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/fd5b7976-4d17-4147-82c7-f6a4175b61ab/call-ldsc/inputs/-261044348/ieu-b-4879.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4879/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Feb  3 19:47:12 2022
Reading summary statistics from /data/cromwell-executions/qc/fd5b7976-4d17-4147-82c7-f6a4175b61ab/call-ldsc/inputs/-261044348/ieu-b-4879.vcf.gz ...
Read summary statistics for 20131699 SNPs.
Dropped 378421 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, 1220905 SNPs remain.
After merging with regression SNP LD, 1220905 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0581 (0.0069)
Lambda GC: 1.2376
Mean Chi^2: 1.6265
Intercept: 1.0498 (0.0121)
Ratio: 0.0795 (0.0193)
Analysis finished at Thu Feb  3 19:50:02 2022
Total time elapsed: 2.0m:50.27s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9643,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 20134421,
    "n_clumped_hits": 154,
    "n_p_sig": 38563,
    "n_mono": 0,
    "n_ns": 1967589,
    "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": 2597262,
    "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": 1220905,
    "ldsc_nsnp_merge_regression_ld": 1220905,
    "ldsc_observed_scale_h2_beta": 0.0581,
    "ldsc_observed_scale_h2_se": 0.0069,
    "ldsc_intercept_beta": 1.0498,
    "ldsc_intercept_se": 0.0121,
    "ldsc_lambda_gc": 1.2376,
    "ldsc_mean_chisq": 1.6265,
    "ldsc_ratio": 0.0795
}

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 TRUE
n_p_sig TRUE
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 2108 0.9998953 3 64 0 20040446 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 25899 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 244 0 111923 0 NA NA NA NA NA NA NA NA NA NA
logical N 20134421 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 9.199792e+00 6.297200e+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 7.869188e+07 5.597224e+07 173.0000000 3.259647e+07 6.961718e+07 1.146990e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.650000e-05 1.877060e-02 -0.5338650 -5.402700e-03 7.200000e-06 5.457500e-03 5.703030e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.389700e-02 1.161030e-02 0.0016501 2.948300e-03 1.004410e-02 2.379700e-02 5.865190e-02 ▇▃▃▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.771745e-01 2.959154e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.771750e-01 2.958909e-01 0.0000000 2.153392e-01 4.705296e-01 7.336017e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 1.973121e-01 3.072276e-01 0.0010000 2.381000e-03 1.838700e-02 2.781380e-01 9.990000e-01 ▇▁▁▁▁
numeric AF_reference 2597262 0.8710039 NA NA NA NA NA NA NA 1.461675e-01 2.309679e-01 0.0000000 2.595800e-03 2.895370e-02 1.861020e-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 0.0045242 0.0029693 0.1299999 0.1275999 0.599214 NA NA
1 10352 rs1557426776 TA T 0.0016334 0.0030508 0.5900000 0.5923844 0.605388 NA NA
1 10511 rs534229142 G A 0.0276516 0.0433190 0.5199996 0.5232622 0.001216 0.0001997 NA
1 10616 rs1557426951 C CCGCCGTTGCAAAGGCGCGCCG 0.0115705 0.0190718 0.5400003 0.5440626 0.005848 NA NA
1 11008 rs575272151 C G 0.0031299 0.0050464 0.5400003 0.5351109 0.086532 0.0880591 NA
1 11012 rs544419019 C G 0.0031299 0.0050464 0.5400003 0.5351109 0.086532 0.0880591 NA
1 13110 rs540538026 G A 0.0097883 0.0068643 0.1499999 0.1538774 0.057246 0.0267572 NA
1 13116 rs62635286 T G 0.0054531 0.0040525 0.1800002 0.1784255 0.185071 0.0970447 NA
1 13118 rs200579949 A G 0.0054531 0.0040525 0.1800002 0.1784255 0.185071 0.0970447 NA
