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/d4932098-321d-49ff-916b-9c5aa9dec561/call-ldsc/inputs/268670747/ieu-b-108.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-108/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Mon Mar 29 16:32:12 2021
Reading summary statistics from /data/cromwell-executions/qc/d4932098-321d-49ff-916b-9c5aa9dec561/call-ldsc/inputs/268670747/ieu-b-108.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 Mar 29 16:33:23 2021
Total time elapsed: 1.0m:11.14s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 198,
    "n_p_sig": 45875,
    "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 TRUE
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 TRUE
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 3.690000e-05 1.041710e-02 -0.6383840 -3.280400e-03 5.400000e-06 3.314300e-03 5.623320e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.893800e-03 6.616700e-03 0.0017162 2.414400e-03 3.877000e-03 8.945600e-03 1.059540e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.585213e-01 3.011596e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.585225e-01 3.011347e-01 0.0000000 1.875014e-01 4.456904e-01 7.192220e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594004e-01 3.020423e-01 0.0009710 1.659900e-02 1.145700e-01 4.379180e-01 9.990220e-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 -0.0052244 0.0030890 0.0909997 0.0907857 0.601008 NA NA
1 10352 rs1557426776 TA T -0.0029553 0.0031809 0.3500000 0.3528509 0.606745 NA NA
1 11008 rs575272151 C G -0.0068603 0.0052887 0.1900002 0.1945742 0.086209 0.0880591 NA
1 11012 rs544419019 C G -0.0068603 0.0052887 0.1900002 0.1945742 0.086209 0.0880591 NA
1 13110 rs540538026 G A -0.0019402 0.0070383 0.7800007 0.7828023 0.058643 0.0267572 NA
1 13116 rs62635286 T G -0.0009427 0.0041639 0.8200001 0.8208971 0.189094 0.0970447 NA
1 13118 rs200579949 A G -0.0009427 0.0041639 0.8200001 0.8208971 0.189094 0.0970447 NA
1 13273 rs531730856 G C -0.0085986 0.0048736 0.0779992 0.0776779 0.134150 0.0950479 NA
1 14464 rs546169444 A T -0.0007074 0.0044355 0.8700001 0.8732862 0.156975 0.0958466 NA
1 14599 rs531646671 T A 0.0009446 0.0040380 0.8200001 0.8150408 0.191497 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0005391 0.0019967 0.7899998 0.7871509 0.751915 0.643179 NA
23 154901964 rs697726 G A 0.0029289 0.0021053 0.1600000 0.1641578 0.347951 0.117616 NA
23 154902105 rs696316 G T 0.0005361 0.0019966 0.7899998 0.7883249 0.751870 0.636026 NA
23 154902889 rs697725 A T 0.0007103 0.0019960 0.7199992 0.7219456 0.751544 0.584106 NA
23 154903118 rs479770 G A 0.0004973 0.0019970 0.8000000 0.8033463 0.751959 0.643444 NA
23 154903224 rs480725 A T 0.0004984 0.0019970 0.8000000 0.8029129 0.751962 0.643444 NA
23 154903937 rs674707 G A 0.0005052 0.0019970 0.8000000 0.8003021 0.751972 0.643444 NA
23 154909055 rs473529 C G -0.0003023 0.0018798 0.8700001 0.8722181 0.304825 0.463046 NA
23 154918266 rs642043 C T -0.0007054 0.0018857 0.7099994 0.7083449 0.302695 0.478675 NA
23 154927581 rs644138 G A -0.0006357 0.0018861 0.7400005 0.7360854 0.302570 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601008 ES:SE:LP:AF:ID  -0.00522436:0.00308902:1.04096:0.601008:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606745 ES:SE:LP:AF:ID  -0.0029553:0.00318091:0.455932:0.606745:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086209 ES:SE:LP:AF:ID  -0.00686032:0.0052887:0.721246:0.086209:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086209 ES:SE:LP:AF:ID  -0.00686032:0.0052887:0.721246:0.086209:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058643 ES:SE:LP:AF:ID  -0.00194023:0.00703826:0.107905:0.058643:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189094 ES:SE:LP:AF:ID  -0.00094268:0.00416394:0.0861861:0.189094:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189094 ES:SE:LP:AF:ID  -0.00094268:0.00416394:0.0861861:0.189094:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13415  ES:SE:LP:AF:ID  -0.00859858:0.00487359:1.10791:0.13415:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156975 ES:SE:LP:AF:ID  -0.000707404:0.00443553:0.0604807:0.156975:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191497 ES:SE:LP:AF:ID  0.000944604:0.00403801:0.0861861:0.191497:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191497 ES:SE:LP:AF:ID  0.000944604:0.00403801:0.0861861:0.191497:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473807 ES:SE:LP:AF:ID  