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/dab4d15d-fe97-4ed2-86d7-232f80134427/call-ldsc/inputs/-261043396/ieu-b-4970.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4970/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Apr 23 00:43:38 2022
Reading summary statistics from /data/cromwell-executions/qc/dab4d15d-fe97-4ed2-86d7-232f80134427/call-ldsc/inputs/-261043396/ieu-b-4970.vcf.gz ...
Read summary statistics for 12242539 SNPs.
Dropped 231421 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: 0.0081 (0.0018)
Lambda GC: 1.073
Mean Chi^2: 1.0855
Intercept: 1.0062 (0.0096)
Ratio: 0.073 (0.1117)
Analysis finished at Sat Apr 23 00:45:39 2022
Total time elapsed: 2.0m:1.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.95,
    "inflation_factor": 1.0561,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 12243539,
    "n_clumped_hits": 3,
    "n_p_sig": 83,
    "n_mono": 0,
    "n_ns": 1279901,
    "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": 404182,
    "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": 0.0081,
    "ldsc_observed_scale_h2_se": 0.0018,
    "ldsc_intercept_beta": 1.0062,
    "ldsc_intercept_se": 0.0096,
    "ldsc_lambda_gc": 1.073,
    "ldsc_mean_chisq": 1.0855,
    "ldsc_ratio": 0.0725
}

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 12193986 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 12243539 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 8.635972e+00 5.758637e+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 7.869394e+07 5.629934e+07 302.0000000 3.250309e+07 6.911924e+07 1.143453e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.100000e-05 8.660090e-02 -27.1320000 -1.892620e-02 -1.197000e-04 1.876540e-02 3.037930e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.629740e-02 8.085320e-02 0.0128046 1.554060e-02 2.512360e-02 5.799700e-02 1.978820e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.912759e-01 2.909752e-01 0.0000000 2.373176e-01 4.882149e-01 7.434196e-01 9.999997e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.912759e-01 2.909752e-01 0.0000000 2.373171e-01 4.882151e-01 7.434199e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.127948e-01 2.602010e-01 0.0000054 1.457910e-02 8.849500e-02 3.382500e-01 9.999950e-01 ▇▂▁▁▁
numeric AF_reference 404182 0.9669881 NA NA NA NA NA NA NA 2.160784e-01 2.512172e-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 0.0375803 0.0198069 0.0577843 0.0577839 0.3989060 0.4253190 NA
1 10352 rs555500075 T TA 0.0351387 0.0204046 0.0850531 0.0850520 0.3932360 0.4375000 NA
1 11008 rs575272151 C G -0.0283632 0.0338926 0.4026744 0.4026739 0.0862242 0.0880591 NA
1 11012 rs544419019 C G -0.0283632 0.0338926 0.4026744 0.4026739 0.0862242 0.0880591 NA
1 13110 rs540538026 G A -0.0928454 0.0451139 0.0395886 0.0395880 0.0586843 0.0267572 NA
1 13116 rs62635286 T G 0.0636401 0.0266856 0.0170880 0.0170879 0.1891810 0.0970447 NA
1 13118 rs200579949 A G 0.0636401 0.0266856 0.0170880 0.0170879 0.1891810 0.0970447 NA
1 13273 rs531730856 G C 0.0185613 0.0313065 0.5532546 0.5532550 0.1341340 0.0950479 NA
1 14464 rs546169444 A T -0.0601317 0.0284630 0.0346330 0.0346327 0.1568980 0.0958466 NA
1 14599 rs531646671 T A 0.0314164 0.0258446 0.2241414 0.2241417 0.1915570 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233182 rs4040317 G A -0.0199616 0.0161852 0.2174528 0.2174548 0.3200860 0.2633790 NA
22 51233300 rs9616839 C T -0.0142356 0.0161624 0.3784330 0.3784342 0.3343140 0.3146960 NA
22 51233312 rs62240043 A G -0.0174394 0.0170187 0.3054949 0.3054954 0.2729950 0.2134580 NA
22 51233347 rs62240044 T C -0.0174394 0.0170187 0.3054949 0.3054954 0.2729950 0.2134580 NA
22 51234799 rs191117135 G A 0.0356663 0.0601451 0.5531781 0.5531783 0.0156550 0.0059904 NA
22 51235959 rs200189535 T C -0.0199110 0.0198131 0.3149249 0.3149252 0.1953500 0.1996810 NA
22 51235979 rs62240045 G A 0.0134809 0.0220666 0.5412551 0.5412534 0.2637980 0.2400160 NA
22 51236013 rs200507571 A AT 0.0263117 0.0170850 0.1235504 0.1235489 0.2513400 0.1487620 NA
22 51237063 rs3896457 T C -0.0316964 0.0156609 0.0429774 0.0429784 0.2979820 0.2050720 NA
22 51237712 rs370652263 G A -0.0116745 0.0313226 0.7093589 0.7093583 0.0553522 0.0690895 NA