1 13273 rs531730856 G C -0.0056560 0.0047276 0.2300001 0.2315513 0.132186 0.0950479 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 155251511 rs770389553 C T 0.0216229 0.0432995 0.6200004 0.6175118 0.001707 0.0095847 NA
23 155254731 rs775655440 G A 0.0089599 0.0364012 0.8100000 0.8055718 0.001394 0.0135783 NA
23 155254802 rs4568757 C A -0.0158658 0.0143975 0.2700001 0.2704691 0.009444 0.0315495 NA
23 155254881 rs28415761 C A 0.0028724 0.0264359 0.9100000 0.9134744 0.003949 NA NA
23 155255047 rs768259986 C T -0.0062477 0.0326930 0.8499999 0.8484466 0.003069 NA NA
23 155255153 rs28742024 G A -0.0182893 0.0199843 0.3599996 0.3600953 0.005476 NA NA
23 155255277 rs1045930 C G 0.0390255 0.0308506 0.2099999 0.2058772 0.003012 NA NA
23 155260480 NA T G -0.0054409 0.0033909 0.1100001 0.1085862 0.500578 NA NA
23 155260480 NA T A -0.0032689 0.0031885 0.3100002 0.3052539 0.480539 NA NA
23 155260523 NA G T -0.0015418 0.0036038 0.6700003 0.6687794 0.485787 NA NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.599214 ES:SE:LP:AF:ID  0.00452419:0.00296934:0.886057:0.599214:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.605388 ES:SE:LP:AF:ID  0.00163336:0.00305082:0.229148:0.605388:rs1557426776
1   10511   rs534229142 G   A   .   PASS    AF=0.001216 ES:SE:LP:AF:ID  0.0276516:0.043319:0.283997:0.001216:rs534229142
1   10616   rs1557426951    C   CCGCCGTTGCAAAGGCGCGCCG  .   PASS    AF=0.00584802   ES:SE:LP:AF:ID  0.0115705:0.0190718:0.267606:0.00584802:rs1557426951
1   11008   rs575272151 C   G   .   PASS    AF=0.086532 ES:SE:LP:AF:ID  0.0031299:0.00504641:0.267606:0.086532:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086532 ES:SE:LP:AF:ID  0.0031299:0.00504641:0.267606:0.086532:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.057246 ES:SE:LP:AF:ID  0.00978832:0.00686433:0.823909:0.057246:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.185071 ES:SE:LP:AF:ID  0.00545308:0.00405247:0.744727:0.185071:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.185071 ES:SE:LP:AF:ID  0.00545308:0.00405247:0.744727:0.185071:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.132186 ES:SE:LP:AF:ID  -0.00565597:0.0047276:0.638272:0.132186:rs531730856
1   13289   rs538791886 C   CCT .   PASS    AF=0.996158 ES:SE:LP:AF:ID  -0.0573536:0.0292463:1.30103:0.996158:rs538791886
1   13453   rs568927457 T   C   .   PASS    AF=0.006163 ES:SE:LP:AF:ID  -0.00361829:0.0187384:0.0705811:0.006163:rs568927457
1   13483   rs554760071 G   C   .   PASS    AF=0.005137 ES:SE:LP:AF:ID  -0.0304648:0.0199481:0.886057:0.005137:rs554760071
1   13494   rs1272445563    A   G   .   PASS    AF=0.003381 ES:SE:LP:AF:ID  0.0137424:0.0293873:0.19382:0.003381:rs1272445563
1   13550   rs554008981 G   A   .   PASS    AF=0.004688 ES:SE:LP:AF:ID  -0.00320199:0.0244535:0.0457575:0.004688:rs554008981
1   14464   rs546169444 A   T   .   PASS    AF=0.15408  ES:SE:LP:AF:ID  0.00203826:0.0043143:0.19382:0.15408:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.190112 ES:SE:LP:AF:ID  -0.00251805:0.00389576:0.283997:0.190112:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.190112 ES:SE:LP:AF:ID  -0.00251805:0.00389576:0.283997:0.190112:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473165 ES:SE:LP:AF:ID  0.00574461:0.00300749:1.25181:0.473165:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.044187 ES:SE:LP:AF:ID  0.00129683:0.0075085:0.0655015:0.044187:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.735176 ES:SE:LP:AF:ID  0.0121772:0.00345436:3.37675:0.735176:rs3982632
