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/a04df373-03e0-4e48-a2ac-5d8be2b12c83/call-ldsc/inputs/-261022215/ieu-b-5088.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5088/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 27 21:47:02 2022
Reading summary statistics from /data/cromwell-executions/qc/a04df373-03e0-4e48-a2ac-5d8be2b12c83/call-ldsc/inputs/-261022215/ieu-b-5088.vcf.gz ...
Read summary statistics for 12242540 SNPs.
Dropped 231422 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: 0.0033 (0.0009)
Lambda GC: 1.0328
Mean Chi^2: 1.0321
Intercept: 1.002 (0.006)
Ratio: 0.0627 (0.1857)
Analysis finished at Thu Oct 27 21:48:55 2022
Total time elapsed: 1.0m:53.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.95,
    "inflation_factor": 1.0279,
    "mean_EFFECT": -0.0002,
    "n": "-Inf",
    "n_snps": 12243540,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1279900,
    "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": 404183,
    "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": 0.0033,
    "ldsc_observed_scale_h2_se": 0.0009,
    "ldsc_intercept_beta": 1.002,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0328,
    "ldsc_mean_chisq": 1.0321,
    "ldsc_ratio": 0.0623
}
 

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 12193990 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 12243540 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 8.635974e+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 7.869393e+07 5.629933e+07 302.0000000 3.250309e+07 6.911922e+07 1.143452e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.990000e-04 8.696170e-02 -25.9891000 -1.888870e-02 -1.342000e-04 1.841410e-02 3.410840e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.675600e-02 8.239420e-02 0.0129077 1.566670e-02 2.532910e-02 5.848480e-02 2.117240e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.958393e-01 2.897946e-01 0.0000003 2.439681e-01 4.940729e-01 7.470437e-01 9.999999e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.958393e-01 2.897946e-01 0.0000003 2.439681e-01 4.940722e-01 7.470431e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.127948e-01 2.602010e-01 0.0000054 1.457920e-02 8.849450e-02 3.382510e-01 9.999950e-01 ▇▂▁▁▁
numeric AF_reference 404183 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 0.0239320 0.0199771 0.2309277 0.2309280 0.3989090 0.4253190 NA
1 10352 rs555500075 T TA 0.0241459 0.0205657 0.2403604 0.2403606 0.3932350 0.4375000 NA
1 11008 rs575272151 C G -0.0218043 0.0340917 0.5224479 0.5224470 0.0862238 0.0880591 NA
1 11012 rs544419019 C G -0.0218043 0.0340917 0.5224479 0.5224470 0.0862238 0.0880591 NA
1 13110 rs540538026 G A -0.0098554 0.0454133 0.8281965 0.8281963 0.0586862 0.0267572 NA
1 13116 rs62635286 T G -0.0050375 0.0268945 0.8514219 0.8514216 0.1891810 0.0970447 NA
1 13118 rs200579949 A G -0.0050375 0.0268945 0.8514219 0.8514216 0.1891810 0.0970447 NA
1 13273 rs531730856 G C 0.0420562 0.0314627 0.1813210 0.1813205 0.1341340 0.0950479 NA
1 14464 rs546169444 A T -0.0428916 0.0286725 0.1346766 0.1346760 0.1568960 0.0958466 NA
1 14599 rs531646671 T A 0.0357521 0.0260905 0.1705886 0.1705898 0.1915560 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233182 rs4040317 G A 0.0278066 0.0163275 0.0885584 0.0885581 0.3200850 0.2633790 NA
22 51233300 rs9616839 C T 0.0239053 0.0162955 0.1423797 0.1423794 0.3343160 0.3146960 NA
22 51233312 rs62240043 A G 0.0194809 0.0171633 0.2563610 0.2563618 0.2729920 0.2134580 NA
22 51233347 rs62240044 T C 0.0194809 0.0171633 0.2563610 0.2563618 0.2729920 0.2134580 NA
22 51234799 rs191117135 G A -0.0840618 0.0608731 0.1672985 0.1672989 0.0156525 0.0059904 NA
22 51235959 rs200189535 T C 0.0342492 0.0199917 0.0866802 0.0866811 0.1953560 0.1996810 NA
22 51235979 rs62240045 G A -0.0354109 0.0222085 0.1108294 0.1108297 0.2637950 0.2400160 NA
22 51236013 rs200507571 A AT -0.0079175 0.0171947 0.6451831 0.6451836 0.2513350 0.1487620 NA
22 51237063 rs3896457 T C 0.0136831 0.0157926 0.3862558 0.3862573 0.2979790 0.2050720 NA
22 51237712 rs370652263 G A -0.0507820 0.0315958 0.1080021 0.1080020 0.0553517 0.0690895 NA

