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/f875ccfa-d371-4faf-8861-d66e6effe522/call-ldsc/inputs/-261044380/ieu-b-4868.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4868/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sun Jan  9 20:42:30 2022
Reading summary statistics from /data/cromwell-executions/qc/f875ccfa-d371-4faf-8861-d66e6effe522/call-ldsc/inputs/-261044380/ieu-b-4868.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 20:43:55 2022
Total time elapsed: 1.0m:25.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 85,
    "n_p_sig": 15163,
    "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 FALSE
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 1.402000e-04 1.544520e-02 -0.3472910 -4.840500e-03 1.490000e-05 4.937500e-03 3.196540e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.080090e-02 1.037870e-02 0.0023021 3.782000e-03 6.073300e-03 1.401620e-02 1.656000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.729211e-01 2.971140e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.729226e-01 2.970909e-01 0.0000000 2.094868e-01 4.644922e-01 7.305205e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594009e-01 3.020434e-01 0.0008490 1.660100e-02 1.145520e-01 4.378855e-01 9.992680e-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 0.0088575 0.0048605 0.0680002 0.0684055 0.600224 NA NA
1 10352 rs1557426776 TA T -0.0023115 0.0050097 0.6400000 0.6445087 0.606991 NA NA
1 11008 rs575272151 C G -0.0065583 0.0082889 0.4299995 0.4288225 0.086583 0.0880591 NA
1 11012 rs544419019 C G -0.0065583 0.0082889 0.4299995 0.4288225 0.086583 0.0880591 NA
1 13110 rs540538026 G A 0.0116345 0.0110862 0.2900000 0.2939674 0.058689 0.0267572 NA
1 13116 rs62635286 T G 0.0036969 0.0065499 0.5700002 0.5724713 0.189397 0.0970447 NA
1 13118 rs200579949 A G 0.0036969 0.0065499 0.5700002 0.5724713 0.189397 0.0970447 NA
1 13273 rs531730856 G C -0.0141186 0.0076864 0.0659994 0.0662355 0.134054 0.0950479 NA
1 14464 rs546169444 A T -0.0033698 0.0069872 0.6300007 0.6296082 0.157035 0.0958466 NA
1 14599 rs531646671 T A 0.0083854 0.0063520 0.1900002 0.1867947 0.192050 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0042008 0.0026671 0.1199999 0.1152481 0.752462 0.643179 NA
23 154901964 rs697726 G A -0.0049485 0.0028085 0.0779992 0.0780764 0.348724 0.117616 NA
23 154902105 rs696316 G T -0.0042158 0.0026670 0.1100001 0.1139431 0.752438 0.636026 NA
23 154902889 rs697725 A T -0.0043008 0.0026662 0.1100001 0.1067211 0.752150 0.584106 NA
23 154903118 rs479770 G A -0.0041685 0.0026673 0.1199999 0.1181035 0.752495 0.643444 NA
23 154903224 rs480725 A T -0.0041680 0.0026673 0.1199999 0.1181414 0.752497 0.643444 NA
23 154903937 rs674707 G A -0.0041660 0.0026674 0.1199999 0.1183249 0.752503 0.643444 NA
23 154909055 rs473529 C G 0.0050763 0.0025103 0.0430002 0.0431594 0.303752 0.463046 NA
23 154918266 rs642043 C T 0.0046111 0.0025182 0.0669993 0.0670847 0.301655 0.478675 NA
23 154927581 rs644138 G A 0.0046215 0.0025186 0.0669993 0.0665164 0.301551 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.600224 ES:SE:LP:AF:ID  0.00885747:0.00486053:1.16749:0.600224:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606991 ES:SE:LP:AF:ID  -0.00231151:0.00500973:0.19382:0.606991:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086583 ES:SE:LP:AF:ID  -0.00655827:0.00828893:0.366532:0.086583:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086583 ES:SE:LP:AF:ID  -0.00655827:0.00828893:0.366532:0.086583:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058689 ES:SE:LP:AF:ID  0.0116345:0.0110862:0.537602:0.058689:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189397 ES:SE:LP:AF:ID  0.00369686:0.00654989:0.244125:0.189397:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189397 ES:SE:LP:AF:ID  0.00369686:0.00654989:0.244125:0.189397:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134054 ES:SE:LP:AF:ID  -0.0141186:0.00768641:1.18046:0.134054:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157035 ES:SE:LP:AF:ID  -0.00336978:0.00698721:0.200659:0.157035:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.19205  ES:SE:LP:AF:ID  0.00838538:0.00635198:0.721246:0.19205:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.19205  ES:SE:LP:AF:ID  0.00838538:0.00635198:0.721246:0.19205:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473903 ES:SE:LP:AF:ID  