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/166e95f2-042c-409c-9c8c-b89d4181f2df/call-ldsc/inputs/-261044565/ieu-b-4809.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4809/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Dec 16 19:52:34 2021
Reading summary statistics from /data/cromwell-executions/qc/166e95f2-042c-409c-9c8c-b89d4181f2df/call-ldsc/inputs/-261044565/ieu-b-4809.vcf.gz ...
Read summary statistics for 12096462 SNPs.
Dropped 202555 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, 1220144 SNPs remain.
After merging with regression SNP LD, 1220144 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0431 (0.0043)
Lambda GC: 1.1129
Mean Chi^2: 1.1721
Intercept: 1.0218 (0.0078)
Ratio: 0.1265 (0.0454)
Analysis finished at Thu Dec 16 19:54:38 2021
Total time elapsed: 2.0m:4.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9498,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -3.2959e-06,
    "n": "-Inf",
    "n_snps": 12097504,
    "n_clumped_hits": 39,
    "n_p_sig": 3453,
    "n_mono": 0,
    "n_ns": 1283818,
    "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": 1376536,
    "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": 1220144,
    "ldsc_nsnp_merge_regression_ld": 1220144,
    "ldsc_observed_scale_h2_beta": 0.0431,
    "ldsc_observed_scale_h2_se": 0.0043,
    "ldsc_intercept_beta": 1.0218,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.1129,
    "ldsc_mean_chisq": 1.1721,
    "ldsc_ratio": 0.1267
}

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 TRUE
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 674 0.9999443 3 58 0 12053925 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 17422 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 71134 0 NA NA NA NA NA NA NA NA NA NA
logical N 12097504 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 8.764304e+00 5.889801e+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 7.868374e+07 5.624302e+07 302.0000000 3.248884e+07 6.922840e+07 1.144345e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.300000e-06 3.035800e-03 -0.1323800 -1.021900e-03 -1.350000e-05 9.867000e-04 1.406710e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.233900e-03 2.000600e-03 0.0005095 8.330000e-04 1.312400e-03 2.949800e-03 3.663960e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.871216e-01 2.928479e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.871226e-01 2.928214e-01 0.0000000 2.303792e-01 4.836845e-01 7.406559e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.629684e-01 3.018262e-01 0.0013690 1.835900e-02 1.206230e-01 4.442520e-01 9.986310e-01 ▇▂▂▁▁
numeric AF_reference 1376536 0.8862132 NA NA NA NA NA NA NA 2.159485e-01 2.516945e-01 0.0000000 1.317890e-02 1.096250e-01 3.426520e-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 -0.0014889 0.0010762 0.1700000 0.1665185 0.600633 NA NA
1 10352 rs1557426776 TA T -0.0017392 0.0011092 0.1199999 0.1168940 0.607088 NA NA
1 11008 rs575272151 C G 0.0035340 0.0018344 0.0539995 0.0540315 0.086716 0.0880591 NA
1 11012 rs544419019 C G 0.0035340 0.0018344 0.0539995 0.0540315 0.086716 0.0880591 NA
1 13110 rs540538026 G A 0.0037501 0.0024454 0.1299999 0.1251494 0.058961 0.0267572 NA
1 13116 rs62635286 T G 0.0002115 0.0014509 0.8800001 0.8841237 0.189513 0.0970447 NA
1 13118 rs200579949 A G 0.0002115 0.0014509 0.8800001 0.8841237 0.189513 0.0970447 NA
1 13273 rs531730856 G C 0.0002035 0.0017024 0.9000000 0.9048628 0.134078 0.0950479 NA
1 14464 rs546169444 A T -0.0020263 0.0015488 0.1900002 0.1907747 0.156680 0.0958466 NA
1 14599 rs531646671 T A 0.0028568 0.0014059 0.0420001 0.0421558 0.192148 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0012525 0.0005901 0.0340001 0.0337834 0.752169 0.643179 NA
23 154901964 rs697726 G A 0.0008790 0.0006218 0.1600000 0.1574538 0.348234 0.117616 NA
23 154902105 rs696316 G T 0.0012545 0.0005900 0.0329997 0.0334905 0.752149 0.636026 NA
23 154902889 rs697725 A T 0.0012348 0.0005898 0.0359998 0.0363112 0.751853 0.584106 NA
23 154903118 rs479770 G A 0.0012624 0.0005901 0.0320000 0.0324067 0.752202 0.643444 NA
23 154903224 rs480725 A T 0.0012624 0.0005901 0.0320000 0.0324152 0.752203 0.643444 NA
23 154903937 rs674707 G A 0.0012615 0.0005901 0.0329997 0.0325369 0.752209 0.643444 NA
23 154909055 rs473529 C G -0.0011323 0.0005555 0.0420001 0.0414994 0.303988 0.463046 NA
23 154918266 rs642043 C T -0.0012232 0.0005572 0.0280001 0.0281485 0.301862 0.478675 NA
23 154927581 rs644138 G A -0.0012364 0.0005573 0.0269998 0.0265262 0.301754 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.600633 ES:SE:LP:AF:SI:ID   -0.00148894:0.00107623:0.769551:0.600633:0.466089:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607088 ES:SE:LP:AF:SI:ID   -0.00173918:0.00110921:0.920819:0.607088:0.44449:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086716 ES:SE:LP:AF:SI:ID   0.00353403:0.00183435:1.26761:0.086716:0.486664:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086716 ES:SE:LP:AF:SI:ID   0.00353403:0.00183435:1.26761:0.086716:0.486664:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058961 ES:SE:LP:AF:SI:ID   0.0037501:0.00244543:0.886057:0.058961:0.39209:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189513 ES:SE:LP:AF:SI:ID   0.000211461:0.00145091:0.0555173:0.189513:0.404681:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189513 ES:SE:LP:AF:SI:ID   0.000211461:0.00145091:0.0555173:0.189513:0.404681:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134078 ES:SE:LP:AF:SI:ID   