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/9eb883da-9750-4252-9a21-d7d27a747562/call-ldsc/inputs/-261021501/ieu-b-5109.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5109/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Tue Aug 22 01:03:04 2023
Reading summary statistics from /data/cromwell-executions/qc/9eb883da-9750-4252-9a21-d7d27a747562/call-ldsc/inputs/-261021501/ieu-b-5109.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 Tue Aug 22 01:04:28 2023
Total time elapsed: 1.0m:24.66s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 62,
    "n_p_sig": 6543,
    "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 1.740000e-05 9.801200e-03 -0.1695870 -3.206600e-03 9.200000e-06 3.237900e-03 1.956500e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.815400e-03 6.552100e-03 0.0014525 2.385900e-03 3.831200e-03 8.842200e-03 1.045270e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.624836e-01 2.996854e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.624852e-01 2.996609e-01 0.0000000 1.931256e-01 4.495772e-01 7.223296e-01 9.999995e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594000e-01 3.020479e-01 0.0008640 1.659700e-02 1.145330e-01 4.379100e-01 9.992710e-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 -0.0007168 0.0030643 0.8200001 0.8150435 0.600398 NA NA
1 10352 rs1557426776 TA T -0.0041860 0.0031582 0.1900002 0.1850271 0.606887 NA NA
1 11008 rs575272151 C G 0.0063183 0.0052250 0.2300001 0.2265712 0.086636 0.0880591 NA
1 11012 rs544419019 C G 0.0063183 0.0052250 0.2300001 0.2265712 0.086636 0.0880591 NA
1 13110 rs540538026 G A -0.0043324 0.0069792 0.5300002 0.5347580 0.058763 0.0267572 NA
1 13116 rs62635286 T G 0.0012177 0.0041302 0.7700005 0.7681271 0.189426 0.0970447 NA
1 13118 rs200579949 A G 0.0012177 0.0041302 0.7700005 0.7681271 0.189426 0.0970447 NA
1 13273 rs531730856 G C -0.0013767 0.0048450 0.7800007 0.7762979 0.134052 0.0950479 NA
1 14464 rs546169444 A T -0.0026854 0.0044079 0.5400003 0.5423830 0.156877 0.0958466 NA
1 14599 rs531646671 T A 0.0035846 0.0040038 0.3700002 0.3706373 0.192112 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0039657 0.0016830 0.0179999 0.0184572 0.752537 0.643179 NA
23 154901964 rs697726 G A -0.0043592 0.0017720 0.0140001 0.0138907 0.348948 0.117616 NA
23 154902105 rs696316 G T -0.0039472 0.0016830 0.0189998 0.0190087 0.752516 0.636026 NA
23 154902889 rs697725 A T -0.0039483 0.0016824 0.0189998 0.0189362 0.752227 0.584106 NA
23 154903118 rs479770 G A -0.0039844 0.0016831 0.0179999 0.0179198 0.752565 0.643444 NA
23 154903224 rs480725 A T -0.0039846 0.0016831 0.0179999 0.0179163 0.752567 0.643444 NA
23 154903937 rs674707 G A -0.0039878 0.0016832 0.0179999 0.0178265 0.752572 0.643444 NA
23 154909055 rs473529 C G 0.0041354 0.0015840 0.0089999 0.0090364 0.303648 0.463046 NA
23 154918266 rs642043 C T 0.0042224 0.0015891 0.0079001 0.0078793 0.301538 0.478675 NA
23 154927581 rs644138 G A 0.0042302 0.0015893 0.0077999 0.0077766 0.301438 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.600398 ES:SE:LP:AF:ID  -0.00071682:0.00306432:0.0861861:0.600398:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606887 ES:SE:LP:AF:ID  -0.004186:0.00315821:0.721246:0.606887:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086636 ES:SE:LP:AF:ID  0.00631832:0.00522504:0.638272:0.086636:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086636 ES:SE:LP:AF:ID  0.00631832:0.00522504:0.638272:0.086636:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058763 ES:SE:LP:AF:ID  -0.00433241:0.00697921:0.275724:0.058763:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189426 ES:SE:LP:AF:ID  0.00121768:0.00413017:0.113509:0.189426:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189426 ES:SE:LP:AF:ID  0.00121768:0.00413017:0.113509:0.189426:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134052 ES:SE:LP:AF:ID  -0.00137668:0.00484496:0.107905:0.134052:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156877 ES:SE:LP:AF:ID  -0.00268537:0.00440793:0.267606:0.156877:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.192112 ES:SE:LP:AF:ID  0.00358455:0.00400383:0.431798:0.192112:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.192112 ES:SE:LP:AF:ID  0.00358455:0.00400383:0.431798:0.192112:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.47392  ES:SE:LP:AF:ID  -0.00390581:0.00310996:0.677781:0.47392:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045177 