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/4a68bd88-e924-4c69-9042-87a3d7ea310e/call-ldsc/inputs/-261043427/ieu-b-4960.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4960/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 16:56:21 2022
Reading summary statistics from /data/cromwell-executions/qc/4a68bd88-e924-4c69-9042-87a3d7ea310e/call-ldsc/inputs/-261043427/ieu-b-4960.vcf.gz ...
Read summary statistics for 8969499 SNPs.
Dropped 159356 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, 1195881 SNPs remain.
After merging with regression SNP LD, 1195881 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0018 (0.0012)
Lambda GC: 1.0263
Mean Chi^2: 1.0228
Intercept: 1.0097 (0.0063)
Ratio: 0.4253 (0.277)
Analysis finished at Fri Mar  4 16:58:05 2022
Total time elapsed: 1.0m:44.14s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9354,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 2.5279e-07,
    "n": "-Inf",
    "n_snps": 8970465,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1094673,
    "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": 1097527,
    "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": 1195881,
    "ldsc_nsnp_merge_regression_ld": 1195881,
    "ldsc_observed_scale_h2_beta": 0.0018,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0097,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0263,
    "ldsc_mean_chisq": 1.0228,
    "ldsc_ratio": 0.4254
}

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 627 0.9999301 3 58 0 8940970 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 14566 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 60020 0 NA NA NA NA NA NA NA NA NA NA
logical N 8970465 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 8.845108e+00 5.942811e+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 7.843178e+07 5.639279e+07 302.0000000 3.205586e+07 6.883411e+07 1.143456e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.000000e-07 1.974000e-04 -0.0019569 -1.060000e-04 -5.000000e-07 1.045000e-04 2.685800e-03 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.771000e-04 8.290000e-05 0.0000847 1.120000e-04 1.419000e-04 2.203000e-04 9.865000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.956477e-01 2.897536e-01 0.0000003 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.956468e-01 2.897269e-01 0.0000003 2.436545e-01 4.939236e-01 7.466701e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.274997e-01 2.905666e-01 0.0168920 7.204000e-02 2.294060e-01 5.362430e-01 9.831080e-01 ▇▃▂▂▂
numeric AF_reference 1097527 0.8776510 NA NA NA NA NA NA NA 2.822926e-01 2.531983e-01 0.0000000 7.228430e-02 2.022760e-01 4.412940e-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 -0.0000354 0.0001539 0.8200001 0.8179536 0.601336 NA NA
1 10352 rs1557426776 TA T -0.0000602 0.0001585 0.6999999 0.7040099 0.607000 NA NA
1 11008 rs575272151 C G -0.0000934 0.0002635 0.7199992 0.7230371 0.086190 0.0880591 NA
1 11012 rs544419019 C G -0.0000934 0.0002635 0.7199992 0.7230371 0.086190 0.0880591 NA
1 13110 rs540538026 G A 0.0003061 0.0003500 0.3800004 0.3819002 0.058745 0.0267572 NA
1 13116 rs62635286 T G -0.0000215 0.0002073 0.9199999 0.9172901 0.189419 0.0970447 NA
1 13118 rs200579949 A G -0.0000215 0.0002073 0.9199999 0.9172901 0.189419 0.0970447 NA
1 13273 rs531730856 G C 0.0000736 0.0002430 0.7600007 0.7619602 0.133935 0.0950479 NA
1 14464 rs546169444 A T -0.0001139 0.0002207 0.6100002 0.6059511 0.157047 0.0958466 NA
1 14599 rs531646671 T A -0.0000121 0.0002012 0.9500000 0.9521084 0.191572 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0001133 9.85e-05 0.2500000 0.2501588 0.751527 0.643179 NA
23 154901964 rs697726 G A 0.0000073 1.04e-04 0.9400001 0.9442684 0.347475 0.117616 NA
23 154902105 rs696316 G T 0.0001135 9.85e-05 0.2500000 0.2493100 0.751480 0.636026 NA
23 154902889 rs697725 A T 0.0001153 9.85e-05 0.2399999 0.2418287 0.751152 0.584106 NA
23 154903118 rs479770 G A 0.0001131 9.85e-05 0.2500000 0.2511749 0.751570 0.643444 NA
23 154903224 rs480725 A T 0.0001131 9.85e-05 0.2500000 0.2511628 0.751573 0.643444 NA
23 154903937 rs674707 G A 0.0001130 9.85e-05 0.2500000 0.2513812 0.751583 0.643444 NA
23 154909055 rs473529 C G -0.0001693 9.28e-05 0.0680002 0.0681030 0.305063 0.463046 NA
23 154918266 rs642043 C T -0.0001808 9.31e-05 0.0519996 0.0521505 0.302924 0.478675 NA
23 154927581 rs644138 G A -0.0001812 9.31e-05 0.0519996 0.0516689 0.302796 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601336 ES:SE:LP:AF:ID  -3.54269e-05:0.000153911:0.0861861:0.601336:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607    ES:SE:LP:AF:ID  -6.02223e-05:0.000158516:0.154902:0.607:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.08619  ES:SE:LP:AF:ID  -9.33915e-05:0.000263518:0.142668:0.08619:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.08619  ES:SE:LP:AF:ID  -9.33915e-05:0.000263518:0.142668:0.08619:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058745 ES:SE:LP:AF:ID  0.000306069:0.000350033:0.420216:0.058745:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189419 ES:SE:LP:AF:ID  -2.15315e-05:0.000207337:0.0362122:0.189419:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189419 