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/c9bc7737-81d2-4440-be20-58923b4110fe/call-ldsc/inputs/-261044379/ieu-b-4869.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4869/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sun Jan  9 20:41:00 2022
Reading summary statistics from /data/cromwell-executions/qc/c9bc7737-81d2-4440-be20-58923b4110fe/call-ldsc/inputs/-261044379/ieu-b-4869.vcf.gz ...
Read summary statistics for 0 SNPs.
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.
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
    sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
  File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
    raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.

Analysis finished at Sun Jan  9 20:42:24 2022
Total time elapsed: 1.0m:24.21s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 125,
    "n_p_sig": 12806,
    "n_mono": 0,
    "n_ns": 1293897,
    "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": 1423040,
    "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": 0,
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq NA
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 675 0.9999452 3 58 0 12276232 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 17566 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 71704 0 NA NA NA NA NA NA NA NA NA NA
logical N 12321875 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 8.757492e+00 5.885387e+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 7.871202e+07 5.622121e+07 302.0000000 3.252510e+07 6.928045e+07 1.144492e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.740000e-05 1.579420e-02 -0.4696790 -5.070800e-03 9.000000e-07 5.136300e-03 6.381220e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.092800e-02 1.048820e-02 0.0031594 3.828500e-03 6.143500e-03 1.417300e-02 1.728980e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.655776e-01 2.990104e-01 0.0000000 2.000000e-01 4.500005e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.655799e-01 2.989870e-01 0.0000000 1.983075e-01 4.536359e-01 7.251377e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594004e-01 3.020433e-01 0.0008370 1.659800e-02 1.145790e-01 4.379270e-01 9.991610e-01 ▇▂▁▁▁
numeric AF_reference 1423040 0.8845111 NA NA NA NA NA NA NA 2.132160e-01 2.513550e-01 0.0000000 1.218050e-02 1.056310e-01 3.376600e-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 -0.0026317 0.0048930 0.5900000 0.5906748 0.601125 NA NA
1 10352 rs1557426776 TA T 0.0008619 0.0050427 0.8600001 0.8642856 0.606522 NA NA
1 11008 rs575272151 C G 0.0071103 0.0084011 0.4000000 0.3973588 0.086182 0.0880591 NA
1 11012 rs544419019 C G 0.0071103 0.0084011 0.4000000 0.3973588 0.086182 0.0880591 NA
1 13110 rs540538026 G A -0.0029817 0.0111850 0.7899998 0.7897931 0.058354 0.0267572 NA
1 13116 rs62635286 T G -0.0086176 0.0066031 0.1900002 0.1918662 0.189109 0.0970447 NA
1 13118 rs200579949 A G -0.0086176 0.0066031 0.1900002 0.1918662 0.189109 0.0970447 NA
1 13273 rs531730856 G C -0.0045045 0.0077100 0.5600000 0.5590520 0.134337 0.0950479 NA
1 14464 rs546169444 A T 0.0067232 0.0070369 0.3400001 0.3393658 0.156772 0.0958466 NA
1 14599 rs531646671 T A -0.0116899 0.0064106 0.0680002 0.0682254 0.191371 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0049844 0.0038073 0.1900002 0.1904794 0.751039 0.643179 NA
23 154901964 rs697726 G A 0.0062517 0.0040255 0.1199999 0.1204149 0.347304 0.117616 NA
23 154902105 rs696316 G T 0.0050018 0.0038070 0.1900002 0.1888980 0.750967 0.636026 NA
23 154902889 rs697725 A T 0.0054457 0.0038058 0.1499999 0.1524635 0.750638 0.584106 NA
23 154903118 rs479770 G A 0.0050662 0.0038079 0.1800002 0.1833727 0.751099 0.643444 NA
23 154903224 rs480725 A T 0.0050680 0.0038079 0.1800002 0.1832208 0.751102 0.643444 NA
23 154903937 rs674707 G A 0.0050725 0.0038081 0.1800002 0.1828483 0.751115 0.643444 NA
23 154909055 rs473529 C G -0.0058985 0.0035853 0.1000000 0.0999295 0.305956 0.463046 NA
23 154918266 rs642043 C T -0.0058761 0.0035965 0.1000000 0.1022937 0.303834 0.478675 NA
23 154927581 rs644138 G A -0.0057477 0.0035972 0.1100001 0.1100791 0.303685 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601125 ES:SE:LP:AF:ID  -0.00263172:0.00489296:0.229148:0.601125:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606522 ES:SE:LP:AF:ID  0.000861907:0.00504271:0.0655015:0.606522:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086182 ES:SE:LP:AF:ID  0.00711026:0.00840111:0.39794:0.086182:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086182 ES:SE:LP:AF:ID  0.00711026:0.00840111:0.39794:0.086182:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058354 ES:SE:LP:AF:ID  -0.00298169:0.011185:0.102373:0.058354:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189109 ES:SE:LP:AF:ID  -0.00861755:0.00660309:0.721246:0.189109:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189109 ES:SE:LP:AF:ID  -0.00861755:0.00660309:0.721246:0.189109:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134337 