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/a9dc6490-7195-4a9d-b1f7-ae6de0424d1e/call-ldsc/inputs/-261044352/ieu-b-4875.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4875/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Jan 28 02:27:39 2022
Reading summary statistics from /data/cromwell-executions/qc/a9dc6490-7195-4a9d-b1f7-ae6de0424d1e/call-ldsc/inputs/-261044352/ieu-b-4875.vcf.gz ...
Read summary statistics for 8628176 SNPs.
Dropped 152978 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, 1185809 SNPs remain.
After merging with regression SNP LD, 1185809 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0018 (0.0012)
Lambda GC: 1.0142
Mean Chi^2: 1.0181
Intercept: 1.0051 (0.0058)
Ratio: 0.2799 (0.3218)
Analysis finished at Fri Jan 28 02:29:28 2022
Total time elapsed: 1.0m:49.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9327,
    "inflation_factor": 1,
    "mean_EFFECT": 7.5525e-08,
    "n": "-Inf",
    "n_snps": 8629116,
    "n_clumped_hits": 2,
    "n_p_sig": 106,
    "n_mono": 0,
    "n_ns": 1064956,
    "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": 1065881,
    "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": 1185809,
    "ldsc_nsnp_merge_regression_ld": 1185809,
    "ldsc_observed_scale_h2_beta": 0.0018,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0051,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0142,
    "ldsc_mean_chisq": 1.0181,
    "ldsc_ratio": 0.2818
}

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 612 0.9999291 3 58 0 8601110 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 14117 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 58260 0 NA NA NA NA NA NA NA NA NA NA
logical N 8629116 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 8.850675e+00 5.948850e+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 7.840903e+07 5.641432e+07 302.0000000 3.200491e+07 6.882032e+07 1.143424e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-07 1.670000e-04 -0.0014486 -9.290000e-05 -9.000000e-07 9.150000e-05 1.618200e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.527000e-04 6.560000e-05 0.0000767 1.008000e-04 1.254000e-04 1.877000e-04 7.892000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.976503e-01 2.889851e-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 4.976511e-01 2.889609e-01 0.0000000 2.469694e-01 4.967509e-01 7.480756e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.355528e-01 2.872367e-01 0.0206280 8.209370e-02 2.432710e-01 5.446900e-01 9.793720e-01 ▇▃▂▂▂
numeric AF_reference 1065881 0.8764785 NA NA NA NA NA NA NA 2.913407e-01 2.519120e-01 0.0000000 8.266770e-02 2.146570e-01 4.522760e-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 -0.0001677 0.0001394 0.2300001 0.2288946 0.601321 NA NA
1 10352 rs1557426776 TA T -0.0002714 0.0001435 0.0589997 0.0586857 0.606977 NA NA
1 11008 rs575272151 C G -0.0001365 0.0002387 0.5700002 0.5673794 0.086188 0.0880591 NA
1 11012 rs544419019 C G -0.0001365 0.0002387 0.5700002 0.5673794 0.086188 0.0880591 NA
1 13110 rs540538026 G A -0.0002951 0.0003171 0.3500000 0.3519011 0.058732 0.0267572 NA
1 13116 rs62635286 T G -0.0002733 0.0001878 0.1499999 0.1455959 0.189403 0.0970447 NA
1 13118 rs200579949 A G -0.0002733 0.0001878 0.1499999 0.1455959 0.189403 0.0970447 NA
1 13273 rs531730856 G C 0.0002411 0.0002201 0.2700001 0.2733569 0.133943 0.0950479 NA
1 14464 rs546169444 A T -0.0001907 0.0001999 0.3400001 0.3401707 0.157043 0.0958466 NA
1 14599 rs531646671 T A -0.0001278 0.0001822 0.4799997 0.4830278 0.191564 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0002262 8.92e-05 0.0109999 0.0112673 0.751559 0.643179 NA
23 154901964 rs697726 G A 0.0000733 9.42e-05 0.4400003 0.4363035 0.347491 0.117616 NA
23 154902105 rs696316 G T 0.0002264 8.92e-05 0.0109999 0.0111867 0.751511 0.636026 NA
23 154902889 rs697725 A T 0.0002280 8.92e-05 0.0109999 0.0105822 0.751183 0.584106 NA
23 154903118 rs479770 G A 0.0002259 8.93e-05 0.0109999 0.0113760 0.751601 0.643444 NA
23 154903224 rs480725 A T 0.0002259 8.93e-05 0.0109999 0.0113671 0.751604 0.643444 NA
23 154903937 rs674707 G A 0.0002258 8.93e-05 0.0109999 0.0113969 0.751614 0.643444 NA
23 154909055 rs473529 C G -0.0001152 8.40e-05 0.1700000 0.1704450 0.305079 0.463046 NA
23 154918266 rs642043 C T -0.0001137 8.43e-05 0.1800002 0.1775061 0.302944 0.478675 NA
23 154927581 rs644138 G A -0.0001134 8.43e-05 0.1800002 0.1787419 0.302816 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601321 ES:SE:LP:AF:SI:ID   -0.000167706:0.000139382:0.638272:0.601321:0.466089:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606977 ES:SE:LP:AF:SI:ID   -0.000271372:0.000143542:1.22915:0.606977:0.44449:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086188 ES:SE:LP:AF:SI:ID   -0.000136495:0.000238663:0.244125:0.086188:0.486664:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086188 ES:SE:LP:AF:SI:ID   -0.000136495:0.000238663:0.244125:0.086188:0.486664:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058732 ES:SE:LP:AF:SI:ID   -0.00029515:0.000317056:0.455932:0.058732:0.39209:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189403 ES:SE:LP:AF:SI:ID   -0.000273258:0.000187772:0.823909:0.189403:0.404681:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189403 ES:SE:LP:AF:SI:ID   -0.000273258:0.000187772:0.823909:0.189403:0.404681:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133943 ES:SE:LP:AF:SI:ID   0.000241081:0.000220092:0.568636:0.133943:0.390731:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157043 