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/24bd7959-7860-4317-8364-fd3b9d7cdb3c/call-ldsc/inputs/-261044351/ieu-b-4876.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4876/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  2 01:22:34 2022
Reading summary statistics from /data/cromwell-executions/qc/24bd7959-7860-4317-8364-fd3b9d7cdb3c/call-ldsc/inputs/-261044351/ieu-b-4876.vcf.gz ...
Read summary statistics for 8505324 SNPs.
Dropped 150750 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, 1181549 SNPs remain.
After merging with regression SNP LD, 1181549 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0009 (0.0022)
Lambda GC: 1.0053
Mean Chi^2: 1.0016
Intercept: 0.9981 (0.0063)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  2 01:24:01 2022
Total time elapsed: 1.0m:26.67s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9316,
    "inflation_factor": 1,
    "mean_EFFECT": 3.7503e-07,
    "n": "-Inf",
    "n_snps": 8506261,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1054244,
    "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": 1054419,
    "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": 1181549,
    "ldsc_nsnp_merge_regression_ld": 1181549,
    "ldsc_observed_scale_h2_beta": 0.0009,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 0.9981,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0053,
    "ldsc_mean_chisq": 1.0016,
    "ldsc_ratio": -1.1875
}

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 610 0.9999283 3 58 0 8478819 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 13975 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 57632 0 NA NA NA NA NA NA NA NA NA NA
logical N 8506261 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 8.854738e+00 5.950010e+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 7.838043e+07 5.641276e+07 302.0000000 3.197628e+07 6.878826e+07 1.143065e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.000000e-07 2.943000e-04 -0.0030461 -1.656000e-04 -1.200000e-06 1.630000e-04 3.325200e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.712000e-04 1.125000e-04 0.0001622 1.817000e-04 2.244000e-04 3.313000e-04 1.402800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.987237e-01 2.886308e-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 4.987260e-01 2.886052e-01 0.0000000 2.482384e-01 4.984006e-01 7.484955e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.386221e-01 2.859763e-01 0.0222029 8.598500e-02 2.482730e-01 5.478270e-01 9.777980e-01 ▇▃▂▂▂
numeric AF_reference 1054419 0.8760420 NA NA NA NA NA NA NA 2.947681e-01 2.514217e-01 0.0000000 8.646170e-02 2.192490e-01 4.564700e-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 0.0000608 0.0002511 0.8100000 0.8086973 0.601810 NA NA
1 10352 rs1557426776 TA T 0.0001471 0.0002585 0.5700002 0.5691844 0.606785 NA NA
1 11008 rs575272151 C G 0.0007137 0.0004313 0.0980009 0.0979646 0.085884 0.0880591 NA
1 11012 rs544419019 C G 0.0007137 0.0004313 0.0980009 0.0979646 0.085884 0.0880591 NA
1 13110 rs540538026 G A 0.0001732 0.0005709 0.7600007 0.7616551 0.058627 0.0267572 NA
1 13116 rs62635286 T G 0.0006793 0.0003379 0.0439997 0.0443908 0.189393 0.0970447 NA
1 13118 rs200579949 A G 0.0006793 0.0003379 0.0439997 0.0443908 0.189393 0.0970447 NA
1 13273 rs531730856 G C 0.0005278 0.0003961 0.1800002 0.1827343 0.133840 0.0950479 NA
1 14464 rs546169444 A T -0.0007185 0.0003591 0.0449997 0.0454272 0.157245 0.0958466 NA
1 14599 rs531646671 T A 0.0001167 0.0003282 0.7199992 0.7222283 0.191243 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0000292 0.0001949 0.8800001 0.8807278 0.751344 0.643179 NA
23 154901964 rs697726 G A -0.0002871 0.0002060 0.1600000 0.1633356 0.347028 0.117616 NA
23 154902105 rs696316 G T 0.0000293 0.0001948 0.8800001 0.8803081 0.751273 0.636026 NA
23 154902889 rs697725 A T 0.0000216 0.0001948 0.9100000 0.9118545 0.750908 0.584106 NA
23 154903118 rs479770 G A 0.0000278 0.0001949 0.8900000 0.8863822 0.751398 0.643444 NA
23 154903224 rs480725 A T 0.0000278 0.0001949 0.8900000 0.8866004 0.751402 0.643444 NA
23 154903937 rs674707 G A 0.0000276 0.0001949 0.8900000 0.8874447 0.751415 0.643444 NA
23 154909055 rs473529 C G -0.0000203 0.0001836 0.9100000 0.9119689 0.305650 0.463046 NA
23 154918266 rs642043 C T -0.0000226 0.0001842 0.9000000 0.9023822 0.303474 0.478675 NA
23 154927581 rs644138 G A -0.0000205 0.0001842 0.9100000 0.9113708 0.303325 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.60181  ES:SE:LP:AF:SI:ID   6.07962e-05:0.000251113:0.091515:0.60181:0.466089:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606785 ES:SE:LP:AF:SI:ID   0.000147128:0.000258458:0.244125:0.606785:0.44449:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.085884 ES:SE:LP:AF:SI:ID   0.000713708:0.000431295:1.00877:0.085884:0.486664:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.085884 ES:SE:LP:AF:SI:ID   0.000713708:0.000431295:1.00877:0.085884:0.486664:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058627 ES:SE:LP:AF:SI:ID   0.000173164:0.000570918:0.119186:0.058627:0.39209:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189393 ES:SE:LP:AF:SI:ID   0.0006793:0.000337896:1.35655:0.189393:0.404681:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189393 ES:SE:LP:AF:SI:ID   0.0006793:0.000337896:1.35655:0.189393:0.404681:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13384  ES:SE:LP:AF:SI:ID   0.000527801:0.000396133:0.744727:0.13384:0.390731:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157245 