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/08c38b4c-7aa9-45cc-bf3c-55ca8b371c34/call-ldsc/inputs/-261044386/ieu-b-4862.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4862/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Jan  6 21:39:19 2022
Reading summary statistics from /data/cromwell-executions/qc/08c38b4c-7aa9-45cc-bf3c-55ca8b371c34/call-ldsc/inputs/-261044386/ieu-b-4862.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 Thu Jan  6 21:41:12 2022
Total time elapsed: 1.0m:52.95s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9559,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 17070463,
    "n_clumped_hits": 36,
    "n_p_sig": 5074,
    "n_mono": 0,
    "n_ns": 1707977,
    "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": 2358076,
    "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 2097 0.9998772 3 64 0 16993268 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 22111 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 96742 0 NA NA NA NA NA NA NA NA NA NA
logical N 17070463 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 9.159987e+00 6.261419e+00 1.0000000 4.000000e+00 8.000000e+00 1.400000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.868952e+07 5.593951e+07 173.0000000 3.262854e+07 6.958619e+07 1.145816e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.950000e-05 3.335190e-02 -0.5807550 -8.792400e-03 -2.120000e-05 8.751600e-03 5.032000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.387780e-02 2.257780e-02 0.0028116 5.238500e-03 1.313130e-02 3.954020e-02 3.028720e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.734139e-01 2.963430e-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 4.735909e-01 2.962524e-01 0.0000000 2.101299e-01 4.652300e-01 7.300994e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.117709e-01 3.041824e-01 0.0010000 3.406000e-03 3.696500e-02 3.272340e-01 9.990000e-01 ▇▁▁▁▁
numeric AF_reference 2358076 0.8618622 NA NA NA NA NA NA NA 1.608704e-01 2.360828e-01 0.0000000 1.397800e-03 3.494410e-02 2.356230e-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 0.0028748 0.0059386 0.6499995 0.6283192 0.6012540 NA NA
1 10352 rs1557426776 TA T -0.0007154 0.0061192 0.8700001 0.9069357 0.6073980 NA NA
1 10511 rs534229142 G A 0.0488699 0.0849115 0.6100002 0.5649267 0.0012510 0.0001997 NA
1 10616 rs1557426951 C CCGCCGTTGCAAAGGCGCGCCG 0.0220388 0.0387658 0.5500004 0.5696878 0.0057758 NA NA
1 11008 rs575272151 C G -0.0079044 0.0101348 0.4199997 0.4354323 0.0863320 0.0880591 NA
1 11012 rs544419019 C G -0.0079044 0.0101348 0.4199997 0.4354323 0.0863320 0.0880591 NA
1 13110 rs540538026 G A -0.0095305 0.0134869 0.4600002 0.4797830 0.0590000 0.0267572 NA
1 13116 rs62635286 T G 0.0276869 0.0080073 0.0007300 0.0005448 0.1892190 0.0970447 NA
1 13118 rs200579949 A G 0.0276869 0.0080073 0.0007300 0.0005448 0.1892190 0.0970447 NA
1 13273 rs531730856 G C -0.0017748 0.0093857 0.8700001 0.8500176 0.1340780 0.0950479 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154927199 rs645904 C T 0.0141898 0.0047884 0.0024000 0.0030430 0.135869 0.3674170 NA
23 154927201 rs778081536 C T -0.0035548 0.0252297 0.8900000 0.8879507 0.004233 0.0068874 NA
23 154927581 rs644138 G A 0.0046722 0.0030758 0.1100001 0.1287506 0.301696 0.4635760 NA
23 154928151 rs144607509 C T -0.0013358 0.0127969 0.9500000 0.9168641 0.020223 0.0084768 NA
