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/050c5144-b478-4426-994f-be754ab82744/call-ldsc/inputs/562856224/ieu-b-46.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-46/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Tue Oct 13 13:48:04 2020
Reading summary statistics from /data/cromwell-executions/qc/050c5144-b478-4426-994f-be754ab82744/call-ldsc/inputs/562856224/ieu-b-46.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 13:49:08 2020
Total time elapsed: 1.0m:4.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 6,
    "n_p_sig": 202,
    "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 FALSE
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 1.000000 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+07 302.000000 3.252510e+07 6.928045e+07 1.144492e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.616000e-04 1.250490e-02 -0.268156 -3.838400e-03 2.990000e-05 3.927400e-03 1.827440e-01 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.723800e-03 8.376500e-03 0.002163 3.054800e-03 4.905200e-03 1.132010e-02 1.353770e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.775445e-01 2.949865e-01 0.000000 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 4.775446e-01 2.949613e-01 0.000000 2.161296e-01 4.704968e-01 7.328364e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594004e-01 3.020440e-01 0.000891 1.659600e-02 1.145520e-01 4.379480e-01 9.990990e-01 ▇▂▁▁▁
numeric AF_reference 1423040 0.8845111 NA NA NA NA NA NA NA 2.132160e-01 2.513550e-01 0.000000 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 0.0013295 0.0039181 0.7300002 0.7343667 0.601270 NA NA
1 10352 rs1557426776 TA T 0.0007834 0.0040377 0.8499999 0.8461528 0.606911 NA NA
1 11008 rs575272151 C G -0.0068623 0.0067099 0.3100002 0.3064437 0.086012 0.0880591 NA
1 11012 rs544419019 C G -0.0068623 0.0067099 0.3100002 0.3064437 0.086012 0.0880591 NA
1 13110 rs540538026 G A 0.0062302 0.0089536 0.4899999 0.4865339 0.058559 0.0267572 NA
1 13116 rs62635286 T G 0.0039337 0.0052753 0.4600002 0.4558637 0.189140 0.0970447 NA
1 13118 rs200579949 A G 0.0039337 0.0052753 0.4600002 0.4558637 0.189140 0.0970447 NA
1 13273 rs531730856 G C -0.0043444 0.0061796 0.4799997 0.4820455 0.134164 0.0950479 NA
1 14464 rs546169444 A T 0.0021062 0.0056234 0.7099994 0.7080067 0.156922 0.0958466 NA
1 14599 rs531646671 T A -0.0046262 0.0051270 0.3700002 0.3668925 0.191423 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0063156 0.0025198 0.0120000 0.0121970 0.752158 0.643179 NA
23 154901964 rs697726 G A 0.0028492 0.0026592 0.2800000 0.2839744 0.347146 0.117616 NA
23 154902105 rs696316 G T 0.0063343 0.0025197 0.0120000 0.0119392 0.752113 0.636026 NA
23 154902889 rs697725 A T 0.0061656 0.0025190 0.0140001 0.0143785 0.751802 0.584106 NA
23 154903118 rs479770 G A 0.0063225 0.0025201 0.0120000 0.0121129 0.752202 0.643444 NA
23 154903224 rs480725 A T 0.0063234 0.0025201 0.0120000 0.0121008 0.752204 0.643444 NA
23 154903937 rs674707 G A 0.0063288 0.0025202 0.0120000 0.0120303 0.752214 0.643444 NA
23 154909055 rs473529 C G -0.0049547 0.0023731 0.0369999 0.0368144 0.304374 0.463046 NA
23 154918266 rs642043 C T -0.0047023 0.0023808 0.0479999 0.0482539 0.302236 0.478675 NA
23 154927581 rs644138 G A -0.0047385 0.0023812 0.0470002 0.0465992 0.302105 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.60127  ES:SE:LP:AF:ID  0.0013295:0.0039181:0.136677:0.60127:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606911 ES:SE:LP:AF:ID  0.000783427:0.00403767:0.0705811:0.606911:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086012 ES:SE:LP:AF:ID  -0.0068623:0.0067099:0.508638:0.086012:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086012 ES:SE:LP:AF:ID  -0.0068623:0.0067099:0.508638:0.086012:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058559 ES:SE:LP:AF:ID  0.00623019:0.00895358:0.309804:0.058559:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.18914  ES:SE:LP:AF:ID  0.00393369:0.00527534:0.337242:0.18914:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.18914  ES:SE:LP:AF:ID  0.00393369:0.00527534:0.337242:0.18914:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134164 ES:SE:LP:AF:ID  -0.00434436:0.0061796:0.318759:0.134164:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156922 ES:SE:LP:AF:ID  0.00210615:0.00562338:0.148742:0.156922:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191423 ES:SE:LP:AF:ID  -0.00462615:0.00512701:0.431798:0.191423:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191423 ES:SE:LP:AF:ID  -0.00462615:0.00512701:0.431798:0.191423:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473898 ES:SE:LP:AF:ID  -0.00837758:0.00397361:1.45593:0.473898:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.04509  ES:SE:LP:AF:ID  -0.0024671:0.00978298:0.09691:0.04509:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741243 ES:SE:LP:AF:ID  0.00582262:0.00458813:0.69897:0.741243:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.27516  ES:SE:LP:AF:ID  -0.000198446:0.00471422:0.0132283:0.27516:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581359 ES:SE:LP:AF:ID  0.000122352:0.00388545:0.0132283:0.581359:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956562 ES:SE:LP:AF:ID  -0.0162419:0.0110482:0.853872:0.956562:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910178 ES:SE:LP:AF:ID  0.0061219:0.00733673:0.39794:0.910178:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062683 ES:SE:LP:AF:ID  0.0117222:0.00838951:0.79588:0.062683:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623892 ES:SE:LP:AF:ID  0.00331467:0.00465662:0.318759:0.623892:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.093029 ES:SE:LP:AF:ID  0.00445486:0.00717854:0.275724:0.093029:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213558 ES:SE:LP:AF:ID  0.00333282:0.00498471:0.30103:0.213558:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154687 ES:SE:LP:AF:ID  0.00520469:0.00559727:0.455932:0.154687:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400366 ES:SE:LP:AF:ID  0.00208411:0.00461031:0.187087:0.400366:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414825 ES:SE:LP:AF:ID  -0.000196251:0.00364892:0.0177288:0.414825:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417247 ES:SE:LP:AF:ID  -0.00243498:0.00422089:0.251812:0.417247:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253829 ES:SE:LP:AF:ID  -0.00077167:0.00474909:0.0604807:0.253829:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089966 ES:SE:LP:AF:ID  -0.00193127:0.00723841:0.102373:0.089966:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088709 ES:SE:LP:AF:ID  0.00249213:0.00727423:0.136677:0.088709:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080858 ES:SE:LP:AF:ID  0.00262827:0.007549:0.136677:0.080858:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438133 ES:SE:LP:AF:ID  -0.000671787:0.0040015:0.0604807:0.438133:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382246 ES:SE:LP:AF:ID  0.00136006:0.00430676:0.124939:0.382246:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158657 ES:SE:LP:AF:ID  0.000769923:0.00549728:0.05061:0.158657:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683863 ES:SE:LP:AF:ID  -0.00238667:0.00426712:0.236572:0.683863:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079487 ES:SE:LP:AF:ID  0.00430857:0.00763656:0.244125:0.079487:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070644 ES:SE:LP:AF:ID  -0.000650418:0.00773024:0.0315171:0.070644:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032901 ES:SE:LP:AF:ID  0.012713:0.0116766:0.552842:0.032901:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073715 ES:SE:LP:AF:ID  0.000455798:0.00761121:0.0222764:0.073715:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751434 ES:SE:LP:AF:ID  0.0053339:0.00484528:0.568636:0.751434:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034215 ES:SE:LP:AF:ID  0.00515593:0.0110589:0.19382:0.034215:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034215 ES:SE:LP:AF:ID  0.00515593:0.0110589:0.19382:0.034215:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077105 ES:SE:LP:AF:ID  0.000921195:0.00778026:0.0409586:0.077105:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077502 ES:SE:LP:AF:ID  0.00809262:0.00749736:0.552842:0.077502:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076904 ES:SE:LP:AF:ID  0.000790945:0.00778237:0.0362122:0.076904:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076904 ES:SE:LP:AF:ID  0.000790945:0.00778237:0.0362122:0.076904:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041561 ES:SE:LP:AF:ID  0.0228738:0.0108078:1.46852:0.041561:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060849 ES:SE:LP:AF:ID  0.00204049:0.00823043:0.09691:0.060849:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075414 ES:SE:LP:AF:ID  0.00834787:0.00759748:0.568636:0.075414:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075444 ES:SE:LP:AF:ID  0.00810284:0.0075955:0.537602:0.075444:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352621 ES:SE:LP:AF:ID  -0.00124834:0.00434178:0.113509:0.352621:rs201754587