ES:SE:LP:AF:SI:ID   -0.000190654:0.000199883:0.468521:0.157043:0.410824:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191564 ES:SE:LP:AF:SI:ID   -0.000127818:0.000182222:0.318759:0.191564:0.424479:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191564 ES:SE:LP:AF:SI:ID   -0.000127818:0.000182222:0.318759:0.191564:0.424479:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473993 ES:SE:LP:AF:SI:ID   -8.61859e-05:0.000141351:0.267606:0.473993:0.437191:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045017 ES:SE:LP:AF:SI:ID   0.000488998:0.000348026:0.79588:0.045017:0.420325:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741409 ES:SE:LP:AF:SI:ID   -0.000109411:0.000163459:0.30103:0.741409:0.425958:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275222 ES:SE:LP:AF:SI:ID   6.85404e-05:0.000167612:0.167491:0.275222:0.388846:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.58103  ES:SE:LP:AF:SI:ID   5.0132e-05:0.000138209:0.142668:0.58103:0.465698:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956501 ES:SE:LP:AF:SI:ID   0.000202726:0.000392829:0.21467:0.956501:0.339465:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910288 ES:SE:LP:AF:SI:ID   0.000226034:0.000260981:0.408935:0.910288:0.391908:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062676 ES:SE:LP:AF:SI:ID   0.000301978:0.000297722:0.508638:0.062676:0.418452:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623628 ES:SE:LP:AF:SI:ID   -0.000100372:0.000165827:0.267606:0.623628:0.338912:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092955 ES:SE:LP:AF:SI:ID   -0.000445119:0.000255086:1.09151:0.092955:0.397311:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213475 ES:SE:LP:AF:SI:ID   -0.000241322:0.000177273:0.769551:0.213475:0.412646:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154517 ES:SE:LP:AF:SI:ID   -0.000236636:0.000199168:0.638272:0.154517:0.420773:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400434 ES:SE:LP:AF:SI:ID   0.000148309:0.000164271:0.431798:0.400434:0.337096:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414848 ES:SE:LP:AF:SI:ID   5.27765e-05:0.000129838:0.167491:0.414848:0.532876:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417217 ES:SE:LP:AF:SI:ID   -9.1958e-05:0.000149963:0.267606:0.417217:0.39825:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253859 ES:SE:LP:AF:SI:ID   -0.000105722:0.000168706:0.275724:0.253859:0.404049:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090025 ES:SE:LP:AF:SI:ID   -0.000294776:0.000256947:0.60206:0.090025:0.402912:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088861 ES:SE:LP:AF:SI:ID   -0.000326355:0.000257934:0.677781:0.088861:0.404541:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081012 ES:SE:LP:AF:SI:ID   -0.000347294:0.000267563:0.721246:0.081012:0.408796:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438476 ES:SE:LP:AF:SI:ID   -8.61049e-05:0.000142568:0.259637:0.438476:0.435397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382118 ES:SE:LP:AF:SI:ID   6.61466e-05:0.00015326:0.173925:0.382118:0.39221:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158842 ES:SE:LP:AF:SI:ID   1.04484e-06:0.000195117:-0:0.158842:0.429054:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683941 ES:SE:LP:AF:SI:ID   -0.000346765:0.000151876:1.65758:0.683941:0.43843:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079619 ES:SE:LP:AF:SI:ID   -0.000377923:0.000270811:0.79588:0.079619:0.405239:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070749 ES:SE:LP:AF:SI:ID   -0.000272192:0.000274654:0.49485:0.070749:0.439754:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032892 ES:SE:LP:AF:SI:ID   -0.000657407:0.000415721:0.958607:0.032892:0.39852:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.07389  ES:SE:LP:AF:SI:ID   -0.000378074:0.000270155:0.79588:0.07389:0.436196:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751159 ES:SE:LP:AF:SI:ID   6.06268e-05:0.000172049:0.142668:0.751159:0.393859:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034044 ES:SE:LP:AF:SI:ID   -8.55421e-05:0.000395241:0.0809219:0.034044:0.425973:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034044 ES:SE:LP:AF:SI:ID   -8.55421e-05:0.000395241:0.0809219:0.034044:0.425973:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077194 ES:SE:LP:AF:SI:ID   -0.000257903:0.000275961:0.455932:0.077194:0.401276:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077448 ES:SE:LP:AF:SI:ID   1.12599e-05:0.000266482:0.0132283:0.077448:0.430178:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076998 ES:SE:LP:AF:SI:ID   -0.000254377:0.000276034:0.443698:0.076998:0.40201:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076998 ES:SE:LP:AF:SI:ID   -0.000254377:0.000276034:0.443698:0.076998:0.40201:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041516 ES:SE:LP:AF:SI:ID   -0.000448847:0.000384739:0.619789:0.041516:0.370765:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060959 ES:SE:LP:AF:SI:ID   -0.000252897:0.000292616:0.408935:0.060959:0.444727:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075409 ES:SE:LP:AF:SI:ID   5.26172e-05:0.000269843:0.0705811:0.075409:0.429704:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075436 ES:SE:LP:AF:SI:ID   5.18518e-05:0.000269789:0.0705811:0.075436:0.429781:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352718 ES:SE:LP:AF:SI:ID   0.000314341:0.00015446:1.37675:0.352718:0.399395:rs201754587