1   15245   rs576044687 C   T   .   PASS    AF=0.001274 ES:SE:LP:AF:ID  -0.0476854:0.0430124:0.568636:0.001274:rs576044687
1   15585   rs533630043 G   A   .   PASS    AF=0.007948 ES:SE:LP:AF:ID  0.0156206:0.018062:0.408935:0.007948:rs533630043
1   15644   rs564003018 G   A   .   PASS    AF=0.004592 ES:SE:LP:AF:ID  -0.0352876:0.0251915:0.79588:0.004592:rs564003018
1   15774   rs374029747 G   A   .   PASS    AF=0.00749  ES:SE:LP:AF:ID  -0.0325748:0.0205948:0.958607:0.00749:rs374029747
1   15777   rs2691317   A   G   .   PASS    AF=0.01738  ES:SE:LP:AF:ID  -0.0226259:0.0128051:1.11351:0.01738:rs2691317
1   15820   rs1316988498    G   T   .   PASS    AF=0.280508 ES:SE:LP:AF:ID  -0.00703192:0.00355773:1.31876:0.280508:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.582028 ES:SE:LP:AF:ID  0.00503366:0.00296278:1.05061:0.582028:rs557514207
1   16142   rs548165136 G   A   .   PASS    AF=0.004094 ES:SE:LP:AF:ID  -0.0600166:0.0253073:1.74473:0.004094:rs548165136
1   16949   rs199745162 A   C   .   PASS    AF=0.018729 ES:SE:LP:AF:ID  -0.0244482:0.0107286:1.63827:0.018729:rs199745162
1   18643   rs564023708 G   A   .   PASS    AF=0.006201 ES:SE:LP:AF:ID  -0.0237558:0.0193626:0.657577:0.006201:rs564023708
1   18849   rs533090414 C   G   .   PASS    AF=0.973441 ES:SE:LP:AF:ID  0.0133263:0.0085492:0.920819:0.973441:rs533090414
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956823 ES:SE:LP:AF:ID  -0.0161468:0.0084269:1.25964:0.956823:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.906886 ES:SE:LP:AF:ID  0.00709999:0.00544888:0.721246:0.906886:rs1165072081
1   46285   rs545414834 A   ATAT    .   PASS    AF=0.997676 ES:SE:LP:AF:ID  0.0361458:0.0307487:0.619789:0.997676:rs545414834
1   47159   rs540662756 T   C   .   PASS    AF=0.06129  ES:SE:LP:AF:ID  5.602e-06:0.00644961:-0:0.06129:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.622769 ES:SE:LP:AF:ID  -0.00092912:0.00353541:0.102373:0.622769:rs10399793
1   49315   rs1231347385    T   A   .   PASS    AF=0.001268 ES:SE:LP:AF:ID  -0.0462149:0.0475559:0.481486:0.001268:rs1231347385
1   49318   rs1231347385    A   G   .   PASS    AF=0.001326 ES:SE:LP:AF:ID  -0.0240805:0.0374815:0.283997:0.001326:rs1231347385
1   49343   rs553572247 T   C   .   PASS    AF=0.001795 ES:SE:LP:AF:ID  0.0631203:0.0358885:1.10237:0.001795:rs553572247
1   49554   rs539322794 A   G   .   PASS    AF=0.091499 ES:SE:LP:AF:ID  -0.00289296:0.0055024:0.221849:0.091499:rs539322794
1   50891   rs542415070 T   C   .   PASS    AF=0.004466 ES:SE:LP:AF:ID  -0.0388053:0.0243243:0.958607:0.004466:rs542415070
1   51047   rs559500163 A   T   .   PASS    AF=0.00163  ES:SE:LP:AF:ID  0.0530228:0.0385419:0.769551:0.00163:rs559500163
1   51049   rs528344458 A   C   .   PASS    AF=0.00163  ES:SE:LP:AF:ID  0.0530228:0.0385419:0.769551:0.00163:rs528344458
1   51050   rs551668143 A   T   .   PASS    AF=0.00163  ES:SE:LP:AF:ID  0.0530228:0.0385419:0.769551:0.00163:rs551668143
1   51053   rs565211799 G   T   .   PASS    AF=0.00163  ES:SE:LP:AF:ID  0.0530228:0.0385419:0.769551:0.00163:rs565211799
1   51479   rs116400033 T   A   .   PASS    AF=0.209244 ES:SE:LP:AF:ID  -0.00194172:0.00382556:0.21467:0.209244:rs116400033
1   51762   rs1359003408    A   G   .   PASS    AF=0.009718 ES:SE:LP:AF:ID  0.009476:0.015442:0.267606:0.009718:rs1359003408
1   51765   rs1359003408    C   G   .   PASS    AF=0.009551 ES:SE:LP:AF:ID  0.0110493:0.0154826:0.318759:0.009551:rs1359003408
1   52152   rs1272293782    A   ATAAT   .   PASS    AF=0.998322 ES:SE:LP:AF:ID  0.00487414:0.0424152:0.0409586:0.998322:rs1272293782