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/2f63c317-b008-4065-90c8-dd0d0eedef08/call-ldsc/inputs/-261044349/ieu-b-4878.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4878/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Thu Feb  3 02:47:42 2022
Reading summary statistics from /data/cromwell-executions/qc/2f63c317-b008-4065-90c8-dd0d0eedef08/call-ldsc/inputs/-261044349/ieu-b-4878.vcf.gz ...
Read summary statistics for 11561550 SNPs.
Dropped 195036 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, 1219243 SNPs remain.
After merging with regression SNP LD, 1219243 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0019 (0.0012)
Lambda GC: 1.0277
Mean Chi^2: 1.0226
Intercept: 1.0084 (0.0063)
Ratio: 0.3725 (0.2808)
Analysis finished at Thu Feb  3 02:49:37 2022
Total time elapsed: 1.0m:54.83s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9484,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -1.4009e-06,
    "n": "-Inf",
    "n_snps": 11562585,
    "n_clumped_hits": 4,
    "n_p_sig": 591,
    "n_mono": 0,
    "n_ns": 1260231,
    "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": 1299207,
    "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": 1219243,
    "ldsc_nsnp_merge_regression_ld": 1219243,
    "ldsc_observed_scale_h2_beta": 0.0019,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0084,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0277,
    "ldsc_mean_chisq": 1.0226,
    "ldsc_ratio": 0.3717
}

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 672 0.9999419 3 58 0 11522886 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 17075 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 69792 0 NA NA NA NA NA NA NA NA NA NA
logical N 11562585 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 8.782001e+00 5.900211e+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 7.863338e+07 5.628224e+07 302.0000000 3.240986e+07 6.914085e+07 1.143983e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.400000e-06 8.711000e-04 -0.0108073 -3.272000e-04 -2.700000e-06 3.190000e-04 1.470580e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.817000e-04 5.298000e-04 0.0002069 2.878000e-04 4.341000e-04 9.168000e-04 5.645100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.952142e-01 2.897670e-01 0.0000000 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 4.952133e-01 2.897391e-01 0.0000000 2.436588e-01 4.927485e-01 7.465787e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.724049e-01 3.014351e-01 0.0027470 2.347600e-02 1.361720e-01 4.600190e-01 9.972540e-01 ▇▂▂▁▂
numeric AF_reference 1299207 0.8876370 NA NA NA NA NA NA NA 2.240804e-01 2.528244e-01 0.0000000 1.717250e-02 1.214060e-01 3.570290e-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 -0.0002864 0.0003759 0.4500005 0.4461944 0.601305 NA NA
1 10352 rs1557426776 TA T -0.0002866 0.0003872 0.4600002 0.4591630 0.606976 NA NA
1 11008 rs575272151 C G -0.0007852 0.0006439 0.2200002 0.2226870 0.086164 0.0880591 NA
1 11012 rs544419019 C G -0.0007852 0.0006439 0.2200002 0.2226870 0.086164 0.0880591 NA
1 13110 rs540538026 G A -0.0011539 0.0008556 0.1800002 0.1774541 0.058713 0.0267572 NA
1 13116 rs62635286 T G -0.0001155 0.0005065 0.8200001 0.8196524 0.189414 0.0970447 NA
1 13118 rs200579949 A G -0.0001155 0.0005065 0.8200001 0.8196524 0.189414 0.0970447 NA
1 13273 rs531730856 G C -0.0009417 0.0005938 0.1100001 0.1127377 0.133889 0.0950479 NA
1 14464 rs546169444 A T 0.0002949 0.0005391 0.5800000 0.5843806 0.157068 0.0958466 NA
1 14599 rs531646671 T A -0.0000602 0.0004916 0.9000000 0.9025290 0.191570 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0002571 0.0002406 0.2900000 0.2853980 0.751569 0.643179 NA
23 154901964 rs697726 G A 0.0004941 0.0002540 0.0519996 0.0516782 0.347597 0.117616 NA
23 154902105 rs696316 G T 0.0002584 0.0002406 0.2800000 0.2829142 0.751522 0.636026 NA
23 154902889 rs697725 A T 0.0002612 0.0002405 0.2800000 0.2775359 0.751194 0.584106 NA
23 154903118 rs479770 G A 0.0002596 0.0002407 0.2800000 0.2806311 0.751613 0.643444 NA
23 154903224 rs480725 A T 0.0002596 0.0002407 0.2800000 0.2807740 0.751615 0.643444 NA
23 154903937 rs674707 G A 0.0002591 0.0002407 0.2800000 0.2816765 0.751625 0.643444 NA
23 154909055 rs473529 C G -0.0001965 0.0002266 0.3900004 0.3859265 0.305051 0.463046 NA
23 154918266 rs642043 C T -0.0001955 0.0002273 0.3900004 0.3896836 0.302916 0.478675 NA
23 154927581 rs644138 G A -0.0001938 0.0002274 0.3900004 0.3940965 0.302789 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601305 ES:SE:LP:AF:SI:ID   -0.000286355:0.000375905:0.346787:0.601305:0.466089:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606976 ES:SE:LP:AF:SI:ID   -0.000286591:0.000387167:0.337242:0.606976:0.44449:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086164 ES:SE:LP:AF:SI:ID   -0.000785221:0.000643933:0.657577:0.086164:0.486664:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086164 ES:SE:LP:AF:SI:ID   -0.000785221:0.000643933:0.657577:0.086164:0.486664:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058713 ES:SE:LP:AF:SI:ID   -0.00115386:0.000855576:0.744727:0.058713:0.39209:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189414 ES:SE:LP:AF:SI:ID   -0.000115478:0.0005065:0.0861861:0.189414:0.404681:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189414 ES:SE:LP:AF:SI:ID   -0.000115478:0.0005065:0.0861861:0.189414:0.404681:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133889 ES:SE:LP:AF:SI:ID   -0.000941744:0.000593783:0.958607:0.133889:0.390731:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157068 ES:SE:LP:AF:SI:ID   0.000294878:0.000539085:0.236572:0.157068:0.410824:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.19157  ES:SE:LP:AF:SI:ID   -6.02043e-05:0.000491595:0.0457575:0.19157:0.424479:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.19157  ES:SE:LP:AF:SI:ID   -6.02043e-05:0.000491595:0.0457575:0.19157:0.424479:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474006 ES:SE:LP:AF:SI:ID   4.28164e-05:0.000381326:0.0409586:0.474006:0.437191:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045012 ES:SE:LP:AF:SI:ID   0.000197365:0.00093887:0.0809219:0.045012:0.420325:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741384 ES:SE:LP:AF:SI:ID   -0.000428071:0.000440896:0.481486:0.741384:0.425958:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275265 ES:SE:LP:AF:SI:ID   0.000614965:0.000452012:0.769551:0.275265:0.388846:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581016 ES:SE:LP:AF:SI:ID   -6.79673e-05:0.000372777:0.0655015:0.581016:0.465698:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956517 ES:SE:LP:AF:SI:ID   0.0013432:0.00106013:0.677781:0.956517:0.339465:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910277 ES:SE:LP:AF:SI:ID   -0.000157628:0.000703865:0.0861861:0.910277:0.391908:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062675 ES:SE:LP:AF:SI:ID   0.000262685:0.000802871:0.130768:0.062675:0.418452:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.62364  ES:SE:LP:AF:SI:ID   3.60992e-05:0.000447216:0.0268721:0.62364:0.338912:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092938 ES:SE:LP:AF:SI:ID   -0.000932563:0.000688216:0.744727:0.092938:0.397311:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213485 ES:SE:LP:AF:SI:ID   -8.98376e-05:0.000478137:0.0705811:0.213485:0.412646:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154552 ES:SE:LP:AF:SI:ID   0.00040479:0.000537126:0.346787:0.154552:0.420773:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400437 ES:SE:LP:AF:SI:ID   0.000205845:0.000443061:0.19382:0.400437:0.337096:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.41484  ES:SE:LP:AF:SI:ID   -1.72714e-05:0.000350281:0.0177288:0.41484:0.532876:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417219 ES:SE:LP:AF:SI:ID   -9.09528e-05:0.000404514:0.0861861:0.417219:0.39825:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253846 ES:SE:LP:AF:SI:ID   -0.00026623:0.000455043:0.251812:0.253846:0.404049:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090003 ES:SE:LP:AF:SI:ID   -0.000943453:0.00069331:0.769551:0.090003:0.402912:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088833 ES:SE:LP:AF:SI:ID   -0.00115142:0.000695963:1.00877:0.088833:0.404541:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080982 ES:SE:LP:AF:SI:ID   -0.00132256:0.000722006:1.17393:0.080982:0.408796:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438412 ES:SE:LP:AF:SI:ID   -0.000690534:0.000384533:1.13668:0.438412:0.435397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382072 ES:SE:LP:AF:SI:ID   -0.00041138:0.000413414:0.49485:0.382072:0.39221:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158825 ES:SE:LP:AF:SI:ID   -0.000284544:0.000526364:0.229148:0.158825:0.429054:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684005 ES:SE:LP:AF:SI:ID   0.000326435:0.000409803:0.366532:0.684005:0.43843:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079585 ES:SE:LP:AF:SI:ID   -0.00151237:0.000730807:1.40894:0.079585:0.405239:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.0708   ES:SE:LP:AF:SI:ID   0.00145635:0.000740356:1.3098:0.0708:0.439754:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032897 ES:SE:LP:AF:SI:ID   -0.000235616:0.00112108:0.0809219:0.032897:0.39852:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.07394  ES:SE:LP:AF:SI:ID   0.00125853:0.000728273:1.07572:0.07394:0.436196:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751176 ES:SE:LP:AF:SI:ID   0.000282102:0.000464154:0.267606:0.751176:0.393859:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034053 ES:SE:LP:AF:SI:ID   0.000578619:0.00106533:0.229148:0.034053:0.425973:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034053 ES:SE:LP:AF:SI:ID   0.000578619:0.00106533:0.229148:0.034053:0.425973:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.07718  ES:SE:LP:AF:SI:ID   -0.000730586:0.000744527:0.481486:0.07718:0.401276:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077454 ES:SE:LP:AF:SI:ID   0.000197745:0.000718694:0.107905:0.077454:0.430178:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076984 ES:SE:LP:AF:SI:ID   -0.000724012:0.000744721:0.481486:0.076984:0.40201:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076984 ES:SE:LP:AF:SI:ID   -0.000724012:0.000744721:0.481486:0.076984:0.40201:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041536 ES:SE:LP:AF:SI:ID   0.000879571:0.00103744:0.39794:0.041536:0.370765:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.061005 ES:SE:LP:AF:SI:ID   0.00152887:0.000788703:1.27572:0.061005:0.444727:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075413 ES:SE:LP:AF:SI:ID   0.000186902:0.000727767:0.09691:0.075413:0.429704:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.07544  ES:SE:LP:AF:SI:ID   0.000181771:0.00072762:0.09691:0.07544:0.429781:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352672 ES:SE:LP:AF:SI:ID   -0.000181736:0.000416685:0.180456:0.352672:0.399395:rs201754587