Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std 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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-30/ieu-a-30.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-30/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 09:23:07 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-30/ieu-a-30.vcf.gz ...
Read summary statistics for 11112707 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1289335 SNPs remain.
After merging with regression SNP LD, 1289335 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.4729 (0.0524)
Lambda GC: 1.1396
Mean Chi^2: 1.2271
Intercept: 1.0305 (0.0083)
Ratio: 0.1342 (0.0364)
Analysis finished at Wed Feb  5 09:24:45 2020
Total time elapsed: 1.0m:38.51s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9552,
    "inflation_factor": 1.0846,
    "mean_EFFECT": 0.0472,
    "n": 20883,
    "n_snps": 11112707,
    "n_clumped_hits": 53,
    "n_p_sig": 5237,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 337907,
    "n_est": 20199.7143,
    "ratio_se_n": 0.9835,
    "mean_diff": -0.0458,
    "ratio_diff": 2.5516,
    "sd_y_est1": 2.4788,
    "sd_y_est2": 2.4379,
    "r2_sum1": 0.8914,
    "r2_sum2": 0.1451,
    "r2_sum3": 0.15,
    "r2_sum4": 0.1537,
    "ldsc_nsnp_merge_refpanel_ld": 1289335,
    "ldsc_nsnp_merge_regression_ld": 1289335,
    "ldsc_observed_scale_h2_beta": 0.4729,
    "ldsc_observed_scale_h2_se": 0.0524,
    "ldsc_intercept_beta": 1.0305,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.1396,
    "ldsc_mean_chisq": 1.2271,
    "ldsc_ratio": 0.1343
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
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 TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 59 0 11112705 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.678906e+00 5.782672e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.868417e+07 5.646563e+07 8.28000e+02 3.239124e+07 6.916853e+07 1.145303e+08 2.492395e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.720560e-02 3.479891e+00 -7.07933e+02 -3.640470e-02 1.199300e-03 4.039500e-02 7.085750e+02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.370718e+00 1.620056e+02 2.18000e-02 2.810000e-02 5.140000e-02 1.355000e-01 5.276000e+04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.876926e-01 2.917999e-01 0.00000e+00 2.330000e-01 4.823997e-01 7.406994e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.876922e-01 2.918002e-01 0.00000e+00 2.330341e-01 4.823477e-01 7.407163e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.952295e-01 2.549277e-01 2.28170e-03 1.100000e-02 6.600000e-02 2.980040e-01 9.977180e-01 ▇▂▁▁▁
numeric AF_reference 337907 0.9695927 NA NA NA NA NA 2.000123e-01 2.492573e-01 0.00000e+00 1.058310e-02 8.686100e-02 3.071090e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.088300e+04 0.000000e+00 2.08830e+04 2.088300e+04 2.088300e+04 2.088300e+04 2.088300e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10611 rs189107123 C G -0.2040020 0.1497 0.1728001 0.1729648 0.0207150 NA 20883
1 51479 rs116400033 T A -0.0826971 0.0528 0.1173000 0.1172941 0.1905740 0.1281950 20883
1 52058 rs62637813 G C -0.1638960 0.1095 0.1343999 0.1344539 0.0426866 NA 20883
1 52144 rs190291950 T A -0.1436970 0.2006 0.4737999 0.4737839 0.0123430 0.0009984 20883
1 54421 rs146477069 A G 0.1184010 0.0870 0.1732000 0.1735355 0.0640000 NA 20883
1 54490 rs141149254 G A -0.0411971 0.0593 0.4874005 0.4872286 0.1417150 0.0960463 20883
1 54676 rs2462492 C T -0.0903953 0.0565 0.1097999 0.1096170 0.1665740 NA 20883
1 54753 rs143174675 T G -0.1670980 0.1282 0.1925001 0.1924326 0.0307150 NA 20883
1 55164 rs3091274 C A 0.0594003 0.1028 0.5634002 0.5633830 0.9497150 0.9233230 20883
