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/27a4e1f2-42d4-4f12-bb6f-c5acd2609da5/call-ldsc/inputs/-261044355/ieu-b-4872.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4872/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Mon Jan 10 04:45:42 2022
Reading summary statistics from /data/cromwell-executions/qc/27a4e1f2-42d4-4f12-bb6f-c5acd2609da5/call-ldsc/inputs/-261044355/ieu-b-4872.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 Mon Jan 10 04:47:03 2022
Total time elapsed: 1.0m:21.18s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9505,
    "inflation_factor": 1,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 1,
    "n_p_sig": 41,
    "n_mono": 0,
    "n_ns": 1293897,
    "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": 1423040,
    "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 675 0.9999452 3 58 0 12276232 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 17566 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 71704 0 NA NA NA NA NA NA NA NA NA NA
logical N 12321875 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 8.757492e+00 5.885387e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.871202e+07 5.622121e+07 302.000000 3.252510e+07 6.928045e+07 1.144492e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.262000e-04 2.794110e-02 -0.446739 -8.333000e-03 3.790000e-05 8.460900e-03 4.852210e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.027450e-02 1.938930e-02 0.005883 7.119100e-03 1.142030e-02 2.633620e-02 3.052980e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.979823e-01 2.892638e-01 0.000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.979829e-01 2.892378e-01 0.000000 2.471526e-01 4.973020e-01 7.484621e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594061e-01 3.020050e-01 0.000672 1.661600e-02 1.146180e-01 4.378810e-01 9.992620e-01 ▇▂▁▁▁
numeric AF_reference 1423040 0.8845111 NA NA NA NA NA NA NA 2.132160e-01 2.513550e-01 0.000000 1.218050e-02 1.056310e-01 3.376600e-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 0.0173726 0.0091196 0.0569994 0.0567845 0.601197 NA NA
1 10352 rs1557426776 TA T -0.0040561 0.0093599 0.6600001 0.6647586 0.606480 NA NA
1 11008 rs575272151 C G -0.0214174 0.0156731 0.1700000 0.1717799 0.085432 0.0880591 NA
1 11012 rs544419019 C G -0.0214174 0.0156731 0.1700000 0.1717799 0.085432 0.0880591 NA
1 13110 rs540538026 G A 0.0035307 0.0211301 0.8700001 0.8672962 0.057702 0.0267572 NA
1 13116 rs62635286 T G -0.0028858 0.0122460 0.8100000 0.8137017 0.189244 0.0970447 NA
1 13118 rs200579949 A G -0.0028858 0.0122460 0.8100000 0.8137017 0.189244 0.0970447 NA
1 13273 rs531730856 G C -0.0058558 0.0142987 0.6800001 0.6821485 0.134721 0.0950479 NA
1 14464 rs546169444 A T 0.0143776 0.0130409 0.2700001 0.2702441 0.157423 0.0958466 NA
1 14599 rs531646671 T A -0.0008122 0.0119529 0.9500000 0.9458277 0.190826 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0052043 0.0070556 0.4600002 0.4607543 0.751205 0.643179 NA
23 154901964 rs697726 G A 0.0047185 0.0074535 0.5300002 0.5266941 0.346650 0.117616 NA
23 154902105 rs696316 G T 0.0050888 0.0070553 0.4700002 0.4707432 0.751124 0.636026 NA
23 154902889 rs697725 A T 0.0046324 0.0070543 0.5099998 0.5113847 0.750679 0.584106 NA
23 154903118 rs479770 G A 0.0050664 0.0070569 0.4700002 0.4727936 0.751241 0.643444 NA
23 154903224 rs480725 A T 0.0050678 0.0070569 0.4700002 0.4726751 0.751244 0.643444 NA
23 154903937 rs674707 G A 0.0050850 0.0070571 0.4700002 0.4711877 0.751255 0.643444 NA
23 154909055 rs473529 C G -0.0004247 0.0066654 0.9500000 0.9491990 0.305682 0.463046 NA
23 154918266 rs642043 C T 0.0003130 0.0066887 0.9599999 0.9626795 0.303653 0.478675 NA
23 154927581 rs644138 G A 0.0001767 0.0066902 0.9800000 0.9789334 0.303454 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601197 ES:SE:LP:AF:ID  0.0173726:0.00911964:1.24413:0.601197:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.60648  ES:SE:LP:AF:ID  -0.00405615:0.00935993:0.180456:0.60648:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.085432 ES:SE:LP:AF:ID  -0.0214174:0.0156731:0.769551:0.085432:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.085432 ES:SE:LP:AF:ID  -0.0214174:0.0156731:0.769551:0.085432:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.057702 ES:SE:LP:AF:ID  0.00353071:0.0211301:0.0604807:0.057702:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189244 ES:SE:LP:AF:ID  -0.00288581:0.012246:0.091515:0.189244:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189244 ES:SE:LP:AF:ID  -0.00288581:0.012246:0.091515:0.189244:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134721 ES:SE:LP:AF:ID  -0.00585579:0.0142987:0.167491:0.134721:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157423 ES:SE:LP:AF:ID  