ES:SE:LP:AF:ID  -2.15315e-05:0.000207337:0.0362122:0.189419:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133935 ES:SE:LP:AF:ID  7.36205e-05:0.000243046:0.119186:0.133935:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157047 ES:SE:LP:AF:ID  -0.000113862:0.000220722:0.21467:0.157047:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191572 ES:SE:LP:AF:ID  -1.20858e-05:0.000201231:0.0222764:0.191572:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191572 ES:SE:LP:AF:ID  -1.20858e-05:0.000201231:0.0222764:0.191572:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474013 ES:SE:LP:AF:ID  9.74814e-05:0.000156078:0.275724:0.474013:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045009 ES:SE:LP:AF:ID  4.5756e-05:0.000384393:0.0409586:0.045009:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741437 ES:SE:LP:AF:ID  0.000222804:0.00018052:0.657577:0.741437:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.2752   ES:SE:LP:AF:ID  -0.000216119:0.000185099:0.619789:0.2752:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581031 ES:SE:LP:AF:ID  5.32794e-05:0.000152625:0.136677:0.581031:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956509 ES:SE:LP:AF:ID  0.000759866:0.000433864:1.09691:0.956509:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910282 ES:SE:LP:AF:ID  1.16668e-05:0.00028816:0.0132283:0.910282:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062676 ES:SE:LP:AF:ID  0.000272588:0.000328785:0.387216:0.062676:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623633 ES:SE:LP:AF:ID  -4.61233e-05:0.000183095:0.09691:0.623633:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092951 ES:SE:LP:AF:ID  -0.000540265:0.000281685:1.25964:0.092951:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213478 ES:SE:LP:AF:ID  -0.000211364:0.000195743:0.552842:0.213478:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154515 ES:SE:LP:AF:ID  -0.000268181:0.000219944:0.657577:0.154515:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400413 ES:SE:LP:AF:ID  -9.83148e-05:0.000181393:0.229148:0.400413:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414821 ES:SE:LP:AF:ID  -0.000151168:0.000143394:0.537602:0.414821:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.41727  ES:SE:LP:AF:ID  0.000448191:0.0001656:2.16749:0.41727:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253835 ES:SE:LP:AF:ID  -0.000414196:0.000186324:1.58503:0.253835:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090023 ES:SE:LP:AF:ID  -0.000337412:0.000283747:0.638272:0.090023:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088859 ES:SE:LP:AF:ID  -0.000371226:0.000284826:0.721246:0.088859:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081013 ES:SE:LP:AF:ID  -0.000304965:0.000295452:0.522879:0.081013:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438507 ES:SE:LP:AF:ID  0.00019678:0.000157439:0.677781:0.438507:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382091 ES:SE:LP:AF:ID  -0.00022183:0.000169245:0.721246:0.382091:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158839 ES:SE:LP:AF:ID  -4.9235e-05:0.000215483:0.0861861:0.158839:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683995 ES:SE:LP:AF:ID  0.000229945:0.000167739:0.769551:0.683995:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079623 ES:SE:LP:AF:ID  -0.000231648:0.000299029:0.356547:0.079623:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070764 ES:SE:LP:AF:ID  0.000248039:0.000303215:0.387216:0.070764:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032898 ES:SE:LP:AF:ID  -0.000182361:0.000458993:0.161151:0.032898:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073908 ES:SE:LP:AF:ID  0.000209578:0.000298256:0.318759:0.073908:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751169 ES:SE:LP:AF:ID  0.000195848:0.000190009:0.522879:0.751169:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034034 ES:SE:LP:AF:ID  -0.000760771:0.000436522:1.09151:0.034034:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034034 ES:SE:LP:AF:ID  -0.000760771:0.000436522:1.09151:0.034034:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077187 ES:SE:LP:AF:ID  -0.000492925:0.000304751:0.958607:0.077187:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077456 ES:SE:LP:AF:ID  0.000248349:0.000294257:0.39794:0.077456:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076991 ES:SE:LP:AF:ID  -0.00049603:0.000304831:1:0.076991:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076991 ES:SE:LP:AF:ID  -0.00049603:0.000304831:1:0.076991:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041528 ES:SE:LP:AF:ID  0.000299186:0.00042476:0.318759:0.041528:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060968 ES:SE:LP:AF:ID  0.000102387:0.000323045:0.124939:0.060968:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075414 ES:SE:LP:AF:ID  0.000204431:0.00029798:0.309804:0.075414:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075441 ES:SE:LP:AF:ID  0.000200224:0.000297919:0.30103:0.075441:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352722 ES:SE:LP:AF:ID  0.000360604:0.000170583:1.45593:0.352722:rs201754587