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/0129004e-cfd6-4fd2-8689-663aa4d1a07b/call-ldsc/inputs/-261043418/ieu-b-4969.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4969/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 20:44:07 2022
Reading summary statistics from /data/cromwell-executions/qc/0129004e-cfd6-4fd2-8689-663aa4d1a07b/call-ldsc/inputs/-261043418/ieu-b-4969.vcf.gz ...
Read summary statistics for 11394988 SNPs.
Dropped 192950 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, 1218877 SNPs remain.
After merging with regression SNP LD, 1218877 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0059 (0.0017)
Lambda GC: 1.0493
Mean Chi^2: 1.0606
Intercept: 1.0169 (0.0063)
Ratio: 0.2793 (0.104)
Analysis finished at Fri Mar  4 20:46:04 2022
Total time elapsed: 1.0m:57.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -7.9501e-06,
    "n": "-Inf",
    "n_snps": 11396019,
    "n_clumped_hits": 11,
    "n_p_sig": 1762,
    "n_mono": 0,
    "n_ns": 1252743,
    "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": 1283150,
    "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": 1218877,
    "ldsc_nsnp_merge_regression_ld": 1218877,
    "ldsc_observed_scale_h2_beta": 0.0059,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0169,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0493,
    "ldsc_mean_chisq": 1.0606,
    "ldsc_ratio": 0.2789
}

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 FALSE
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 670 0.9999412 3 58 0 11357277 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 16950 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 69394 0 NA NA NA NA NA NA NA NA NA NA
logical N 11396019 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 8.788266e+00 5.904347e+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 7.861705e+07 5.629749e+07 302.0000000 3.237071e+07 6.911412e+07 1.143929e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -8.000000e-06 7.554000e-04 -0.0092559 -2.994000e-04 -5.600000e-06 2.817000e-04 2.054730e-02 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.987000e-04 4.492000e-04 0.0001886 2.612000e-04 3.888000e-04 8.049000e-04 5.122600e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.950554e-01 2.897529e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.950537e-01 2.897271e-01 0.0000000 2.434590e-01 4.931179e-01 7.456750e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.755186e-01 3.012583e-01 0.0033328 2.530400e-02 1.413510e-01 4.651900e-01 9.966670e-01 ▇▂▂▁▂
numeric AF_reference 1283150 0.8874037 NA NA NA NA NA NA NA 2.269825e-01 2.531567e-01 0.0000000 1.896960e-02 1.255990e-01 3.620210e-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 -0.0005997 0.0003425 0.0800000 0.0799458 0.601275 NA NA
1 10352 rs1557426776 TA T 0.0004289 0.0003528 0.2200002 0.2240087 0.607053 NA NA
1 11008 rs575272151 C G -0.0005046 0.0005865 0.3900004 0.3896712 0.086173 0.0880591 NA
1 11012 rs544419019 C G -0.0005046 0.0005865 0.3900004 0.3896712 0.086173 0.0880591 NA
1 13110 rs540538026 G A -0.0010608 0.0007794 0.1700000 0.1734777 0.058717 0.0267572 NA
1 13116 rs62635286 T G -0.0007080 0.0004615 0.1299999 0.1250093 0.189376 0.0970447 NA
1 13118 rs200579949 A G -0.0007080 0.0004615 0.1299999 0.1250093 0.189376 0.0970447 NA
1 13273 rs531730856 G C -0.0002735 0.0005408 0.6100002 0.6130927 0.133920 0.0950479 NA
1 14464 rs546169444 A T -0.0001481 0.0004912 0.7600007 0.7629511 0.157048 0.0958466 NA
1 14599 rs531646671 T A 0.0000804 0.0004478 0.8600001 0.8575306 0.191576 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0006146 0.0002193 0.0051000 0.0050730 0.751666 0.643179 NA
23 154901964 rs697726 G A 0.0005241 0.0002315 0.0239999 0.0235656 0.347603 0.117616 NA
23 154902105 rs696316 G T 0.0006160 0.0002193 0.0050000 0.0049689 0.751619 0.636026 NA
23 154902889 rs697725 A T 0.0006211 0.0002192 0.0046000 0.0046093 0.751292 0.584106 NA
23 154903118 rs479770 G A 0.0006139 0.0002193 0.0051000 0.0051300 0.751709 0.643444 NA
23 154903224 rs480725 A T 0.0006140 0.0002193 0.0051000 0.0051235 0.751712 0.643444 NA
23 154903937 rs674707 G A 0.0006146 0.0002194 0.0051000 0.0050791 0.751722 0.643444 NA
23 154909055 rs473529 C G -0.0005772 0.0002065 0.0052000 0.0051978 0.304936 0.463046 NA
23 154918266 rs642043 C T -0.0005668 0.0002072 0.0062000 0.0062236 0.302804 0.478675 NA
23 154927581 rs644138 G A -0.0005606 0.0002072 0.0068000 0.0068310 0.302679 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601275 ES:SE:LP:AF:ID  -0.000599681:0.000342479:1.09691:0.601275:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607053 ES:SE:LP:AF:ID  0.000428939:0.000352764:0.657577:0.607053:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086173 ES:SE:LP:AF:ID  -0.000504555:0.000586546:0.408935:0.086173:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086173 ES:SE:LP:AF:ID  -0.000504555:0.000586546:0.408935:0.086173:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058717 ES:SE:LP:AF:ID  -0.00106081:0.000779369:0.769551:0.058717:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189376 ES:SE:LP:AF:ID  -0.00070797:0.000461494:0.886057:0.189376:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189376 