ES:SE:LP:AF:ID  -0.00450454:0.00770995:0.251812:0.134337:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156772 ES:SE:LP:AF:ID  0.00672317:0.00703688:0.468521:0.156772:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191371 ES:SE:LP:AF:ID  -0.0116899:0.00641064:1.16749:0.191371:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191371 ES:SE:LP:AF:ID  -0.0116899:0.00641064:1.16749:0.191371:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473931 ES:SE:LP:AF:ID  0.00581325:0.00496316:0.619789:0.473931:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045024 ES:SE:LP:AF:ID  -0.0188071:0.012237:0.920819:0.045024:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741078 ES:SE:LP:AF:ID  -0.00686861:0.00573827:0.638272:0.741078:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.2751   ES:SE:LP:AF:ID  0.000756107:0.00589598:0.0457575:0.2751:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581483 ES:SE:LP:AF:ID  0.00465525:0.00485154:0.468521:0.581483:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956615 ES:SE:LP:AF:ID  0.0141876:0.0138368:0.508638:0.956615:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910671 ES:SE:LP:AF:ID  -0.0212571:0.0092087:1.67778:0.910671:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062699 ES:SE:LP:AF:ID  0.00465383:0.010468:0.180456:0.062699:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623354 ES:SE:LP:AF:ID  0.000291041:0.00583478:0.0177288:0.623354:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.09333  ES:SE:LP:AF:ID  0.000864168:0.0089429:0.0362122:0.09333:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.21277  ES:SE:LP:AF:ID  -0.00216067:0.00624084:0.136677:0.21277:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154029 ES:SE:LP:AF:ID  -0.00339483:0.00701074:0.200659:0.154029:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.40084  ES:SE:LP:AF:ID  0.00736632:0.00576652:0.69897:0.40084:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414202 ES:SE:LP:AF:ID  0.00222083:0.00457103:0.200659:0.414202:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417586 ES:SE:LP:AF:ID  0.00360351:0.00527001:0.309804:0.417586:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253984 ES:SE:LP:AF:ID  0.00462373:0.00593076:0.356547:0.253984:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090377 ES:SE:LP:AF:ID  -1.71784e-05:0.00901817:-0:0.090377:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.089176 ES:SE:LP:AF:ID  -0.00128507:0.00906037:0.05061:0.089176:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081357 ES:SE:LP:AF:ID  -0.00268562:0.00939395:0.113509:0.081357:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438094 ES:SE:LP:AF:ID  -0.00189006:0.00501891:0.148742:0.438094:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382515 ES:SE:LP:AF:ID  0.00146843:0.00538205:0.107905:0.382515:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.159062 ES:SE:LP:AF:ID  -0.00047275:0.00686166:0.0222764:0.159062:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684236 ES:SE:LP:AF:ID  -0.00344689:0.00535003:0.283997:0.684236:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079958 ES:SE:LP:AF:ID  -0.00204231:0.00950189:0.0809219:0.079958:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070856 ES:SE:LP:AF:ID  -0.00278205:0.00965903:0.113509:0.070856:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032804 ES:SE:LP:AF:ID  -0.000275228:0.0146236:0.00877392:0.032804:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073984 ES:SE:LP:AF:ID  -0.000184117:0.00949873:0.00877392:0.073984:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751099 ES:SE:LP:AF:ID  -0.00652478:0.00605554:0.552842:0.751099:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034181 ES:SE:LP:AF:ID  -0.00855989:0.0138467:0.267606:0.034181:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034181 ES:SE:LP:AF:ID  -0.00855989:0.0138467:0.267606:0.034181:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077382 ES:SE:LP:AF:ID  -0.000954398:0.00969482:0.0362122:0.077382:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.07718  ES:SE:LP:AF:ID  0.00333751:0.00939492:0.142668:0.07718:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.07719  ES:SE:LP:AF:ID  -0.000876367:0.00969775:0.0315171:0.07719:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.07719  ES:SE:LP:AF:ID  -0.000876367:0.00969775:0.0315171:0.07719:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041459 ES:SE:LP:AF:ID  0.00429689:0.0135868:0.124939:0.041459:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060965 ES:SE:LP:AF:ID  8.11922e-05:0.0102869:0.00436481:0.060965:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075182 ES:SE:LP:AF:ID  0.000223293:0.00951151:0.00877392:0.075182:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075226 ES:SE:LP:AF:ID  -0.000200139:0.00950764:0.00877392:0.075226:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.35297  ES:SE:LP:AF:ID  -0.00409018:0.00543066:0.346787:0.35297:rs201754587