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/e74f88d7-129d-4f19-9174-356e14a6f119/call-ldsc/inputs/-261022282/ieu-b-5063.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5063/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Apr 23 07:32:38 2022
Reading summary statistics from /data/cromwell-executions/qc/e74f88d7-129d-4f19-9174-356e14a6f119/call-ldsc/inputs/-261022282/ieu-b-5063.vcf.gz ...
Read summary statistics for 12242497 SNPs.
Dropped 231379 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, 1220578 SNPs remain.
After merging with regression SNP LD, 1220578 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0016 (0.0009)
Lambda GC: 1.0132
Mean Chi^2: 1.0156
Intercept: 1.0003 (0.0058)
Ratio: 0.0194 (0.3748)
Analysis finished at Sat Apr 23 07:34:38 2022
Total time elapsed: 2.0m:0.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.95,
    "inflation_factor": 1.0096,
    "mean_EFFECT": -0.0007,
    "n": "-Inf",
    "n_snps": 12243497,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1279891,
    "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": 404160,
    "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": 1220578,
    "ldsc_nsnp_merge_regression_ld": 1220578,
    "ldsc_observed_scale_h2_beta": 0.0016,
    "ldsc_observed_scale_h2_se": 0.0009,
    "ldsc_intercept_beta": 1.0003,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0132,
    "ldsc_mean_chisq": 1.0156,
    "ldsc_ratio": 0.0192
}

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 FALSE
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 566 0.9999538 3 58 0 12193985 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 101 0 56052 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 34526 0 NA NA NA NA NA NA NA NA NA NA
logical N 12243497 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 8.635976e+00 5.758636e+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 7.869393e+07 5.629934e+07 302.0000000 3.250308e+07 6.911920e+07 1.143453e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.455000e-04 1.661929e-01 -48.3895000 -3.932260e-02 -6.077000e-04 3.741680e-02 7.538800e+01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.698880e-02 1.702789e-01 0.0268925 3.260820e-02 5.270050e-02 1.216400e-01 4.440200e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.986903e-01 2.885878e-01 0.0000000 2.490852e-01 4.979411e-01 7.482556e-01 9.999999e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.986903e-01 2.885878e-01 0.0000000 2.490851e-01 4.979417e-01 7.482561e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.127956e-01 2.602011e-01 0.0000054 1.457940e-02 8.849660e-02 3.382510e-01 9.999950e-01 ▇▂▁▁▁
numeric AF_reference 404160 0.9669898 NA NA NA NA NA NA NA 2.160787e-01 2.512173e-01 0.0000000 1.357830e-02 1.106230e-01 3.426520e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs367896724 A AC -0.0022879 0.0415742 0.9561134 0.9561134 0.3989060 0.4253190 NA
1 10352 rs555500075 T TA -0.0098093 0.0428246 0.8188244 0.8188245 0.3932360 0.4375000 NA
1 11008 rs575272151 C G 0.1001830 0.0709640 0.1580240 0.1580254 0.0862242 0.0880591 NA
1 11012 rs544419019 C G 0.1001830 0.0709640 0.1580240 0.1580254 0.0862242 0.0880591 NA
1 13110 rs540538026 G A 0.0150990 0.0949524 0.8736559 0.8736559 0.0586843 0.0267572 NA
1 13116 rs62635286 T G 0.0034249 0.0559180 0.9511614 0.9511614 0.1891810 0.0970447 NA
1 13118 rs200579949 A G 0.0034249 0.0559180 0.9511614 0.9511614 0.1891810 0.0970447 NA
1 13273 rs531730856 G C 0.0532071 0.0655220 0.4167629 0.4167633 0.1341340 0.0950479 NA
1 14464 rs546169444 A T 0.0043777 0.0596782 0.9415229 0.9415230 0.1568980 0.0958466 NA
1 14599 rs531646671 T A 0.0251811 0.0541774 0.6420827 0.6420820 0.1915570 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233182 rs4040317 G A -0.0457648 0.0340584 0.1790404 0.1790404 0.3200860 0.2633790 NA
22 51233300 rs9616839 C T -0.0476179 0.0339766 0.1610675 0.1610673 0.3343140 0.3146960 NA
22 51233312 rs62240043 A G -0.0586319 0.0357671 0.1011572 0.1011572 0.2729950 0.2134580 NA
22 51233347 rs62240044 T C -0.0586319 0.0357671 0.1011572 0.1011572 0.2729950 0.2134580 NA
22 51234799 rs191117135 G A 0.1775440 0.1251650 0.1560533 0.1560508 0.0156550 0.0059904 NA
22 51235959 rs200189535 T C 0.0721331 0.0415789 0.0827675 0.0827676 0.1953500 0.1996810 NA
22 51235979 rs62240045 G A -0.0161423 0.0462086 0.7268386 0.7268375 0.2637980 0.2400160 NA
22 51236013 rs200507571 A AT 0.0289839 0.0358127 0.4183310 0.4183317 0.2513400 0.1487620 NA
22 51237063 rs3896457 T C -0.0544841 0.0329524 0.0982449 0.0982458 0.2979820 0.2050720 NA
22 51237712 rs370652263 G A -0.1036360 0.0656721 0.1145460 0.1145466 0.0553522 0.0690895 NA

