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/20c5946e-efc5-406d-9cf1-f764b9db4d00/call-ldsc/inputs/-261043452/ieu-b-4956.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4956/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 05:14:24 2022
Reading summary statistics from /data/cromwell-executions/qc/20c5946e-efc5-406d-9cf1-f764b9db4d00/call-ldsc/inputs/-261043452/ieu-b-4956.vcf.gz ...
Read summary statistics for 9014094 SNPs.
Dropped 160167 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, 1196981 SNPs remain.
After merging with regression SNP LD, 1196981 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0021 (0.0011)
Lambda GC: 1.0031
Mean Chi^2: 1.0092
Intercept: 0.9937 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Fri Mar  4 05:16:08 2022
Total time elapsed: 1.0m:44.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9358,
    "inflation_factor": 1,
    "mean_EFFECT": -4.7015e-07,
    "n": "-Inf",
    "n_snps": 9015063,
    "n_clumped_hits": 3,
    "n_p_sig": 46,
    "n_mono": 0,
    "n_ns": 1098554,
    "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": 1101650,
    "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": 1196981,
    "ldsc_nsnp_merge_regression_ld": 1196981,
    "ldsc_observed_scale_h2_beta": 0.0021,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 0.9937,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0031,
    "ldsc_mean_chisq": 1.0092,
    "ldsc_ratio": -0.6848
}

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 FALSE
n_p_sig FALSE
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 630 0.9999301 3 58 0 8985363 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 14631 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 60241 0 NA NA NA NA NA NA NA NA NA NA
logical N 9015063 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 8.844321e+00 5.941966e+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 7.843124e+07 5.639185e+07 302.0000000 3.206138e+07 6.882794e+07 1.143381e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.000000e-07 2.012000e-04 -0.0018735 -1.081000e-04 -1.800000e-06 1.050000e-04 2.083800e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.806000e-04 8.550000e-05 0.0000859 1.136000e-04 1.443000e-04 2.250000e-04 9.999000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.976358e-01 2.895803e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.976345e-01 2.895543e-01 0.0000000 2.462143e-01 4.967983e-01 7.487797e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.264498e-01 2.909553e-01 0.0164480 7.077200e-02 2.276630e-01 5.350670e-01 9.835520e-01 ▇▃▂▂▂
numeric AF_reference 1101650 0.8777990 NA NA NA NA NA NA NA 2.811135e-01 2.533218e-01 0.0000000 7.088660e-02 2.006790e-01 4.396960e-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 0.0000120 0.0001560 0.9400001 0.9389264 0.601341 NA NA
1 10352 rs1557426776 TA T 0.0001444 0.0001606 0.3700002 0.3688581 0.607021 NA NA
1 11008 rs575272151 C G 0.0001416 0.0002671 0.5999997 0.5959047 0.086199 0.0880591 NA
1 11012 rs544419019 C G 0.0001416 0.0002671 0.5999997 0.5959047 0.086199 0.0880591 NA
1 13110 rs540538026 G A -0.0000783 0.0003548 0.8300000 0.8252777 0.058737 0.0267572 NA
1 13116 rs62635286 T G -0.0000378 0.0002101 0.8600001 0.8572554 0.189418 0.0970447 NA
1 13118 rs200579949 A G -0.0000378 0.0002101 0.8600001 0.8572554 0.189418 0.0970447 NA
1 13273 rs531730856 G C -0.0002556 0.0002463 0.2999998 0.2993819 0.133920 0.0950479 NA
1 14464 rs546169444 A T 0.0000647 0.0002237 0.7700005 0.7723875 0.157056 0.0958466 NA
1 14599 rs531646671 T A -0.0002298 0.0002039 0.2599998 0.2598207 0.191558 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0001056 0.0000999 0.2900000 0.2903524 0.751526 0.643179 NA
23 154901964 rs697726 G A 0.0000990 0.0001054 0.3500000 0.3473604 0.347497 0.117616 NA
23 154902105 rs696316 G T 0.0001055 0.0000998 0.2900000 0.2906782 0.751478 0.636026 NA
23 154902889 rs697725 A T 0.0001025 0.0000998 0.2999998 0.3046092 0.751149 0.584106 NA
23 154903118 rs479770 G A 0.0001051 0.0000999 0.2900000 0.2928258 0.751569 0.643444 NA
23 154903224 rs480725 A T 0.0001051 0.0000999 0.2900000 0.2928222 0.751571 0.643444 NA
23 154903937 rs674707 G A 0.0001050 0.0000999 0.2900000 0.2932029 0.751581 0.643444 NA
23 154909055 rs473529 C G -0.0000261 0.0000940 0.7800007 0.7814245 0.305106 0.463046 NA
23 154918266 rs642043 C T -0.0000117 0.0000943 0.9000000 0.9010520 0.302975 0.478675 NA
23 154927581 rs644138 G A -0.0000132 0.0000944 0.8900000 0.8885977 0.302847 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601341 ES:SE:LP:AF:ID  1.1951e-05:0.000155979:0.0268721:0.601341:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607021 ES:SE:LP:AF:ID  0.000144357:0.000160644:0.431798:0.607021:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086199 ES:SE:LP:AF:ID  0.000141628:0.000267072:0.221849:0.086199:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086199 ES:SE:LP:AF:ID  0.000141628:0.000267072:0.221849:0.086199:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058737 ES:SE:LP:AF:ID  -7.83277e-05:0.000354806:0.0809219:0.058737:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189418 ES:SE:LP:AF:ID  -3.77957e-05:0.000210129:0.0655015:0.189418:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189418 ES:SE:LP:AF:ID  -3.77957e-05:0.000210129:0.0655015:0.189418:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13392  ES:SE:LP:AF:ID  -0.000255621:0.00024632:0.522879:0.13392:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157056 ES:SE:LP:AF:ID  6.46999e-05:0.000223679:0.113509:0.157056:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191558 ES:SE:LP:AF:ID  -0.000229797:0.000203935:0.585027:0.191558:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191558 ES:SE:LP:AF:ID  -0.000229797:0.000203935:0.585027:0.191558:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474007 ES:SE:LP:AF:ID  4.35731e-05:0.000158184:0.107905:0.474007:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045002 ES:SE:LP:AF:ID  -0.000336465:0.000389648:0.408935:0.045002:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741417 ES:SE:LP:AF:ID  -2.03735e-05:0.000182926:0.0409586:0.741417:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.2752   ES:SE:LP:AF:ID  -0.000211323:0.000187575:0.585027:0.2752:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581012 ES:SE:LP:AF:ID  -0.000105459:0.000154668:0.30103:0.581012:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956492 ES:SE:LP:AF:ID  -0.000402952:0.000439508:0.443698:0.956492:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910272 ES:SE:LP:AF:ID  -0.000279094:0.000292014:0.468521:0.910272:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062672 ES:SE:LP:AF:ID  0.000111098:0.00033317:0.130768:0.062672:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.62366  ES:SE:LP:AF:ID  0.000293388:0.000185569:0.958607:0.62366:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092979 ES:SE:LP:AF:ID  0.000271025:0.000285391:0.468521:0.092979:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213498 ES:SE:LP:AF:ID  7.81264e-05:0.000198362:0.161151:0.213498:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.15454  ES:SE:LP:AF:ID  0.000177579:0.000222856:0.366532:0.15454:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.40043  ES:SE:LP:AF:ID  0.000102767:0.000183828:0.236572:0.40043:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.41487  ES:SE:LP:AF:ID  0.000223679:0.000145316:0.920819:0.41487:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417207 ES:SE:LP:AF:ID  -0.000198293:0.000167814:0.619789:0.417207:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253878 ES:SE:LP:AF:ID  0.000149338:0.000188799:0.366532:0.253878:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090043 ES:SE:LP:AF:ID  0.000261042:0.000287493:0.443698:0.090043:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088881 ES:SE:LP:AF:ID  0.000297604:0.000288576:0.522879:0.088881:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081032 ES:SE:LP:AF:ID  0.000316299:0.000299351:0.537602:0.081032:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438455 ES:SE:LP:AF:ID  -0.000277167:0.000159549:1.08619:0.438455:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382127 ES:SE:LP:AF:ID  0.000165912:0.000171506:0.481486:0.382127:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158851 ES:SE:LP:AF:ID  0.000161276:0.000218361:0.337242:0.158851:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683985 ES:SE:LP:AF:ID  0.000114905:0.00017:0.30103:0.683985:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079638 ES:SE:LP:AF:ID  0.000264145:0.00030299:0.420216:0.079638:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070759 ES:SE:LP:AF:ID  4.89823e-05:0.000307331:0.0604807:0.070759:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032898 ES:SE:LP:AF:ID  -0.00012594:0.000465138:0.102373:0.032898:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073905 ES:SE:LP:AF:ID  0.000101723:0.00030229:0.130768:0.073905:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751126 ES:SE:LP:AF:ID  -0.000375943:0.000192544:1.29243:0.751126:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034052 ES:SE:LP:AF:ID  0.000513373:0.000442087:0.60206:0.034052:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034052 ES:SE:LP:AF:ID  0.000513373:0.000442087:0.60206:0.034052:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077214 ES:SE:LP:AF:ID  0.00042366:0.000308744:0.769551:0.077214:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.07745  ES:SE:LP:AF:ID  7.19052e-05:0.000298182:0.091515:0.07745:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077017 ES:SE:LP:AF:ID  0.000427021:0.000308826:0.769551:0.077017:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077017 ES:SE:LP:AF:ID  0.000427021:0.000308826:0.769551:0.077017:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041519 ES:SE:LP:AF:ID  -0.000305389:0.000430567:0.318759:0.041519:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060969 ES:SE:LP:AF:ID  0.000139268:0.000327407:0.173925:0.060969:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.07541  ES:SE:LP:AF:ID  6.42102e-05:0.000301949:0.0809219:0.07541:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075437 ES:SE:LP:AF:ID  6.56987e-05:0.000301888:0.0809219:0.075437:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352683 ES:SE:LP:AF:ID  -6.9359e-05:0.000172868:0.161151:0.352683:rs201754587