bcf preview

1   10177   rs1264289758    A   AC  .   PASS    AF=0.398909 ES:SE:LP:AF:ID  0.023932:0.0199771:0.636524:0.398909:rs1264289758
1   10352   rs1557426776    T   TA  .   PASS    AF=0.393235 ES:SE:LP:AF:ID  0.0241459:0.0205657:0.619137:0.393235:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.0862238    ES:SE:LP:AF:ID  -0.0218043:0.0340917:0.281957:0.0862238:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.0862238    ES:SE:LP:AF:ID  -0.0218043:0.0340917:0.281957:0.0862238:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.0586862    ES:SE:LP:AF:ID  -0.00985539:0.0454133:0.0818666:0.0586862:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  -0.00503747:0.0268945:0.0698552:0.189181:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  -0.00503747:0.0268945:0.0698552:0.189181:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134134 ES:SE:LP:AF:ID  0.0420562:0.0314627:0.741552:0.134134:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156896 ES:SE:LP:AF:ID  -0.0428916:0.0286725:0.870708:0.156896:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191556 ES:SE:LP:AF:ID  0.0357521:0.0260905:0.76805:0.191556:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191556 ES:SE:LP:AF:ID  0.0357521:0.0260905:0.76805:0.191556:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.47382  ES:SE:LP:AF:ID  0.00531532:0.0202382:0.10082:0.47382:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.0450772    ES:SE:LP:AF:ID  -0.037712:0.0497654:0.348166:0.0450772:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741354 ES:SE:LP:AF:ID  -0.0181075:0.023399:0.357522:0.741354:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275123 ES:SE:LP:AF:ID  -0.00267011:0.0240267:0.0402374:0.275123:rs1316988498
1   15903   rs557514207 G   GC  .   PASS    AF=0.418839 ES:SE:LP:AF:ID  -0.0036548:0.0198079:0.0687395:0.418839:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.95657  ES:SE:LP:AF:ID  0.0426652:0.0562507:0.348565:0.95657:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910222 ES:SE:LP:AF:ID  -0.007182:0.0373812:0.0717877:0.910222:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.0627122    ES:SE:LP:AF:ID  -0.021891:0.0427005:0.215964:0.0627122:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623769 ES:SE:LP:AF:ID  0.0133215:0.0237362:0.240604:0.623769:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.0929559    ES:SE:LP:AF:ID  -0.0267843:0.0365164:0.334174:0.0929559:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213261 ES:SE:LP:AF:ID  -0.0109207:0.0254269:0.175506:0.213261:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.15439  ES:SE:LP:AF:ID  0.00380134:0.0285535:0.0486188:0.15439:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400396 ES:SE:LP:AF:ID  -0.000886954:0.0235038:0.0132741:0.400396:rs2462492
1   54712   rs573184866 T   TTTTC   .   PASS    AF=0.585266 ES:SE:LP:AF:ID  0.00879583:0.0186184:0.196118:0.585266:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417369 ES:SE:LP:AF:ID  0.014407:0.0214778:0.298987:0.417369:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253778 ES:SE:LP:AF:ID  -0.0359831:0.0241683:0.864787:0.253778:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.0899991    ES:SE:LP:AF:ID  -0.0421569:0.036821:0.598177:0.0899991:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.0887901    ES:SE:LP:AF:ID  -0.0455775:0.0369295:0.663266:0.0887901:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.0809852    ES:SE:LP:AF:ID  -0.0351892:0.038317:0.445602:0.0809852:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438264 ES:SE:LP:AF:ID  -0.0144478:0.0204143:0.319562:0.438264:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382183 ES:SE:LP:AF:ID  -0.0202877:0.0219613:0.449044:0.382183:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158758 ES:SE:LP:AF:ID  -0.0688015:0.027928:1.86145:0.158758:rs80011619
1   63735   rs61158452  CCTA    C   .   PASS    AF=0.315972 ES:SE:LP:AF:ID  0.0164919:0.0217781:0.347861:0.315972:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.0795808    ES:SE:LP:AF:ID  -0.0360687:0.0388032:0.4527:0.0795808:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.0707815    ES:SE:LP:AF:ID  -0.00770986:0.0392961:0.0734239:0.0707815:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0329171    ES:SE:LP:AF:ID  -0.0556473:0.0594707:0.456649:0.0329171:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0738755    ES:SE:LP:AF:ID  0.00182371:0.0386804:0.0166466:0.0738755:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.75122  ES:SE:LP:AF:ID  0.0256645:0.0246645:0.525656:0.75122:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0340935    ES:SE:LP:AF:ID  -0.0941684:0.0565569:1.01814:0.0340935:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.0340935    ES:SE:LP:AF:ID  -0.0941684:0.0565569:1.01814:0.0340935:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.0771376    ES:SE:LP:AF:ID  -0.0429128:0.0394606:0.557799:0.0771376:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.0775039    ES:SE:LP:AF:ID  -0.0277825:0.0381794:0.330863:0.0775039:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.0769428    ES:SE:LP:AF:ID  -0.044448:0.0394703:0.58483:0.0769428:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.0769428    ES:SE:LP:AF:ID  -0.044448:0.0394703:0.58483:0.0769428:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.0414644    ES:SE:LP:AF:ID  0.107121:0.0550906:1.28533:0.0414644:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.0609442    ES:SE:LP:AF:ID  -0.016392:0.0418708:0.157743:0.0609442:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.0754483    ES:SE:LP:AF:ID  -0.0293118:0.038687:0.348091:0.0754483:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0754758    ES:SE:LP:AF:ID  -0.030205:0.0386808:0.361638:0.0754758:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352797 ES:SE:LP:AF:ID  0.0205878:0.0221157:0.453584:0.352797:rs201754587