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/d62384bd-1073-416b-8c01-a663b3167a9e/call-ldsc/inputs/-261044354/ieu-b-4873.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4873/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Mon Jan 10 04:41:02 2022
Reading summary statistics from /data/cromwell-executions/qc/d62384bd-1073-416b-8c01-a663b3167a9e/call-ldsc/inputs/-261044354/ieu-b-4873.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 04:42:24 2022
Total time elapsed: 1.0m:21.93s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9502,
    "inflation_factor": 1,
    "mean_EFFECT": -0.0002,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 2,
    "n_p_sig": 379,
    "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 1.0000000 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+07 302.0000000 3.252510e+07 6.928045e+07 1.144492e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.720000e-04 5.013960e-02 -0.8641880 -1.489120e-02 -2.500000e-05 1.472380e-02 1.406890e+00 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.606720e-02 3.491660e-02 0.0076617 1.259430e-02 2.023210e-02 4.668000e-02 6.902350e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.981701e-01 2.887263e-01 0.0000000 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 4.981694e-01 2.886995e-01 0.0000000 2.477413e-01 4.970369e-01 7.481186e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594005e-01 3.020533e-01 0.0003990 1.658200e-02 1.144970e-01 4.378615e-01 9.995770e-01 ▇▂▁▁▁
numeric AF_reference 1423040 0.8845111 NA NA NA NA NA NA NA 2.132160e-01 2.513550e-01 0.0000000 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 0.0220743 0.0161324 0.1700000 0.1712117 0.599124 NA NA
1 10352 rs1557426776 TA T -0.0119876 0.0166593 0.4700002 0.4717873 0.607470 NA NA
1 11008 rs575272151 C G 0.0209790 0.0272783 0.4400003 0.4418501 0.088641 0.0880591 NA
1 11012 rs544419019 C G 0.0209790 0.0272783 0.4400003 0.4418501 0.088641 0.0880591 NA
1 13110 rs540538026 G A -0.0244399 0.0373231 0.5099998 0.5125839 0.058376 0.0267572 NA
1 13116 rs62635286 T G -0.0064877 0.0217763 0.7700005 0.7657623 0.188494 0.0970447 NA
1 13118 rs200579949 A G -0.0064877 0.0217763 0.7700005 0.7657623 0.188494 0.0970447 NA
1 13273 rs531730856 G C 0.0040488 0.0255008 0.8700001 0.8738474 0.135583 0.0950479 NA
1 14464 rs546169444 A T 0.0298589 0.0233551 0.2000000 0.2010822 0.156562 0.0958466 NA
1 14599 rs531646671 T A -0.0117903 0.0212842 0.5800000 0.5796157 0.189594 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0149131 0.0088662 0.0929994 0.0925663 0.751551 0.643179 NA
23 154901964 rs697726 G A -0.0029061 0.0093487 0.7600007 0.7559079 0.349022 0.117616 NA
23 154902105 rs696316 G T 0.0149135 0.0088662 0.0929994 0.0925568 0.751550 0.636026 NA
23 154902889 rs697725 A T 0.0149005 0.0088613 0.0929994 0.0926620 0.751010 0.584106 NA
23 154903118 rs479770 G A 0.0149076 0.0088665 0.0929994 0.0926969 0.751556 0.643444 NA
23 154903224 rs480725 A T 0.0149065 0.0088665 0.0929994 0.0927217 0.751557 0.643444 NA
23 154903937 rs674707 G A 0.0148980 0.0088666 0.0929994 0.0929128 0.751561 0.643444 NA
23 154909055 rs473529 C G -0.0189218 0.0083449 0.0230001 0.0233614 0.305233 0.463046 NA
23 154918266 rs642043 C T -0.0172474 0.0083719 0.0389996 0.0393839 0.303013 0.478675 NA
23 154927581 rs644138 G A -0.0173425 0.0083742 0.0379997 0.0383629 0.302869 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.599124 ES:SE:LP:AF:ID  0.0220743:0.0161324:0.769551:0.599124:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.60747  ES:SE:LP:AF:ID  -0.0119876:0.0166593:0.327902:0.60747:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.088641 ES:SE:LP:AF:ID  0.020979:0.0272783:0.356547:0.088641:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.088641 ES:SE:LP:AF:ID  0.020979:0.0272783:0.356547:0.088641:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058376 ES:SE:LP:AF:ID  -0.0244399:0.0373231:0.29243:0.058376:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.188494 ES:SE:LP:AF:ID  -0.00648765:0.0217763:0.113509:0.188494:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.188494 ES:SE:LP:AF:ID  -0.00648765:0.0217763:0.113509:0.188494:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.135583 ES:SE:LP:AF:ID  0.00404885:0.0255008:0.0604807:0.135583:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156562 ES:SE:LP:AF:ID  0.0298589:0.0233551:0.69897:0.156562:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.189594 ES:SE:LP:AF:ID  -0.0117903:0.0212842:0.236572:0.189594:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.189594 