:0.07983:0.405239:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070063 ES:SE:LP:AF:SI:ID   0.161671:0.165774:0.481486:0.070063:0.439754:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032814 ES:SE:LP:AF:SI:ID   0.165933:0.249625:0.29243:0.032814:0.39852:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073002 ES:SE:LP:AF:SI:ID   0.197153:0.16353:0.638272:0.073002:0.436196:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.750677 ES:SE:LP:AF:SI:ID   0.0700293:0.102941:0.30103:0.750677:0.393859:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034149 ES:SE:LP:AF:SI:ID   -0.0315765:0.238626:0.05061:0.034149:0.425973:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034149 ES:SE:LP:AF:SI:ID   -0.0315765:0.238626:0.05061:0.034149:0.425973:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077498 ES:SE:LP:AF:SI:ID   -0.229016:0.164864:0.79588:0.077498:0.401276:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.078661 ES:SE:LP:AF:SI:ID   0.223066:0.157389:0.79588:0.078661:0.430178:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077327 ES:SE:LP:AF:SI:ID   -0.2314:0.164849:0.79588:0.077327:0.40201:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077327 ES:SE:LP:AF:SI:ID   -0.2314:0.164849:0.79588:0.077327:0.40201:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041393 ES:SE:LP:AF:SI:ID   0.0234418:0.233252:0.0362122:0.041393:0.370765:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.059778 ES:SE:LP:AF:SI:ID   0.266842:0.177624:0.886057:0.059778:0.444727:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.076535 ES:SE:LP:AF:SI:ID   0.245681:0.159786:0.920819:0.076535:0.429704:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.076589 ES:SE:LP:AF:SI:ID   0.242075:0.159727:0.886057:0.076589:0.429781:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.35264  ES:SE:LP:AF:SI:ID   -0.00617708:0.0924057:0.0222764:0.35264:0.399395:rs201754587
1   86028   rs114608975 T   C   .   PASS    AF=0.10225  ES:SE:LP:AF:SI:ID   -0.140547:0.158985:0.420216:0.10225:0.340979:rs114608975