0.0143776:0.0130409:0.568636:0.157423:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.190826 ES:SE:LP:AF:ID  -0.000812165:0.0119529:0.0222764:0.190826:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.190826 ES:SE:LP:AF:ID  -0.000812165:0.0119529:0.0222764:0.190826:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474859 ES:SE:LP:AF:ID  -0.00773444:0.00923922:0.39794:0.474859:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045074 ES:SE:LP:AF:ID  0.00590106:0.0227931:0.09691:0.045074:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.740337 ES:SE:LP:AF:ID  -0.00547277:0.0106732:0.21467:0.740337:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275997 ES:SE:LP:AF:ID  0.012624:0.0109421:0.60206:0.275997:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.582021 ES:SE:LP:AF:ID  -0.00212814:0.00904579:0.091515:0.582021:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956148 ES:SE:LP:AF:ID  0.00655441:0.025568:0.09691:0.956148:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.909255 ES:SE:LP:AF:ID  0.00293617:0.0169258:0.0655015:0.909255:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.06264  ES:SE:LP:AF:ID  -0.0115911:0.0195287:0.259637:0.06264:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.622722 ES:SE:LP:AF:ID  0.00578988:0.0108768:0.229148:0.622722:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.09269  ES:SE:LP:AF:ID  0.012746:0.0167226:0.346787:0.09269:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213695 ES:SE:LP:AF:ID  -0.0101533:0.0116126:0.420216:0.213695:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154424 ES:SE:LP:AF:ID  -0.0054695:0.0130484:0.167491:0.154424:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.401029 ES:SE:LP:AF:ID  -0.0128353:0.0108325:0.619789:0.401029:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.415243 ES:SE:LP:AF:ID  0.00040738:0.00850983:0.0177288:0.415243:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417456 ES:SE:LP:AF:ID  -0.0179295:0.00983991:1.16749:0.417456:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253339 ES:SE:LP:AF:ID  0.0169807:0.0110377:0.920819:0.253339:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089965 ES:SE:LP:AF:ID  0.013829:0.0168121:0.387216:0.089965:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088467 ES:SE:LP:AF:ID  0.0219174:0.0169322:0.69897:0.088467:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080643 ES:SE:LP:AF:ID  0.0158092:0.0175726:0.431798:0.080643:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438545 ES:SE:LP:AF:ID  0.0151048:0.00931857:0.958607:0.438545:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381813 ES:SE:LP:AF:ID  0.0205416:0.0100162:1.39794:0.381813:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158797 ES:SE:LP:AF:ID  0.0176265:0.0127896:0.769551:0.158797:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684071 ES:SE:LP:AF:ID  -0.0136698:0.00992251:0.769551:0.684071:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079204 ES:SE:LP:AF:ID  0.0149451:0.0178053:0.39794:0.079204:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.071062 ES:SE:LP:AF:ID  -0.0284491:0.0179613:0.958607:0.071062:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.033261 ES:SE:LP:AF:ID  -0.00697895:0.0268321:0.102373:0.033261:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.07428  ES:SE:LP:AF:ID  -0.0254677:0.017644:0.823909:0.07428:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751277 ES:SE:LP:AF:ID  -0.0160928:0.0112439:0.823909:0.751277:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.033727 ES:SE:LP:AF:ID  -0.00358035:0.0260796:0.05061:0.033727:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.033727 ES:SE:LP:AF:ID  -0.00358035:0.0260796:0.05061:0.033727:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.076835 ES:SE:LP:AF:ID  0.0297889:0.0181299:1:0.076835:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077483 ES:SE:LP:AF:ID  -0.012025:0.0174234:0.309804:0.077483:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076654 ES:SE:LP:AF:ID  0.0295295:0.0181339:1:0.076654:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076654 ES:SE:LP:AF:ID  0.0295295:0.0181339:1:0.076654:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041304 ES:SE:LP:AF:ID  -0.0501353:0.025413:1.3098:0.041304:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.061263 ES:SE:LP:AF:ID  -0.0225851:0.0190749:0.619789:0.061263:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075559 ES:SE:LP:AF:ID  -0.0132422:0.0176409:0.346787:0.075559:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075577 ES:SE:LP:AF:ID  -0.0125371:0.0176367:0.318759:0.075577:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352389 ES:SE:LP:AF:ID  0.00954333:0.0100908:0.468521:0.352389:rs201754587