0.00645857:0.0031317:1.40894:0.473807:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045073 ES:SE:LP:AF:ID  0.00615495:0.00770352:0.376751:0.045073:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741383 ES:SE:LP:AF:ID  -0.000955281:0.00362144:0.102373:0.741383:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275176 ES:SE:LP:AF:ID  -0.00162466:0.00371695:0.180456:0.275176:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581214 ES:SE:LP:AF:ID  0.00240456:0.00306186:0.366532:0.581214:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956526 ES:SE:LP:AF:ID  -0.0152527:0.00871436:1.09691:0.956526:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910242 ES:SE:LP:AF:ID  0.00093495:0.00578515:0.0604807:0.910242:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062691 ES:SE:LP:AF:ID  0.0102923:0.00660005:0.920819:0.062691:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623668 ES:SE:LP:AF:ID  0.00220994:0.00367516:0.259637:0.623668:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092944 ES:SE:LP:AF:ID  -0.00802757:0.0056585:0.79588:0.092944:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213251 ES:SE:LP:AF:ID  -0.00188721:0.00393268:0.200659:0.213251:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154434 ES:SE:LP:AF:ID  0.0032791:0.00441699:0.337242:0.154434:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.40034  ES:SE:LP:AF:ID  -0.00318257:0.00364085:0.420216:0.40034:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414791 ES:SE:LP:AF:ID  -0.00289544:0.00287886:0.508638:0.414791:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417321 ES:SE:LP:AF:ID  -0.00358733:0.00332499:0.552842:0.417321:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253764 ES:SE:LP:AF:ID  -0.00557495:0.00374103:0.853872:0.253764:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089988 ES:SE:LP:AF:ID  -0.00864306:0.00570297:0.886057:0.089988:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088777 ES:SE:LP:AF:ID  -0.00915724:0.00572665:0.958607:0.088777:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080977 ES:SE:LP:AF:ID  -0.00928:0.00593911:0.920819:0.080977:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.43823  ES:SE:LP:AF:ID  -0.00424637:0.00315926:0.744727:0.43823:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382126 ES:SE:LP:AF:ID  -0.00654078:0.00339685:1.26761:0.382126:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158744 ES:SE:LP:AF:ID  -0.00395196:0.0043279:0.443698:0.158744:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683931 ES:SE:LP:AF:ID  -0.000809788:0.00336919:0.091515:0.683931:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079582 ES:SE:LP:AF:ID  -0.00967706:0.00601165:0.958607:0.079582:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070778 ES:SE:LP:AF:ID  0.00768856:0.00608762:0.677781:0.070778:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032911 ES:SE:LP:AF:ID  -0.0142871:0.00920593:0.920819:0.032911:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073861 ES:SE:LP:AF:ID  0.00757192:0.00599196:0.677781:0.073861:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751214 ES:SE:LP:AF:ID  0.00291187:0.00381639:0.346787:0.751214:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034128 ES:SE:LP:AF:ID  -0.00132759:0.00874048:0.0555173:0.034128:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034128 ES:SE:LP:AF:ID  -0.00132759:0.00874048:0.0555173:0.034128:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077102 ES:SE:LP:AF:ID  -0.00739174:0.0061289:0.638272:0.077102:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077474 ES:SE:LP:AF:ID  0.000673504:0.00590632:0.0409586:0.077474:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076906 ES:SE:LP:AF:ID  -0.00734175:0.00613044:0.638272:0.076906:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076906 ES:SE:LP:AF:ID  -0.00734175:0.00613044:0.638272:0.076906:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041498 ES:SE:LP:AF:ID  0.00621506:0.00853791:0.327902:0.041498:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060919 ES:SE:LP:AF:ID  0.0128494:0.00648986:1.31876:0.060919:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075427 ES:SE:LP:AF:ID  -6.04492e-05:0.00598212:0.00436481:0.075427:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075453 ES:SE:LP:AF:ID  -0.000266504:0.00598091:0.0177288:0.075453:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.35275  ES:SE:LP:AF:ID  -0.00450664:0.00342129:0.721246:0.35275:rs201754587