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/33cfc6f2-a71c-42b6-9e5b-8efae2485e6e/call-ldsc/inputs/-261043388/ieu-b-4978.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4978/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Apr 23 02:13:08 2022
Reading summary statistics from /data/cromwell-executions/qc/33cfc6f2-a71c-42b6-9e5b-8efae2485e6e/call-ldsc/inputs/-261043388/ieu-b-4978.vcf.gz ...
Read summary statistics for 12242396 SNPs.
Dropped 231278 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: 0.0014 (0.0011)
Lambda GC: 1.0099
Mean Chi^2: 1.0116
Intercept: 0.9993 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Sat Apr 23 02:14:59 2022
Total time elapsed: 1.0m:50.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9501,
    "inflation_factor": 1.0129,
    "mean_EFFECT": -0.0009,
    "n": "-Inf",
    "n_snps": 12243396,
    "n_clumped_hits": 0,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1279881,
    "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": 404119,
    "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": 0.0014,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 0.9993,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0099,
    "ldsc_mean_chisq": 1.0116,
    "ldsc_ratio": -0.0603
}

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 12193968 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 12243396 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 5.758639e+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 5.629935e+07 302.0000000 3.250309e+07 6.911917e+07 1.143453e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -8.628000e-04 1.658600e-01 -49.9728000 -3.950410e-02 -6.795000e-04 3.760970e-02 5.592560e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.710680e-02 1.698637e-01 0.0268059 3.254990e-02 5.262380e-02 1.214780e-01 4.488720e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.979829e-01 2.891926e-01 0.0000000 2.464433e-01 4.972520e-01 7.489210e-01 9.999999e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.979829e-01 2.891926e-01 0.0000000 2.464432e-01 4.972522e-01 7.489210e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.128003e-01 2.601903e-01 0.0000061 1.458450e-02 8.853000e-02 3.382490e-01 9.999930e-01 ▇▂▁▁▁
numeric AF_reference 404119 0.9669929 NA NA NA NA NA NA NA 2.160796e-01 2.512171e-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 0.0115966 0.0414808 0.7798104 0.7798109 0.3989430 0.4253190 NA
1 10352 rs555500075 T TA -0.0113632 0.0427219 0.7902545 0.7902541 0.3930400 0.4375000 NA
1 11008 rs575272151 C G -0.0384615 0.0705799 0.5857968 0.5857978 0.0863651 0.0880591 NA
1 11012 rs544419019 C G -0.0384615 0.0705799 0.5857968 0.5857978 0.0863651 0.0880591 NA
1 13110 rs540538026 G A 0.0464028 0.0947783 0.6244217 0.6244219 0.0586161 0.0267572 NA
1 13116 rs62635286 T G -0.0766389 0.0559755 0.1709523 0.1709521 0.1890610 0.0970447 NA
1 13118 rs200579949 A G -0.0766389 0.0559755 0.1709523 0.1709521 0.1890610 0.0970447 NA
1 13273 rs531730856 G C 0.0510484 0.0654892 0.4356884 0.4356891 0.1341500 0.0950479 NA
1 14464 rs546169444 A T -0.0525182 0.0594260 0.3768279 0.3768269 0.1568120 0.0958466 NA
1 14599 rs531646671 T A 0.0264643 0.0541832 0.6252504 0.6252505 0.1914280 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233182 rs4040317 G A 0.0777245 0.0338311 0.0215943 0.0215944 0.3197730 0.2633790 NA
22 51233300 rs9616839 C T 0.0587339 0.0337794 0.0820786 0.0820789 0.3336920 0.3146960 NA
22 51233312 rs62240043 A G 0.0737987 0.0355728 0.0380251 0.0380253 0.2724880 0.2134580 NA
22 51233347 rs62240044 T C 0.0737987 0.0355728 0.0380251 0.0380253 0.2724880 0.2134580 NA
22 51234799 rs191117135 G A -0.0928969 0.1249710 0.4572724 0.4572712 0.0158080 0.0059904 NA
22 51235959 rs200189535 T C -0.0371415 0.0415167 0.3709924 0.3709924 0.1956440 0.1996810 NA
22 51235979 rs62240045 G A 0.0493950 0.0461928 0.2849240 0.2849244 0.2634720 0.2400160 NA
22 51236013 rs200507571 A AT 0.0122889 0.0358152 0.7315095 0.7315084 0.2512440 0.1487620 NA
22 51237063 rs3896457 T C 0.0790562 0.0327412 0.0157536 0.0157534 0.2979830 0.2050720 NA
22 51237712 rs370652263 G A -0.1041180 0.0654065 0.1114177 0.1114161 0.0554577 0.0690895 NA