ES:SE:LP:AF:SI:ID   -0.000718477:0.000359117:1.34679:0.157245:0.410824:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191243 ES:SE:LP:AF:SI:ID   0.000116675:0.000328216:0.142668:0.191243:0.424479:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191243 ES:SE:LP:AF:SI:ID   0.000116675:0.000328216:0.142668:0.191243:0.424479:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473747 ES:SE:LP:AF:SI:ID   -0.00021593:0.000254513:0.39794:0.473747:0.437191:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.044896 ES:SE:LP:AF:SI:ID   0.000626332:0.000627781:0.49485:0.044896:0.420325:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741257 ES:SE:LP:AF:SI:ID   -0.000268555:0.000294173:0.443698:0.741257:0.425958:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275142 ES:SE:LP:AF:SI:ID   -0.000388331:0.000302009:0.69897:0.275142:0.388846:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.580967 ES:SE:LP:AF:SI:ID   -6.91953e-05:0.00024867:0.107905:0.580967:0.465698:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956603 ES:SE:LP:AF:SI:ID   0.000129892:0.000708549:0.0705811:0.956603:0.339465:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910125 ES:SE:LP:AF:SI:ID   -0.000443657:0.000469235:0.468521:0.910125:0.391908:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.06272  ES:SE:LP:AF:SI:ID   0.000547954:0.000536692:0.508638:0.06272:0.418452:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623059 ES:SE:LP:AF:SI:ID   -0.000400092:0.000298923:0.744727:0.623059:0.338912:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.093097 ES:SE:LP:AF:SI:ID   0.000315571:0.000458715:0.309804:0.093097:0.397311:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213536 ES:SE:LP:AF:SI:ID   -0.000538111:0.000319269:1.03621:0.213536:0.412646:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.15443  ES:SE:LP:AF:SI:ID   -0.00085371:0.000358699:1.76955:0.15443:0.420773:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.401082 ES:SE:LP:AF:SI:ID   0.000225038:0.000295556:0.346787:0.401082:0.337096:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414749 ES:SE:LP:AF:SI:ID   0.000178762:0.000234045:0.356547:0.414749:0.532876:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417128 ES:SE:LP:AF:SI:ID   0.00073287:0.00027009:2.17393:0.417128:0.39825:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253995 ES:SE:LP:AF:SI:ID   0.000500042:0.000303985:1:0.253995:0.404049:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090304 ES:SE:LP:AF:SI:ID   0.000127759:0.000462102:0.107905:0.090304:0.402912:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.089071 ES:SE:LP:AF:SI:ID   0.00039725:0.000464104:0.408935:0.089071:0.404541:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081218 ES:SE:LP:AF:SI:ID   0.000138146:0.000481321:0.113509:0.081218:0.408796:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438446 ES:SE:LP:AF:SI:ID   0.0002411:0.000257068:0.455932:0.438446:0.435397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382505 ES:SE:LP:AF:SI:ID   0.000407909:0.000275918:0.853872:0.382505:0.39221:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.159312 ES:SE:LP:AF:SI:ID   0.000688955:0.000351457:1.30103:0.159312:0.429054:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684383 ES:SE:LP:AF:SI:ID   0.000243754:0.000273746:0.431798:0.684383:0.43843:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079882 ES:SE:LP:AF:SI:ID   0.000254419:0.000486669:0.221849:0.079882:0.405239:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070759 ES:SE:LP:AF:SI:ID   5.64168e-05:0.000495543:0.0409586:0.070759:0.439754:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032914 ES:SE:LP:AF:SI:ID   0.00119347:0.000747193:0.958607:0.032914:0.39852:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073889 ES:SE:LP:AF:SI:ID   -0.000314124:0.000487237:0.283997:0.073889:0.436196:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.750787 ES:SE:LP:AF:SI:ID   -0.000561248:0.000309836:1.1549:0.750787:0.393859:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034045 ES:SE:LP:AF:SI:ID   0.000615367:0.000714066:0.408935:0.034045:0.425973:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034045 ES:SE:LP:AF:SI:ID   0.000615367:0.000714066:0.408935:0.034045:0.425973:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077317 ES:SE:LP:AF:SI:ID   0.000391316:0.000496547:0.366532:0.077317:0.401276:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077315 ES:SE:LP:AF:SI:ID   0.000262994:0.000481061:0.236572:0.077315:0.430178:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077119 ES:SE:LP:AF:SI:ID   0.000391127:0.00049671:0.366532:0.077119:0.40201:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077119 ES:SE:LP:AF:SI:ID   0.000391127:0.00049671:0.366532:0.077119:0.40201:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041449 ES:SE:LP:AF:SI:ID   0.00117545:0.000695799:1.04096:0.041449:0.370765:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.061005 ES:SE:LP:AF:SI:ID   -0.000350165:0.000527094:0.29243:0.061005:0.444727:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075329 ES:SE:LP:AF:SI:ID   0.000274767:0.000486874:0.244125:0.075329:0.429704:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075361 ES:SE:LP:AF:SI:ID   0.000280749:0.000486743:0.251812:0.075361:0.429781:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352703 ES:SE:LP:AF:SI:ID   7.25045e-07:0.000278288:-0:0.352703:0.399395:rs201754587