ES:SE:LP:AF:ID  0.00628671:0.00763188:0.387216:0.045177:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741562 ES:SE:LP:AF:ID  0.00512887:0.00359596:0.823909:0.741562:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275224 ES:SE:LP:AF:ID  0.00150625:0.00368467:0.167491:0.275224:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.580962 ES:SE:LP:AF:ID  0.00241947:0.00304034:0.366532:0.580962:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956505 ES:SE:LP:AF:ID  -0.00458361:0.00865275:0.221849:0.956505:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910179 ES:SE:LP:AF:ID  0.00396737:0.00573768:0.309804:0.910179:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.06271  ES:SE:LP:AF:ID  -0.00522405:0.00654625:0.376751:0.06271:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.624168 ES:SE:LP:AF:ID  -0.00321444:0.00363885:0.420216:0.624168:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092721 ES:SE:LP:AF:ID  0.00119102:0.00562501:0.0809219:0.092721:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.21337  ES:SE:LP:AF:ID  -0.00620722:0.00390247:0.958607:0.21337:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154503 ES:SE:LP:AF:ID  -0.0097793:0.00438483:1.58503:0.154503:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.399836 ES:SE:LP:AF:ID  0.0010583:0.00361321:0.113509:0.399836:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414629 ES:SE:LP:AF:ID  -0.00167441:0.00285383:0.251812:0.414629:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417698 ES:SE:LP:AF:ID  -0.00275583:0.00329682:0.39794:0.417698:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253743 ES:SE:LP:AF:ID  0.00396543:0.00370844:0.552842:0.253743:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089694 ES:SE:LP:AF:ID  0.000592631:0.00566798:0.0362122:0.089694:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088551 ES:SE:LP:AF:ID  0.00136615:0.00568495:0.091515:0.088551:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080724 ES:SE:LP:AF:ID  0.00231481:0.00589943:0.161151:0.080724:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438397 ES:SE:LP:AF:ID  0.00212605:0.00313231:0.30103:0.438397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381812 ES:SE:LP:AF:ID  0.00215861:0.00337155:0.283997:0.381812:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158418 ES:SE:LP:AF:ID  -0.00461722:0.00429032:0.552842:0.158418:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683588 ES:SE:LP:AF:ID  0.00222629:0.00334028:0.29243:0.683588:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079259 ES:SE:LP:AF:ID  0.00148098:0.00597836:0.09691:0.079259:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070676 ES:SE:LP:AF:ID  0.0113449:0.0060326:1.22185:0.070676:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032798 ES:SE:LP:AF:ID  -0.00527134:0.00917759:0.244125:0.032798:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073761 ES:SE:LP:AF:ID  0.00952624:0.00594272:0.958607:0.073761:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751649 ES:SE:LP:AF:ID  -0.00172621:0.003787:0.187087:0.751649:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034055 ES:SE:LP:AF:ID  0.00962622:0.00865871:0.568636:0.034055:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034055 ES:SE:LP:AF:ID  0.00962622:0.00865871:0.568636:0.034055:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.076952 ES:SE:LP:AF:ID  -0.000183784:0.00608417:0.00877392:0.076952:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077692 ES:SE:LP:AF:ID  -0.00565722:0.00584885:0.481486:0.077692:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076758 ES:SE:LP:AF:ID  0.000138386:0.00608528:0.00877392:0.076758:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076758 ES:SE:LP:AF:ID  0.000138386:0.00608528:0.00877392:0.076758:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041653 ES:SE:LP:AF:ID  -0.00135754:0.00840919:0.0604807:0.041653:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060777 ES:SE:LP:AF:ID  0.0138613:0.00643953:1.50864:0.060777:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075593 ES:SE:LP:AF:ID  -0.00524707:0.00592598:0.420216:0.075593:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075616 ES:SE:LP:AF:ID  -0.00533423:0.00592516:0.431798:0.075616:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352813 ES:SE:LP:AF:ID  -0.000439855:0.00339133:0.0457575:0.352813:rs201754587