bcf preview

1   10177   rs1264289758    A   AC  .   PASS    AF=0.398943 ES:SE:LP:AF:ID  0.0115966:0.0414808:0.108011:0.398943:rs1264289758
1   10352   rs1557426776    T   TA  .   PASS    AF=0.39304  ES:SE:LP:AF:ID  -0.0113632:0.0427219:0.102233:0.39304:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.0863651    ES:SE:LP:AF:ID  -0.0384615:0.0705799:0.232253:0.0863651:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.0863651    ES:SE:LP:AF:ID  -0.0384615:0.0705799:0.232253:0.0863651:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.0586161    ES:SE:LP:AF:ID  0.0464028:0.0947783:0.204522:0.0586161:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189061 ES:SE:LP:AF:ID  -0.0766389:0.0559755:0.767125:0.189061:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189061 ES:SE:LP:AF:ID  -0.0766389:0.0559755:0.767125:0.189061:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13415  ES:SE:LP:AF:ID  0.0510484:0.0654892:0.360824:0.13415:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156812 ES:SE:LP:AF:ID  -0.0525182:0.059426:0.423857:0.156812:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191428 ES:SE:LP:AF:ID  0.0264643:0.0541832:0.203946:0.191428:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191428 ES:SE:LP:AF:ID  0.0264643:0.0541832:0.203946:0.191428:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474471 ES:SE:LP:AF:ID  0.00760552:0.0419987:0.0673754:0.474471:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.0448431    ES:SE:LP:AF:ID  0.0499593:0.103367:0.20144:0.0448431:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.740981 ES:SE:LP:AF:ID  -0.0321299:0.0487268:0.292732:0.740981:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275358 ES:SE:LP:AF:ID  -0.0703451:0.0497542:0.802981:0.275358:rs1316988498
1   15903   rs557514207 G   GC  .   PASS    AF=0.418903 ES:SE:LP:AF:ID  -0.00703734:0.0411406:0.0633958:0.418903:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956694 ES:SE:LP:AF:ID  0.13759:0.117414:0.617511:0.956694:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910086 ES:SE:LP:AF:ID  -0.0540515:0.0778687:0.311939:0.910086:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.0628754    ES:SE:LP:AF:ID  0.000475536:0.0881795:0.00187272:0.0628754:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.624138 ES:SE:LP:AF:ID  -0.0233815:0.0492504:0.197248:0.624138:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.0930177    ES:SE:LP:AF:ID  0.147765:0.0758156:1.28993:0.0930177:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213359 ES:SE:LP:AF:ID  -0.0594089:0.0526906:0.585813:0.213359:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154366 ES:SE:LP:AF:ID  -0.0357429:0.0591024:0.263335:0.154366:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400197 ES:SE:LP:AF:ID  0.0543079:0.0488977:0.573942:0.400197:rs2462492
1   54712   rs573184866 T   TTTTC   .   PASS    AF=0.584992 ES:SE:LP:AF:ID  -0.00504623:0.0386893:0.0475823:0.584992:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.416967 ES:SE:LP:AF:ID  0.064398:0.0446306:0.826682:0.416967:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253628 ES:SE:LP:AF:ID  0.0452337:0.0501541:0.435201:0.253628:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089982 ES:SE:LP:AF:ID  0.121656:0.0764658:0.952287:0.089982:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.0887216    ES:SE:LP:AF:ID  0.15432:0.0768353:1.35072:0.0887216:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.0809189    ES:SE:LP:AF:ID  0.132278:0.0796499:1.01429:0.0809189:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.437735 ES:SE:LP:AF:ID  -0.0470277:0.0424156:0.572604:0.437735:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381703 ES:SE:LP:AF:ID  0.0352707:0.0455743:0.357555:0.381703:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158572 ES:SE:LP:AF:ID  0.0891894:0.0579317:0.907746:0.158572:rs80011619
1   63735   rs61158452  CCTA    C   .   PASS    AF=0.316293 ES:SE:LP:AF:ID  -0.0340748:0.0452188:0.345711:0.316293:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.07951  ES:SE:LP:AF:ID  0.12856:0.0806608:0.954785:0.07951:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.0706186    ES:SE:LP:AF:ID  -0.0581456:0.0819912:0.320373:0.0706186:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0325994    ES:SE:LP:AF:ID  0.0556574:0.124038:0.184662:0.0325994:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0736849    ES:SE:LP:AF:ID  -0.0379132:0.0806133:0.195088:0.0736849:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751157 ES:SE:LP:AF:ID  -0.0610402:0.0511732:0.632752:0.751157:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0342591    ES:SE:LP:AF:ID  -0.151417:0.116937:0.709143:0.0342591:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.0342591    ES:SE:LP:AF:ID  -0.151417:0.116937:0.709143:0.0342591:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.0771777    ES:SE:LP:AF:ID  0.155541:0.0820394:1.2368:0.0771777:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.0776044    ES:SE:LP:AF:ID  0.0451484:0.079178:0.245245:0.0776044:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.0769797    ES:SE:LP:AF:ID  0.15731:0.08206:1.25777:0.0769797:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.0769797    ES:SE:LP:AF:ID  0.15731:0.08206:1.25777:0.0769797:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.0415022    ES:SE:LP:AF:ID  0.262901:0.115218:1.64777:0.0415022:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.0608357    ES:SE:LP:AF:ID  -0.083221:0.0873399:0.467665:0.0608357:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.0755592    ES:SE:LP:AF:ID  0.0289931:0.0801186:0.144212:0.0755592:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075589 ES:SE:LP:AF:ID  0.0331152:0.0801016:0.167937:0.075589:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352949 ES:SE:LP:AF:ID  0.0377764:0.0459263:0.386404:0.352949:rs201754587