bcf preview

1   10177   rs1264289758    A   AC  .   PASS    AF=0.398906 ES:SE:LP:AF:ID  -0.00228789:0.0415742:0.0194906:0.398906:rs1264289758
1   10352   rs1557426776    T   TA  .   PASS    AF=0.393236 ES:SE:LP:AF:ID  -0.00980928:0.0428246:0.0868092:0.393236:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.0862242    ES:SE:LP:AF:ID  0.100183:0.070964:0.801277:0.0862242:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.0862242    ES:SE:LP:AF:ID  0.100183:0.070964:0.801277:0.0862242:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.0586843    ES:SE:LP:AF:ID  0.015099:0.0949524:0.0586596:0.0586843:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  0.00342489:0.055918:0.0217458:0.189181:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  0.00342489:0.055918:0.0217458:0.189181:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134134 ES:SE:LP:AF:ID  0.0532071:0.065522:0.380111:0.134134:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156898 ES:SE:LP:AF:ID  0.00437774:0.0596782:0.0261691:0.156898:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191557 ES:SE:LP:AF:ID  0.0251811:0.0541774:0.192409:0.191557:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191557 ES:SE:LP:AF:ID  0.0251811:0.0541774:0.192409:0.191557:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473819 ES:SE:LP:AF:ID  0.053418:0.0421498:0.688173:0.473819:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.0450802    ES:SE:LP:AF:ID  0.0408506:0.103944:0.158444:0.0450802:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741355 ES:SE:LP:AF:ID  0.107851:0.0487594:1.56907:0.741355:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275124 ES:SE:LP:AF:ID  0.0434631:0.0500233:0.414624:0.275124:rs1316988498
1   15903   rs557514207 G   GC  .   PASS    AF=0.41884  ES:SE:LP:AF:ID  -0.0105186:0.0412482:0.0976071:0.41884:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956571 ES:SE:LP:AF:ID  -0.0332541:0.116816:0.110196:0.956571:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910221 ES:SE:LP:AF:ID  0.021236:0.0777968:0.105198:0.910221:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.0627121    ES:SE:LP:AF:ID  0.130423:0.0891628:0.843043:0.0627121:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623768 ES:SE:LP:AF:ID  0.045535:0.0494557:0.447096:0.623768:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.0929554    ES:SE:LP:AF:ID  -0.128537:0.0759353:1.04331:0.0929554:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.21326  ES:SE:LP:AF:ID  -0.00495279:0.0529053:0.0336639:0.21326:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154391 ES:SE:LP:AF:ID  0.00819772:0.0593586:0.0505332:0.154391:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400396 ES:SE:LP:AF:ID  0.00372807:0.04898:0.0271826:0.400396:rs2462492
1   54712   rs573184866 T   TTTTC   .   PASS    AF=0.585268 ES:SE:LP:AF:ID  -0.00806388:0.0387312:0.0782761:0.585268:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417371 ES:SE:LP:AF:ID  0.0347021:0.044795:0.358006:0.417371:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253777 ES:SE:LP:AF:ID  -0.0213257:0.0502158:0.173233:0.253777:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.0899979    ES:SE:LP:AF:ID  -0.160465:0.0766019:1.44142:0.0899979:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.0887883    ES:SE:LP:AF:ID  -0.12789:0.0768895:1.01658:0.0887883:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.0809837    ES:SE:LP:AF:ID  -0.152228:0.0798045:1.2483:0.0809837:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438273 ES:SE:LP:AF:ID  -0.0559028:0.0425537:0.72366:0.438273:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382186 ES:SE:LP:AF:ID  -0.0202635:0.0456684:0.182268:0.382186:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158756 ES:SE:LP:AF:ID  -0.0423151:0.0583298:0.329588:0.158756:rs80011619
1   63735   rs61158452  CCTA    C   .   PASS    AF=0.315972 ES:SE:LP:AF:ID  0.054556:0.0454123:0.638996:0.315972:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.0795793    ES:SE:LP:AF:ID  -0.129267:0.0807627:0.9607:0.0795793:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.0707801    ES:SE:LP:AF:ID  -0.031563:0.0819175:0.154894:0.0707801:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0329199    ES:SE:LP:AF:ID  -0.143629:0.123746:0.609464:0.0329199:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0738738    ES:SE:LP:AF:ID  -0.0272905:0.0805684:0.133821:0.0738738:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751218 ES:SE:LP:AF:ID  0.0997093:0.0512506:1.28641:0.751218:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0340921    ES:SE:LP:AF:ID  0.0730219:0.116795:0.274226:0.0340921:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.0340921    ES:SE:LP:AF:ID  0.0730219:0.116795:0.274226:0.0340921:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.0771356    ES:SE:LP:AF:ID  -0.111209:0.0821759:0.754595:0.0771356:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.0775037    ES:SE:LP:AF:ID  0.0712185:0.0795242:0.431225:0.0775037:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.0769408    ES:SE:LP:AF:ID  -0.110134:0.0821969:0.744042:0.0769408:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.0769408    ES:SE:LP:AF:ID  -0.110134:0.0821969:0.744042:0.0769408:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.0414632    ES:SE:LP:AF:ID  0.0990295:0.115356:0.408231:0.0414632:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.0609432    ES:SE:LP:AF:ID  -0.0672142:0.087197:0.355752:0.0609432:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.0754482    ES:SE:LP:AF:ID  0.0671137:0.080536:0.392916:0.0754482:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0754758    ES:SE:LP:AF:ID  0.0673544:0.080522:0.394814:0.0754758:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352798 ES:SE:LP:AF:ID  0.0688558:0.0460473:0.870216:0.352798:rs201754587