0.000203471:0.00170239:0.0457575:0.134078:0.390731:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.15668  ES:SE:LP:AF:SI:ID   -0.00202632:0.00154883:0.721246:0.15668:0.410824:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.192148 ES:SE:LP:AF:SI:ID   0.0028568:0.00140592:1.37675:0.192148:0.424479:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.192148 ES:SE:LP:AF:SI:ID   0.0028568:0.00140592:1.37675:0.192148:0.424479:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474321 ES:SE:LP:AF:SI:ID   0.000446207:0.0010926:0.167491:0.474321:0.437191:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045051 ES:SE:LP:AF:SI:ID   -0.00538646:0.00268862:1.34679:0.045051:0.420325:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741663 ES:SE:LP:AF:SI:ID   0.000869725:0.00126402:0.309804:0.741663:0.425958:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275179 ES:SE:LP:AF:SI:ID   -0.0010108:0.00129445:0.366532:0.275179:0.388846:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581079 ES:SE:LP:AF:SI:ID   -0.000129093:0.00106824:0.0457575:0.581079:0.465698:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.9564   ES:SE:LP:AF:SI:ID   0.00112883:0.00303085:0.148742:0.9564:0.339465:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.91039  ES:SE:LP:AF:SI:ID   -0.00178107:0.00201925:0.420216:0.91039:0.391908:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062623 ES:SE:LP:AF:SI:ID   -0.000347345:0.00229861:0.0555173:0.062623:0.418452:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.62422  ES:SE:LP:AF:SI:ID   -0.00057666:0.0012788:0.187087:0.62422:0.338912:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.09278  ES:SE:LP:AF:SI:ID   -0.0016303:0.00197506:0.387216:0.09278:0.397311:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213466 ES:SE:LP:AF:SI:ID   0.000920248:0.00136906:0.30103:0.213466:0.412646:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154554 ES:SE:LP:AF:SI:ID   -0.000607096:0.00153855:0.161151:0.154554:0.420773:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.399696 ES:SE:LP:AF:SI:ID   5.86681e-05:0.00126937:0.0177288:0.399696:0.337096:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414919 ES:SE:LP:AF:SI:ID   -0.000340612:0.00100261:0.136677:0.414919:0.532876:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417547 ES:SE:LP:AF:SI:ID   0.0013008:0.00115831:0.585027:0.417547:0.39825:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253655 ES:SE:LP:AF:SI:ID   -0.00131552:0.00130302:0.508638:0.253655:0.404049:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089752 ES:SE:LP:AF:SI:ID   0.000489979:0.00198795:0.091515:0.089752:0.402912:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088659 ES:SE:LP:AF:SI:ID   -6.96469e-05:0.00199457:0.0132283:0.088659:0.404541:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080814 ES:SE:LP:AF:SI:ID   0.000168289:0.00206954:0.0268721:0.080814:0.408796:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438548 ES:SE:LP:AF:SI:ID   -0.000111832:0.00109978:0.0362122:0.438548:0.435397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381625 ES:SE:LP:AF:SI:ID   -0.000717925:0.0011847:0.267606:0.381625:0.39221:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158364 ES:SE:LP:AF:SI:ID   0.000301746:0.00150665:0.0757207:0.158364:0.429054:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683664 ES:SE:LP:AF:SI:ID   0.00126918:0.00117288:0.552842:0.683664:0.43843:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079376 ES:SE:LP:AF:SI:ID   0.000710324:0.00209661:0.136677:0.079376:0.405239:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070757 ES:SE:LP:AF:SI:ID   -7.28606e-05:0.00211758:0.0132283:0.070757:0.439754:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032834 ES:SE:LP:AF:SI:ID   -0.00530577:0.00322292:1:0.032834:0.39852:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.07387  ES:SE:LP:AF:SI:ID   -0.00120347:0.00208514:0.251812:0.07387:0.436196:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751623 ES:SE:LP:AF:SI:ID   0.00118477:0.00132982:0.431798:0.751623:0.393859:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034055 ES:SE:LP:AF:SI:ID   -0.000353675:0.00304427:0.0409586:0.034055:0.425973:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034055 ES:SE:LP:AF:SI:ID   -0.000353675:0.00304427:0.0409586:0.034055:0.425973:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077092 ES:SE:LP:AF:SI:ID   0.000198804:0.00213351:0.0315171:0.077092:0.401276:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077553 ES:SE:LP:AF:SI:ID   -0.00204727:0.00205463:0.49485:0.077553:0.430178:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076897 ES:SE:LP:AF:SI:ID   0.00018844:0.0021339:0.0315171:0.076897:0.40201:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076897 ES:SE:LP:AF:SI:ID   0.00018844:0.0021339:0.0315171:0.076897:0.40201:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041642 ES:SE:LP:AF:SI:ID   0.00099473:0.00295348:0.130768:0.041642:0.370765:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060905 ES:SE:LP:AF:SI:ID   -0.000317364:0.0022606:0.05061:0.060905:0.444727:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075447 ES:SE:LP:AF:SI:ID   -0.00212879:0.00208189:0.508638:0.075447:0.429704:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075468 ES:SE:LP:AF:SI:ID   -0.00216801:0.00208164:0.522879:0.075468:0.429781:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.35254  ES:SE:LP:AF:SI:ID   -0.00138102:0.00119309:0.60206:0.35254:0.399395:rs201754587