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/607e2024-ddbf-491a-96a0-c63a8022d3d0/call-ldsc/inputs/562856223/ieu-b-45.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-45/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Tue Oct 13 13:52:23 2020
Reading summary statistics from /data/cromwell-executions/qc/607e2024-ddbf-491a-96a0-c63a8022d3d0/call-ldsc/inputs/562856223/ieu-b-45.vcf.gz ...
Read summary statistics for 0 SNPs.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ...
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] ...
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 Oct 13 13:53:27 2020
Total time elapsed: 1.0m:4.35s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 14,
    "n_p_sig": 1356,
    "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": "NA",
    "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 8.470000e-05 2.222940e-02 -0.3820360 -7.038000e-03 -1.720000e-05 6.966300e-03 4.270310e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.558550e-02 1.496960e-02 0.0038733 5.456600e-03 8.762200e-03 2.021680e-02 2.352020e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.754887e-01 2.953390e-01 0.0000000 2.099999e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.754889e-01 2.953124e-01 0.0000000 2.139725e-01 4.674699e-01 7.308905e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594004e-01 3.020450e-01 0.0008680 1.660200e-02 1.145640e-01 4.379540e-01 9.990960e-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 -0.0004986 0.0070096 0.9400001 0.9432975 0.600937 NA NA
1 10352 rs1557426776 TA T -0.0062174 0.0072116 0.3900004 0.3886100 0.606560 NA NA
1 11008 rs575272151 C G -0.0113402 0.0119976 0.3400001 0.3445539 0.086324 0.0880591 NA
1 11012 rs544419019 C G -0.0113402 0.0119976 0.3400001 0.3445539 0.086324 0.0880591 NA
1 13110 rs540538026 G A -0.0151950 0.0159128 0.3400001 0.3396325 0.058814 0.0267572 NA
1 13116 rs62635286 T G 0.0062927 0.0094564 0.5099998 0.5057684 0.189107 0.0970447 NA
1 13118 rs200579949 A G 0.0062927 0.0094564 0.5099998 0.5057684 0.189107 0.0970447 NA
1 13273 rs531730856 G C -0.0054622 0.0110503 0.6200004 0.6210939 0.134021 0.0950479 NA
1 14464 rs546169444 A T 0.0065519 0.0100677 0.5199996 0.5151839 0.156921 0.0958466 NA
1 14599 rs531646671 T A 0.0105040 0.0091484 0.2500000 0.2508952 0.191685 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0132314 0.0044983 0.00330 0.0032672 0.751568 0.643179 NA
23 154901964 rs697726 G A -0.0125714 0.0047421 0.00800 0.0080247 0.348387 0.117616 NA
23 154902105 rs696316 G T -0.0132438 0.0044980 0.00320 0.0032360 0.751522 0.636026 NA
23 154902889 rs697725 A T -0.0130552 0.0044965 0.00370 0.0036909 0.751198 0.584106 NA
23 154903118 rs479770 G A -0.0133137 0.0044987 0.00310 0.0030821 0.751617 0.643444 NA
23 154903224 rs480725 A T -0.0133105 0.0044987 0.00310 0.0030892 0.751620 0.643444 NA
23 154903937 rs674707 G A -0.0133072 0.0044989 0.00310 0.0030974 0.751631 0.643444 NA
23 154909055 rs473529 C G 0.0154425 0.0042335 0.00026 0.0002646 0.305260 0.463046 NA
23 154918266 rs642043 C T 0.0158613 0.0042472 0.00019 0.0001881 0.303085 0.478675 NA
23 154927581 rs644138 G A 0.0159491 0.0042479 0.00017 0.0001736 0.302965 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.600937 ES:SE:LP:AF:ID  -0.000498561:0.00700955:0.0268721:0.600937:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.60656  ES:SE:LP:AF:ID  -0.00621745:0.00721164:0.408935:0.60656:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086324 ES:SE:LP:AF:ID  -0.0113402:0.0119976:0.468521:0.086324:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086324 ES:SE:LP:AF:ID  -0.0113402:0.0119976:0.468521:0.086324:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058814 ES:SE:LP:AF:ID  -0.015195:0.0159128:0.468521:0.058814:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189107 ES:SE:LP:AF:ID  0.00629271:0.00945645:0.29243:0.189107:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189107 ES:SE:LP:AF:ID  0.00629271:0.00945645:0.29243:0.189107:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134021 ES:SE:LP:AF:ID  -0.00546217:0.0110503:0.207608:0.134021:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156921 ES:SE:LP:AF:ID  0.00655193:0.0100677:0.283997:0.156921:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191685 ES:SE:LP:AF:ID  0.010504:0.00914841:0.60206:0.191685:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191685 ES:SE:LP:AF:ID  0.010504:0.00914841:0.60206:0.191685:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.47377  