0.000597842:0.00493318:0.0457575:0.473903:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045083 ES:SE:LP:AF:ID  -0.010743:0.0121151:0.420216:0.045083:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741661 ES:SE:LP:AF:ID  0.00218001:0.00570339:0.154902:0.741661:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275103 ES:SE:LP:AF:ID  -0.00428027:0.00584702:0.337242:0.275103:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.580834 ES:SE:LP:AF:ID  -0.0016321:0.00482167:0.136677:0.580834:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956559 ES:SE:LP:AF:ID  -0.00292764:0.0137481:0.0809219:0.956559:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910101 ES:SE:LP:AF:ID  0.0144036:0.00908357:0.958607:0.910101:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062688 ES:SE:LP:AF:ID  0.0121878:0.0103739:0.619789:0.062688:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.624026 ES:SE:LP:AF:ID  0.000703554:0.00577569:0.0457575:0.624026:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092728 ES:SE:LP:AF:ID  0.0155429:0.00892798:1.08619:0.092728:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213521 ES:SE:LP:AF:ID  0.0034056:0.0061853:0.236572:0.213521:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154686 ES:SE:LP:AF:ID  0.00377658:0.00694359:0.229148:0.154686:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.399673 ES:SE:LP:AF:ID  -0.00316977:0.00573569:0.236572:0.399673:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414539 ES:SE:LP:AF:ID  0.00244494:0.00452502:0.229148:0.414539:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417767 ES:SE:LP:AF:ID  -0.00804521:0.00522925:0.920819:0.417767:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253726 ES:SE:LP:AF:ID  0.000728194:0.00587916:0.0457575:0.253726:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.08969  ES:SE:LP:AF:ID  0.0105546:0.00899577:0.619789:0.08969:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088511 ES:SE:LP:AF:ID  0.0168055:0.0090292:1.20066:0.088511:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080724 ES:SE:LP:AF:ID  0.0198197:0.00936548:1.46852:0.080724:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438115 ES:SE:LP:AF:ID  -0.000195212:0.00496788:0.0132283:0.438115:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.38146  ES:SE:LP:AF:ID  -0.00327138:0.00534784:0.267606:0.38146:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158372 ES:SE:LP:AF:ID  0.0123769:0.00680881:1.16115:0.158372:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683646 ES:SE:LP:AF:ID  -0.00962764:0.00529831:1.16115:0.683646:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079294 ES:SE:LP:AF:ID  0.0193239:0.00948793:1.37675:0.079294:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070861 ES:SE:LP:AF:ID  0.00706091:0.00956626:0.337242:0.070861:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032834 ES:SE:LP:AF:ID  -0.012168:0.0145451:0.39794:0.032834:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073895 ES:SE:LP:AF:ID  0.00918306:0.00942629:0.481486:0.073895:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751584 ES:SE:LP:AF:ID  0.00275721:0.00600597:0.187087:0.751584:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034071 ES:SE:LP:AF:ID  0.0053677:0.0137312:0.154902:0.034071:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034071 ES:SE:LP:AF:ID  0.0053677:0.0137312:0.154902:0.034071:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.076955 ES:SE:LP:AF:ID  0.0120672:0.00966016:0.677781:0.076955:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077675 ES:SE:LP:AF:ID  -0.0102307:0.0092698:0.568636:0.077675:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076759 ES:SE:LP:AF:ID  0.0123161:0.00966217:0.69897:0.076759:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076759 ES:SE:LP:AF:ID  0.0123161:0.00966217:0.69897:0.076759:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041576 ES:SE:LP:AF:ID  -0.0130962:0.0133653:0.481486:0.041576:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060966 ES:SE:LP:AF:ID  0.0101709:0.0101991:0.49485:0.060966:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075588 ES:SE:LP:AF:ID  -0.00756387:0.00939039:0.376751:0.075588:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075605 ES:SE:LP:AF:ID  -0.00781441:0.00938965:0.387216:0.075605:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352602 ES:SE:LP:AF:ID  -0.00567553:0.00538039:0.537602:0.352602:rs201754587