1 55299 rs10399749 C T 0.0467977 0.0550 0.3951000 0.3948431 0.1755700 NA 20883
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51227937 rs6009970 A C -0.7670990 1.9330 0.6914997 0.6914827 0.9949310 1.0000000 20883
22 51229805 rs9616985 T C -0.0197046 0.0538 0.7136003 0.7141737 0.0758590 0.0730831 20883
22 51229855 rs144549712 G A 0.0239021 0.0561 0.6697998 0.6700624 0.0984722 0.1160140 20883
22 51234159 rs8138356 T A -0.2968980 0.2918 0.3089001 0.3089295 0.0067144 0.0215655 20883
22 51234677 rs189571549 A C -0.2981990 0.2856 0.2963999 0.2964326 0.0070000 0.0227636 20883
22 51234799 rs191117135 G A 0.2549990 0.2066 0.2171001 0.2171044 0.0067952 0.0059904 20883
22 51237063 rs3896457 T C -0.0003999 0.0378 0.9925000 0.9915586 0.2430000 0.2050720 20883
22 51238249 rs149733995 A C -0.0739008 0.0571 0.1958001 0.1955844 0.0815740 NA 20883
23 50040891 rs192267219 C T -0.0966981 0.1525 0.5257000 0.5260248 0.9870000 0.0222517 20883
23 100784211 rs188350543 C A 0.0075018 0.0290 0.7954000 0.7958803 0.7374300 0.6498010 20883

bcf preview

1   10611   rs189107123 C   G   .   PASS    AF=0.020715 ES:SE:LP:AF:SS:ID   -0.204002:0.1497:0.762456:0.020715:20883:rs189107123
1   51479   rs116400033 T   A   .   PASS    AF=0.190574 ES:SE:LP:AF:SS:ID   -0.0826971:0.0528:0.930702:0.190574:20883:rs116400033
1   52058   rs62637813  G   C   .   PASS    AF=0.0426866    ES:SE:LP:AF:SS:ID   -0.163896:0.1095:0.871601:0.0426866:20883:rs62637813
1   52144   rs190291950 T   A   .   PASS    AF=0.012343 ES:SE:LP:AF:SS:ID   -0.143697:0.2006:0.324405:0.012343:20883:rs190291950
1   54421   rs146477069 A   G   .   PASS    AF=0.064    ES:SE:LP:AF:SS:ID   0.118401:0.087:0.761452:0.064:20883:rs146477069
1   54490   rs141149254 G   A   .   PASS    AF=0.141715 ES:SE:LP:AF:SS:ID   -0.0411971:0.0593:0.312114:0.141715:20883:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.166574 ES:SE:LP:AF:SS:ID   -0.0903953:0.0565:0.959398:0.166574:20883:rs2462492
1   54753   rs143174675 T   G   .   PASS    AF=0.030715 ES:SE:LP:AF:SS:ID   -0.167098:0.1282:0.715569:0.030715:20883:rs143174675
1   55164   rs3091274   C   A   .   PASS    AF=0.949715 ES:SE:LP:AF:SS:ID   0.0594003:0.1028:0.249183:0.949715:20883:rs3091274
1   55299   rs10399749  C   T   .   PASS    AF=0.17557  ES:SE:LP:AF:SS:ID   0.0467977:0.055:0.403293:0.17557:20883:rs10399749
1   55326   rs3107975   T   C   .   PASS    AF=0.021285 ES:SE:LP:AF:SS:ID   0.214394:0.1348:0.951947:0.021285:20883:rs3107975
1   55394   rs2949420   T   A   .   PASS    AF=0.013457 ES:SE:LP:AF:SS:ID   -0.012599:0.1843:0.0243385:0.013457:20883:rs2949420
1   55850   rs191890754 C   G   .   PASS    AF=0.008    ES:SE:LP:AF:SS:ID   0.0628972:0.1919:0.128953:0.008:20883:rs191890754
1   55852   rs184233019 G   C   .   PASS    AF=0.00519943   ES:SE:LP:AF:SS:ID   0.395698:0.6303:0.275642:0.00519943:20883:rs184233019
1   58814   rs114420996 G   A   .   PASS    AF=0.0827412    ES:SE:LP:AF:SS:ID   0.130396:0.0752:1.08071:0.0827412:20883:rs114420996
1   61462   rs56992750  T   A   .   PASS    AF=0.00659141   ES:SE:LP:AF:SS:ID   -0.333796:0.3461:0.475085:0.00659141:20883:rs56992750
1   61987   rs76735897  A   G   .   PASS    AF=0.335715 ES:SE:LP:AF:SS:ID   -0.0425038:0.044:0.475864:0.335715:20883:rs76735897
1   61989   rs77573425  G   C   .   PASS    AF=0.335715 ES:SE:LP:AF:SS:ID   -0.0423962:0.0439:0.475994:0.335715:20883:rs77573425
1   64649   rs181431124 A   C   .   PASS    AF=0.02057  ES:SE:LP:AF:SS:ID   0.279304:0.1362:1.39491:0.02057:20883:rs181431124
1   66162   rs62639105  A   T   .   PASS    AF=0.327715 ES:SE:LP:AF:SS:ID   -0.0537967:0.0442:0.650917:0.327715:20883:rs62639105
1   66176   rs28552463  T   A   .   PASS    AF=0.00815528   ES:SE:LP:AF:SS:ID   0.457298:0.2437:1.21789:0.00815528:20883:rs28552463