ES:SE:LP:AF:ID  -0.00070797:0.000461494:0.886057:0.189376:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13392  ES:SE:LP:AF:ID  -0.000273466:0.000540806:0.21467:0.13392:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157048 ES:SE:LP:AF:ID  -0.000148144:0.000491181:0.119186:0.157048:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191576 ES:SE:LP:AF:ID  8.03821e-05:0.000447765:0.0655015:0.191576:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191576 ES:SE:LP:AF:ID  8.03821e-05:0.000447765:0.0655015:0.191576:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473924 ES:SE:LP:AF:ID  -0.000710227:0.000347318:1.38722:0.473924:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.044994 ES:SE:LP:AF:ID  -0.000771348:0.000855507:0.431798:0.044994:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741443 ES:SE:LP:AF:ID  0.00026657:0.000401708:0.29243:0.741443:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.27519  ES:SE:LP:AF:ID  -0.000309436:0.000411896:0.346787:0.27519:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581038 ES:SE:LP:AF:ID  0.000102734:0.000339584:0.119186:0.581038:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.95651  ES:SE:LP:AF:ID  0.000831833:0.000965465:0.408935:0.95651:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910287 ES:SE:LP:AF:ID  0.000142259:0.000641424:0.0861861:0.910287:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062701 ES:SE:LP:AF:ID  0.00124062:0.000731411:1.04576:0.062701:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623673 ES:SE:LP:AF:ID  0.00048064:0.000407425:0.619789:0.623673:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092998 ES:SE:LP:AF:ID  0.000852854:0.000626548:0.769551:0.092998:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213487 ES:SE:LP:AF:ID  -9.99253e-05:0.000435586:0.0861861:0.213487:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154518 ES:SE:LP:AF:ID  -0.000245704:0.000489435:0.207608:0.154518:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400427 ES:SE:LP:AF:ID  3.01929e-05:0.000403628:0.0268721:0.400427:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414798 ES:SE:LP:AF:ID  -0.000329238:0.000319065:0.522879:0.414798:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.41722  ES:SE:LP:AF:ID  -7.77751e-05:0.000368515:0.0809219:0.41722:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253904 ES:SE:LP:AF:ID  0.000485339:0.000414544:0.619789:0.253904:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090074 ES:SE:LP:AF:ID  0.00117171:0.000631174:1.20066:0.090074:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088899 ES:SE:LP:AF:ID  0.000834398:0.000633624:0.721246:0.088899:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081057 ES:SE:LP:AF:ID  0.00111797:0.000657193:1.05061:0.081057:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438451 ES:SE:LP:AF:ID  -0.000331636:0.000350267:0.468521:0.438451:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382154 ES:SE:LP:AF:ID  0.000454944:0.0003766:0.638272:0.382154:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158887 ES:SE:LP:AF:ID  0.000763691:0.000479371:0.958607:0.158887:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684034 ES:SE:LP:AF:ID  0.000611789:0.000373246:1:0.684034:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079668 ES:SE:LP:AF:ID  0.00124672:0.000665146:1.21467:0.079668:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070764 ES:SE:LP:AF:ID  0.000230371:0.000674799:0.136677:0.070764:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032887 ES:SE:LP:AF:ID  -0.000979127:0.00102168:0.468521:0.032887:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073906 ES:SE:LP:AF:ID  0.000127464:0.000663747:0.0705811:0.073906:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751133 ES:SE:LP:AF:ID  -0.000327828:0.000422783:0.356547:0.751133:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034051 ES:SE:LP:AF:ID  0.000434864:0.00097092:0.187087:0.034051:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034051 ES:SE:LP:AF:ID  0.000434864:0.00097092:0.187087:0.034051:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077229 ES:SE:LP:AF:ID  0.00098065:0.000677903:0.823909:0.077229:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077495 ES:SE:LP:AF:ID  0.00149579:0.000654552:1.65758:0.077495:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077033 ES:SE:LP:AF:ID  0.000980838:0.000678082:0.823909:0.077033:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077033 ES:SE:LP:AF:ID  0.000980838:0.000678082:0.823909:0.077033:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041505 ES:SE:LP:AF:ID  -0.00116357:0.000945326:0.657577:0.041505:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060976 ES:SE:LP:AF:ID  0.000410725:0.000718928:0.244125:0.060976:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075455 ES:SE:LP:AF:ID  0.00154404:0.000662802:1.69897:0.075455:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075483 ES:SE:LP:AF:ID  0.00154741:0.000662669:1.69897:0.075483:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352645 ES:SE:LP:AF:ID  -0.00048192:0.000379589:0.69897:0.352645:rs201754587