23 154928676 rs190885471 A G 0.0686895 0.0460498 0.1299999 0.1357948 0.001641 0.0063576 NA
23 154929412 rs557132 C T 0.0102171 0.0032735 0.0014000 0.0018016 0.245131 0.3568210 NA
23 154929637 rs35185538 C CT -0.0087999 0.0034174 0.0075999 0.0100220 0.770904 NA NA
23 154929952 rs4012982 C CAA -0.0104861 0.0034401 0.0018000 0.0023025 0.760508 NA NA
23 154930230 rs781880 A G 0.0100538 0.0032722 0.0017000 0.0021227 0.245657 0.3618540 NA
23 154930487 rs781879 T A 0.0220772 0.0111542 0.0430002 0.0477853 0.019758 0.1263580 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601254 ES:SE:LP:AF:ID  0.00287485:0.00593862:0.187087:0.601254:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607398 ES:SE:LP:AF:ID  -0.000715362:0.0061192:0.0604807:0.607398:rs1557426776
1   10511   rs534229142 G   A   .   PASS    AF=0.001251 ES:SE:LP:AF:ID  0.0488699:0.0849115:0.21467:0.001251:rs534229142
1   10616   rs1557426951    C   CCGCCGTTGCAAAGGCGCGCCG  .   PASS    AF=0.00577577   ES:SE:LP:AF:ID  0.0220388:0.0387658:0.259637:0.00577577:rs1557426951
1   11008   rs575272151 C   G   .   PASS    AF=0.086332 ES:SE:LP:AF:ID  -0.00790443:0.0101348:0.376751:0.086332:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086332 ES:SE:LP:AF:ID  -0.00790443:0.0101348:0.376751:0.086332:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.059    ES:SE:LP:AF:ID  -0.00953054:0.0134869:0.337242:0.059:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189219 ES:SE:LP:AF:ID  0.0276869:0.00800727:3.13668:0.189219:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189219 ES:SE:LP:AF:ID  0.0276869:0.00800727:3.13668:0.189219:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134078 ES:SE:LP:AF:ID  -0.00177479:0.00938566:0.0604807:0.134078:rs531730856
1   13289   rs538791886 C   CCT .   PASS    AF=0.996173 ES:SE:LP:AF:ID  0.0904714:0.0584495:0.920819:0.996173:rs538791886
1   13453   rs568927457 T   C   .   PASS    AF=0.006555 ES:SE:LP:AF:ID  -0.0279664:0.0358697:0.346787:0.006555:rs568927457
1   13483   rs554760071 G   C   .   PASS    AF=0.004981 ES:SE:LP:AF:ID  -0.0182264:0.0400632:0.180456:0.004981:rs554760071
1   13494   rs1272445563    A   G   .   PASS    AF=0.003439 ES:SE:LP:AF:ID  -0.0264102:0.0591429:0.173925:0.003439:rs1272445563
1   13550   rs554008981 G   A   .   PASS    AF=0.004841 ES:SE:LP:AF:ID  0.0153217:0.047899:0.102373:0.004841:rs554008981
1   14464   rs546169444 A   T   .   PASS    AF=0.157446 ES:SE:LP:AF:ID  -0.00586959:0.00851045:0.337242:0.157446:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191758 ES:SE:LP:AF:ID  0.0116524:0.00776045:0.886057:0.191758:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191758 ES:SE:LP:AF:ID  0.0116524:0.00776045:0.886057:0.191758:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474065 ES:SE:LP:AF:ID  -0.00683351:0.00602174:0.585027:0.474065:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.04526  ES:SE:LP:AF:ID  0.00653144:0.0147521:0.161151:0.04526:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741865 ES:SE:LP:AF:ID  0.00674593:0.00696837:0.420216:0.741865:rs3982632
1   15245   rs576044687 C   T   .   PASS    AF=0.001159 ES:SE:LP:AF:ID  0.0606803:0.0909493:0.327902:0.001159:rs576044687
1   15585   rs533630043 G   A   .   PASS    AF=0.008157 ES:SE:LP:AF:ID  0.0865591:0.0357371:1.85387:0.008157:rs533630043