ES:SE:LP:AF:ID  -0.0150512:0.00710536:1.46852:0.47377:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045001 ES:SE:LP:AF:ID  -0.0131831:0.0174636:0.346787:0.045001:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741246 ES:SE:LP:AF:ID  0.00575746:0.00822077:0.318759:0.741246:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275016 ES:SE:LP:AF:ID  0.0145461:0.00842862:1.07572:0.275016:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581071 ES:SE:LP:AF:ID  -0.0198532:0.00694311:2.37675:0.581071:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956546 ES:SE:LP:AF:ID  0.0104528:0.0198302:0.221849:0.956546:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910367 ES:SE:LP:AF:ID  0.0037691:0.0131273:0.113509:0.910367:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062787 ES:SE:LP:AF:ID  0.0174098:0.0149466:0.619789:0.062787:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623747 ES:SE:LP:AF:ID  0.00564177:0.00833793:0.30103:0.623747:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.09297  ES:SE:LP:AF:ID  0.00144133:0.0128193:0.0409586:0.09297:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213005 ES:SE:LP:AF:ID  0.00187034:0.00892269:0.0809219:0.213005:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154186 ES:SE:LP:AF:ID  -0.00264495:0.0100274:0.102373:0.154186:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400441 ES:SE:LP:AF:ID  0.00337504:0.00826366:0.167491:0.400441:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414513 ES:SE:LP:AF:ID  0.000641465:0.0065403:0.0362122:0.414513:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417632 ES:SE:LP:AF:ID  -0.00542211:0.00753772:0.327902:0.417632:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253655 ES:SE:LP:AF:ID  0.00913619:0.0084865:0.552842:0.253655:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090046 ES:SE:LP:AF:ID  0.00356335:0.0129253:0.107905:0.090046:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088937 ES:SE:LP:AF:ID  0.0137938:0.0129553:0.537602:0.088937:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081172 ES:SE:LP:AF:ID  0.010206:0.0134306:0.346787:0.081172:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438474 ES:SE:LP:AF:ID  -0.00865381:0.00717488:0.638272:0.438474:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382127 ES:SE:LP:AF:ID  0.00812438:0.00771327:0.537602:0.382127:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158843 ES:SE:LP:AF:ID  0.00526802:0.00979788:0.229148:0.158843:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683906 ES:SE:LP:AF:ID  -0.0144612:0.00764623:1.22915:0.683906:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079711 ES:SE:LP:AF:ID  0.0103328:0.0136086:0.346787:0.079711:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070968 ES:SE:LP:AF:ID  -0.0151132:0.0137685:0.568636:0.070968:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032915 ES:SE:LP:AF:ID  -0.0371857:0.0208999:1.12494:0.032915:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.074085 ES:SE:LP:AF:ID  -0.0184716:0.0135513:0.769551:0.074085:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751186 ES:SE:LP:AF:ID  0.00413097:0.00865502:0.200659:0.751186:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.033979 ES:SE:LP:AF:ID  0.00410545:0.0199151:0.0757207:0.033979:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.033979 ES:SE:LP:AF:ID  0.00410545:0.0199151:0.0757207:0.033979:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077244 ES:SE:LP:AF:ID  -0.000232329:0.013864:0.00436481:0.077244:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077504 ES:SE:LP:AF:ID  0.00584169:0.0133871:0.180456:0.077504:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077054 ES:SE:LP:AF:ID  -0.000320652:0.0138672:0.00877392:0.077054:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077054 ES:SE:LP:AF:ID  -0.000320652:0.0138672:0.00877392:0.077054:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041341 ES:SE:LP:AF:ID  -0.00230774:0.0194499:0.0409586:0.041341:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.061113 ES:SE:LP:AF:ID  -0.0181658:0.014688:0.657577:0.061113:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075484 ES:SE:LP:AF:ID  0.00767653:0.0135552:0.244125:0.075484:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.07551  ES:SE:LP:AF:ID  0.00729399:0.0135525:0.229148:0.07551:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.353034 ES:SE:LP:AF:ID  0.00579453:0.00775504:0.346787:0.353034:rs201754587