ES:SE:LP:AF:ID  -0.0117903:0.0212842:0.236572:0.189594:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.472035 ES:SE:LP:AF:ID  0.00838339:0.0164667:0.21467:0.472035:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045447 ES:SE:LP:AF:ID  0.00423866:0.0403509:0.0362122:0.045447:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.73762  ES:SE:LP:AF:ID  0.00683911:0.0188084:0.142668:0.73762:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.273544 ES:SE:LP:AF:ID  0.00727474:0.019447:0.148742:0.273544:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.580619 ES:SE:LP:AF:ID  -0.0132391:0.0160215:0.387216:0.580619:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956322 ES:SE:LP:AF:ID  0.0273224:0.0454731:0.259637:0.956322:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.909708 ES:SE:LP:AF:ID  0.0156875:0.0302718:0.221849:0.909708:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062914 ES:SE:LP:AF:ID  -0.051514:0.0342106:0.886057:0.062914:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.625075 ES:SE:LP:AF:ID  -0.00888518:0.0191257:0.19382:0.625075:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.091892 ES:SE:LP:AF:ID  -0.0357178:0.0296648:0.638272:0.091892:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.214666 ES:SE:LP:AF:ID  -0.00919113:0.0205287:0.187087:0.214666:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.1553   ES:SE:LP:AF:ID  0.0106676:0.0230879:0.19382:0.1553:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.399922 ES:SE:LP:AF:ID  0.0126544:0.0191013:0.29243:0.399922:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.416481 ES:SE:LP:AF:ID  -0.0157499:0.0151309:0.522879:0.416481:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.416415 ES:SE:LP:AF:ID  -0.00715662:0.0174243:0.167491:0.416415:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.251591 ES:SE:LP:AF:ID  -0.0168659:0.0196613:0.408935:0.251591:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089376 ES:SE:LP:AF:ID  -0.0134124:0.0298543:0.187087:0.089376:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.087947 ES:SE:LP:AF:ID  -0.0276404:0.0299868:0.443698:0.087947:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080378 ES:SE:LP:AF:ID  -0.011597:0.0310823:0.148742:0.080378:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.435691 ES:SE:LP:AF:ID  0.030378:0.0165702:1.17393:0.435691:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381047 ES:SE:LP:AF:ID  -0.00953503:0.0177395:0.229148:0.381047:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.1582   ES:SE:LP:AF:ID  -0.0370863:0.0226712:1:0.1582:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683089 ES:SE:LP:AF:ID  0.0101242:0.017622:0.244125:0.683089:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079109 ES:SE:LP:AF:ID  -0.011521:0.0313529:0.148742:0.079109:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.069252 ES:SE:LP:AF:ID  0.00660449:0.0324265:0.0757207:0.069252:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032733 ES:SE:LP:AF:ID  0.0746865:0.0484812:0.920819:0.032733:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0725   ES:SE:LP:AF:ID  0.00312128:0.0318761:0.0362122:0.0725:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.752094 ES:SE:LP:AF:ID  0.000731217:0.020041:0.0132283:0.752094:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034051 ES:SE:LP:AF:ID  -0.00123945:0.0455369:0.00877392:0.034051:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034051 ES:SE:LP:AF:ID  -0.00123945:0.0455369:0.00877392:0.034051:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.07639  ES:SE:LP:AF:ID  -0.0268995:0.0321041:0.39794:0.07639:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077895 ES:SE:LP:AF:ID  -0.0434171:0.0306621:0.79588:0.077895:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076183 ES:SE:LP:AF:ID  -0.0274566:0.0321029:0.408935:0.076183:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076183 ES:SE:LP:AF:ID  -0.0274566:0.0321029:0.408935:0.076183:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041643 ES:SE:LP:AF:ID  0.0252632:0.0443006:0.244125:0.041643:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.059673 ES:SE:LP:AF:ID  0.0170846:0.0346286:0.207608:0.059673:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075685 ES:SE:LP:AF:ID  -0.0479908:0.0311216:0.920819:0.075685:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075701 ES:SE:LP:AF:ID  -0.047506:0.0311186:0.886057:0.075701:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.354828 ES:SE:LP:AF:ID  0.0269082:0.0179424:0.886057:0.354828:rs201754587