1   15644   rs564003018 G   A   .   PASS    AF=0.004353 ES:SE:LP:AF:ID  -0.0289327:0.052068:0.200659:0.004353:rs564003018
1   15774   rs374029747 G   A   .   PASS    AF=0.007167 ES:SE:LP:AF:ID  -0.0602064:0.043087:0.69897:0.007167:rs374029747
1   15777   rs2691317   A   G   .   PASS    AF=0.016792 ES:SE:LP:AF:ID  0.00271216:0.0262879:0.0655015:0.016792:rs2691317
1   15820   rs1316988498    G   T   .   PASS    AF=0.274796 ES:SE:LP:AF:ID  -0.00305339:0.00714021:0.161151:0.274796:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581857 ES:SE:LP:AF:ID  0.00969559:0.00588868:0.958607:0.581857:rs557514207
1   16142   rs548165136 G   A   .   PASS    AF=0.003932 ES:SE:LP:AF:ID  0.0418406:0.0515388:0.39794:0.003932:rs548165136
1   16949   rs199745162 A   C   .   PASS    AF=0.018894 ES:SE:LP:AF:ID  0.0385545:0.0212393:1.12494:0.018894:rs199745162
1   18643   rs564023708 G   A   .   PASS    AF=0.006286 ES:SE:LP:AF:ID  -0.0607164:0.0382605:0.958607:0.006286:rs564023708
1   18849   rs533090414 C   G   .   PASS    AF=0.975708 ES:SE:LP:AF:ID  0.0121098:0.0180858:0.236572:0.975708:rs533090414
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956678 ES:SE:LP:AF:ID  -0.00968979:0.0168411:0.283997:0.956678:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910321 ES:SE:LP:AF:ID  0.0196152:0.0111249:1.01323:0.910321:rs1165072081
1   46285   rs545414834 A   ATAT    .   PASS    AF=0.997902 ES:SE:LP:AF:ID  -0.00912463:0.0667082:0.0457575:0.997902:rs545414834
1   47159   rs540662756 T   C   .   PASS    AF=0.063013 ES:SE:LP:AF:ID  -0.00934536:0.0126303:0.318759:0.063013:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623944 ES:SE:LP:AF:ID  0.00386842:0.00704587:0.267606:0.623944:rs10399793
1   49315   rs1231347385    T   A   .   PASS    AF=0.001231 ES:SE:LP:AF:ID  0.0773795:0.0975299:0.309804:0.001231:rs1231347385
1   49318   rs1231347385    A   G   .   PASS    AF=0.00142  ES:SE:LP:AF:ID  -0.0655808:0.0717563:0.468521:0.00142:rs1231347385
1   49343   rs553572247 T   C   .   PASS    AF=0.001598 ES:SE:LP:AF:ID  -0.188951:0.0767346:1.85387:0.001598:rs553572247
1   49554   rs539322794 A   G   .   PASS    AF=0.0927   ES:SE:LP:AF:ID  0.00791466:0.0108979:0.30103:0.0927:rs539322794
1   50891   rs542415070 T   C   .   PASS    AF=0.004623 ES:SE:LP:AF:ID  -0.0710454:0.0476436:0.886057:0.004623:rs542415070
1   51047   rs559500163 A   T   .   PASS    AF=0.001659 ES:SE:LP:AF:ID  0.0779755:0.0759626:0.60206:0.001659:rs559500163
1   51049   rs528344458 A   C   .   PASS    AF=0.001659 ES:SE:LP:AF:ID  0.0779755:0.0759626:0.60206:0.001659:rs528344458
1   51050   rs551668143 A   T   .   PASS    AF=0.001659 ES:SE:LP:AF:ID  0.0779755:0.0759626:0.60206:0.001659:rs551668143
1   51053   rs565211799 G   T   .   PASS    AF=0.001659 ES:SE:LP:AF:ID  0.0779755:0.0759626:0.60206:0.001659:rs565211799
1   51479   rs116400033 T   A   .   PASS    AF=0.213777 ES:SE:LP:AF:ID  0.0100678:0.0075449:0.721246:0.213777:rs116400033
1   51762   rs1359003408    A   G   .   PASS    AF=0.009404 ES:SE:LP:AF:ID  0.0112459:0.0318914:0.148742:0.009404:rs1359003408
1   51765   rs1359003408    C   G   .   PASS    AF=0.009237 ES:SE:LP:AF:ID  0.0127687:0.0319482:0.173925:0.009237:rs1359003408
1   52152   rs1272293782    A   ATAAT   .   PASS    AF=0.998295 ES:SE:LP:AF:ID  0.0355078:0.0852969:0.161151:0.998295:rs1272293782