bcf preview

1   10177   rs1264289758    A   AC  .   PASS    AF=0.398906 ES:SE:LP:AF:ID  0.0375803:0.0198069:1.23819:0.398906:rs1264289758
1   10352   rs1557426776    T   TA  .   PASS    AF=0.393236 ES:SE:LP:AF:ID  0.0351387:0.0204046:1.07031:0.393236:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.0862242    ES:SE:LP:AF:ID  -0.0283632:0.0338926:0.395046:0.0862242:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.0862242    ES:SE:LP:AF:ID  -0.0283632:0.0338926:0.395046:0.0862242:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.0586843    ES:SE:LP:AF:ID  -0.0928454:0.0451139:1.40243:0.0586843:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  0.0636401:0.0266856:1.76731:0.189181:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  0.0636401:0.0266856:1.76731:0.189181:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134134 ES:SE:LP:AF:ID  0.0185613:0.0313065:0.257075:0.134134:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156898 ES:SE:LP:AF:ID  -0.0601317:0.028463:1.46051:0.156898:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191557 ES:SE:LP:AF:ID  0.0314164:0.0258446:0.649478:0.191557:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191557 ES:SE:LP:AF:ID  0.0314164:0.0258446:0.649478:0.191557:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473819 ES:SE:LP:AF:ID  -0.00285074:0.0201032:0.051962:0.473819:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.0450802    ES:SE:LP:AF:ID  0.0322621:0.0494816:0.288699:0.0450802:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741355 ES:SE:LP:AF:ID  0.024378:0.023236:0.531491:0.741355:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275124 ES:SE:LP:AF:ID  0.00166306:0.0237979:0.024896:0.275124:rs1316988498
1   15903   rs557514207 G   GC  .   PASS    AF=0.41884  ES:SE:LP:AF:ID  -0.0180908:0.0196501:0.447048:0.41884:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956571 ES:SE:LP:AF:ID  -0.0989962:0.0558489:1.11748:0.956571:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910221 ES:SE:LP:AF:ID  0.0415748:0.0370004:0.583078:0.910221:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.0627121    ES:SE:LP:AF:ID  0.024948:0.0422117:0.256093:0.0627121:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623768 ES:SE:LP:AF:ID  -0.00760811:0.0235449:0.126915:0.623768:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.0929554    ES:SE:LP:AF:ID  0.0124026:0.0362695:0.135261:0.0929554:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.21326  ES:SE:LP:AF:ID  -0.0333566:0.0252077:0.731082:0.21326:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154391 ES:SE:LP:AF:ID  -0.0523541:0.0283151:1.19071:0.154391:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400396 ES:SE:LP:AF:ID  0.0306591:0.0233598:0.72271:0.400396:rs2462492
1   54712   rs573184866 T   TTTTC   .   PASS    AF=0.585268 ES:SE:LP:AF:ID  0.0253801:0.0184613:0.771598:0.585268:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417371 ES:SE:LP:AF:ID  0.0115318:0.0213154:0.230251:0.417371:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253777 ES:SE:LP:AF:ID  0.0372048:0.023983:0.917825:0.253777:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.0899979    ES:SE:LP:AF:ID  0.0315913:0.036568:0.411572:0.0899979:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.0887883    ES:SE:LP:AF:ID  0.0312803:0.0367286:0.404059:0.0887883:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.0809837    ES:SE:LP:AF:ID  0.0175585:0.0380752:0.190651:0.0809837:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438273 ES:SE:LP:AF:ID  0.00964404:0.0202669:0.197788:0.438273:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382186 ES:SE:LP:AF:ID  0.00437144:0.0217951:0.0751861:0.382186:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158756 ES:SE:LP:AF:ID  0.0101585:0.0277074:0.146368:0.158756:rs80011619
1   63735   rs61158452  CCTA    C   .   PASS    AF=0.315972 ES:SE:LP:AF:ID  -0.0410997:0.0216011:1.24349:0.315972:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.0795793    ES:SE:LP:AF:ID  0.0150274:0.0385571:0.156939:0.0795793:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.0707801    ES:SE:LP:AF:ID  0.00684185:0.0390691:0.065005:0.0707801:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0329199    ES:SE:LP:AF:ID  -0.0698079:0.0593483:0.620698:0.0329199:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0738738    ES:SE:LP:AF:ID  -0.00165079:0.0384458:0.0151349:0.0738738:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751218 ES:SE:LP:AF:ID  -0.0318164:0.0244798:0.712864:0.751218:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0340921    ES:SE:LP:AF:ID  -0.0937253:0.0560612:1.02431:0.0340921:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.0340921    ES:SE:LP:AF:ID  -0.0937253:0.0560612:1.02431:0.0340921:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.0771356    ES:SE:LP:AF:ID  0.0293076:0.0392811:0.341409:0.0771356:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.0775037    ES:SE:LP:AF:ID  -0.0232403:0.0377603:0.26902:0.0775037:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.0769408    ES:SE:LP:AF:ID  0.0298956:0.0392893:0.349974:0.0769408:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.0769408    ES:SE:LP:AF:ID  0.0298956:0.0392893:0.349974:0.0769408:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.0414632    ES:SE:LP:AF:ID  0.0485773:0.054693:0.426614:0.0414632:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.0609432    ES:SE:LP:AF:ID  -0.00689416:0.0416827:0.0611641:0.0609432:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.0754482    ES:SE:LP:AF:ID  -0.0267016:0.0382506:0.314139:0.0754482:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0754758    ES:SE:LP:AF:ID  -0.0274252:0.0382426:0.324874:0.0754758:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352798 ES:SE:LP:AF:ID  -0.013744:0.0219383:0.274908:0.352798:rs201754587