1   66219   rs181028663 A   T   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.248205:0.1522:0.987163:0.021:20883:rs181028663
1   66331   rs186063952 A   C   .   PASS    AF=0.006715 ES:SE:LP:AF:SS:ID   -0.511697:0.3437:0.864549:0.006715:20883:rs186063952
1   66442   rs192044252 T   A   .   PASS    AF=0.0198852    ES:SE:LP:AF:SS:ID   0.108397:0.1541:0.317133:0.0198852:20883:rs192044252
1   66457   rs13328655  T   A   .   PASS    AF=0.0106856    ES:SE:LP:AF:SS:ID   -0.0540972:0.1989:0.104799:0.0106856:20883:rs13328655
1   66507   rs12401368  T   A   .   PASS    AF=0.0951866    ES:SE:LP:AF:SS:ID   -0.00290421:0.0716:0.014349:0.0951866:20883:rs12401368
1   73841   rs143773730 C   T   .   PASS    AF=0.231    ES:SE:LP:AF:SS:ID   0.00420116:0.0492:0.0303977:0.231:20883:rs143773730
1   77961   rs78385339  G   A   .   PASS    AF=0.0644137    ES:SE:LP:AF:SS:ID   0.109697:0.0872:0.681311:0.0644137:20883:rs78385339
1   79137   rs143777184 A   T   .   PASS    AF=0.006856 ES:SE:LP:AF:SS:ID   0.282204:0.4248:0.295421:0.006856:20883:rs143777184
1   79772   rs147215883 C   G   .   PASS    AF=0.080715 ES:SE:LP:AF:SS:ID   -0.0158044:0.0811:0.0727323:0.080715:20883:rs147215883
1   82163   rs139113303 G   A   .   PASS    AF=0.0526   ES:SE:LP:AF:SS:ID   0.0133011:0.0975:0.0498299:0.0526:20883:rs139113303
1   82249   rs1851945   A   G   .   PASS    AF=0.036    ES:SE:LP:AF:SS:ID   0.0628972:0.1186:0.224535:0.036:20883:rs1851945
1   82609   rs149189449 C   G   .   PASS    AF=0.056    ES:SE:LP:AF:SS:ID   -0.00370313:0.0945:0.0138107:0.056:20883:rs149189449
1   82676   rs185237834 T   G   .   PASS    AF=0.086715 ES:SE:LP:AF:SS:ID   -0.0273038:0.0788:0.137332:0.086715:20883:rs185237834
1   82734   rs4030331   T   C   .   PASS    AF=0.18357  ES:SE:LP:AF:SS:ID   0.0216016:0.0557:0.15602:0.18357:20883:rs4030331
1   83771   rs189906733 T   G   .   PASS    AF=0.003711 ES:SE:LP:AF:SS:ID   4.32754:4.652:0.453211:0.003711:20883:rs189906733
1   84002   rs28850140  G   A   .   PASS    AF=0.109715 ES:SE:LP:AF:SS:ID   -0.00930314:0.0676:0.0502685:0.109715:20883:rs28850140
1   84010   rs186443818 G   A   .   PASS    AF=0.0515415    ES:SE:LP:AF:SS:ID   0.169802:0.0997:1.0532:0.0515415:20883:rs186443818
1   84139   rs183605470 A   T   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.1994:0.2642:0.346305:0.01:20883:rs183605470
1   84244   rs191297051 A   C   .   PASS    AF=0.09843  ES:SE:LP:AF:SS:ID   -0.0613961:0.075:0.383735:0.09843:20883:rs191297051
1   84295   rs183209871 G   A   .   PASS    AF=0.00541306   ES:SE:LP:AF:SS:ID   -0.413396:0.4262:0.478731:0.00541306:20883:rs183209871
1   85063   rs187802690 T   C   .   PASS    AF=0.026    ES:SE:LP:AF:SS:ID   -0.0558982:0.1336:0.170118:0.026:20883:rs187802690
1   85597   rs192472955 A   C   .   PASS    AF=0.076715 ES:SE:LP:AF:SS:ID   -0.0260965:0.0811:0.126389:0.076715:20883:rs192472955
1   86018   rs142878000 C   G   .   PASS    AF=0.098    ES:SE:LP:AF:SS:ID   -0.00929665:0.0745:0.0455645:0.098:20883:rs142878000
1   86028   rs114608975 T   C   .   PASS    AF=0.058    ES:SE:LP:AF:SS:ID   -0.00750179:0.0924:0.0289098:0.058:20883:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0607144    ES:SE:LP:AF:SS:ID   -0.00399798:0.0897:0.0156077:0.0607144:20883:rs116504101
1   86303   rs2949417   G   T   .   PASS    AF=0.0987437    ES:SE:LP:AF:SS:ID   -0.0293979:0.0726:0.163676:0.0987437:20883:rs2949417
1   86331   rs115209712 A   G   .   PASS    AF=0.099715 ES:SE:LP:AF:SS:ID   -0.0227004:0.0724:0.122974:0.099715:20883:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.01257  ES:SE:LP:AF:SS:ID   0.188597:0.1866:0.505567:0.01257:20883:rs188486692
1   87190   rs1524602   G   A   .   PASS    AF=0.152711 ES:SE:LP:AF:SS:ID   0.140996:0.06:1.72469:0.152711:20883:rs1524602