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-294/ieu-a-294.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-294/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 21:09:06 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-294/ieu-a-294.vcf.gz ...
Read summary statistics for 125253 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, 50575 SNPs remain.
After merging with regression SNP LD, 50575 SNPs remain.
WARNING: number of SNPs less than 200k; this is almost always bad.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 3.5478 (0.4223)
Lambda GC: 2.5951
Mean Chi^2: 6.5486
Intercept: 1.537 (0.0775)
Ratio: 0.0968 (0.014)
Analysis finished at Tue Feb  4 21:09:16 2020
Total time elapsed: 9.88s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7665,
    "inflation_factor": 3.0818,
    "mean_EFFECT": 0.0002,
    "n": 65642,
    "n_snps": 125253,
    "n_clumped_hits": 134,
    "n_p_sig": 7495,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 29,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 848,
    "n_est": 65950.5747,
    "ratio_se_n": 1.0023,
    "mean_diff": 0.0002,
    "ratio_diff": 0.7166,
    "sd_y_est1": 1.8494,
    "sd_y_est2": 1.8537,
    "r2_sum1": 0.633,
    "r2_sum2": 0.1851,
    "r2_sum3": 0.1842,
    "r2_sum4": 0.1836,
    "ldsc_nsnp_merge_refpanel_ld": 50575,
    "ldsc_nsnp_merge_regression_ld": 50575,
    "ldsc_observed_scale_h2_beta": 3.5478,
    "ldsc_observed_scale_h2_se": 0.4223,
    "ldsc_intercept_beta": 1.537,
    "ldsc_intercept_se": 0.0775,
    "ldsc_lambda_gc": 2.5951,
    "ldsc_mean_chisq": 6.5486,
    "ldsc_ratio": 0.0968
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta TRUE
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 5 25 0 125253 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 8.085100e+00 5.769473e+00 1.0000e+00 3.000000e+00 6.000000e+00 1.200000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.909516e+07 5.780924e+07 6.3411e+04 3.292569e+07 6.222801e+07 1.176693e+08 2.492107e+08 ▇▅▃▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.765000e-04 5.329470e-02 -1.1825e+00 -2.031740e-02 -4.374000e-04 1.986030e-02 1.259280e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.233890e-02 2.710410e-02 9.7639e-03 1.102320e-02 1.375100e-02 2.206100e-02 8.461290e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 3.270993e-01 3.152972e-01 0.0000e+00 2.360750e-02 2.363845e-01 5.857887e-01 9.999970e-01 ▇▂▂▂▂
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 3.270993e-01 3.152972e-01 0.0000e+00 2.360760e-02 2.363839e-01 5.857881e-01 9.999970e-01 ▇▂▂▂▂
numeric AF 0 1.0000000 NA NA NA NA NA 3.115968e-01 2.834389e-01 1.4900e-05 7.054000e-02 2.206000e-01 4.996000e-01 9.999850e-01 ▇▃▂▂▂
numeric AF_reference 848 0.9932297 NA NA NA NA NA 2.856280e-01 2.579406e-01 1.9970e-04 7.248400e-02 2.046730e-01 4.452880e-01 1.000000e+00 ▇▃▂▂▁
numeric N 0 1.0000000 NA NA NA NA NA 6.564200e+04 0.000000e+00 6.5642e+04 6.564200e+04 6.564200e+04 6.564200e+04 6.564200e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1118275 rs61733845 C T -0.0050020 0.0255474 0.8447716 0.8447719 0.04416 0.185703 65642
1 1120431 rs1320571 G A -0.0072789 0.0251118 0.7719248 0.7719241 0.04653 0.185304 65642
1 1135242 rs9729550 A C 0.0474646 0.0117498 0.0000535 0.0000535 0.25870 0.551917 65642
1 1140435 rs1815606 G T 0.0417639 0.0113960 0.0002475 0.0002475 0.31790 0.712061 65642
1 1163804 rs7515488 C T 0.0874308 0.0138634 0.0000000 0.0000000 0.14860 0.186901 65642
1 1165310 rs11260562 G A 0.0914881 0.0210530 0.0000139 0.0000139 0.05560 0.101837 65642
1 1173611 rs6697886 G A 0.0912882 0.0143832 0.0000000 0.0000000 0.13730 0.220647 65642
1 1186502 rs6603785 A T 0.0943327 0.0152899 0.0000000 0.0000000 0.11950 0.246206 65642
1 1194804 rs11804831 T C 0.0767614 0.0129065 0.0000000 0.0000000 0.18560 0.685903 65642
1 1218086 rs6603788 C T 0.0511661 0.0186037 0.0059537 0.0059537 0.07697 0.469449 65642
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50966914 rs470119 T C -0.0521197 0.0101490 0.0000003 0.0000003 0.609800 0.5547120 65642
22 50971752 rs131794 A C -0.0577899 0.0121158 0.0000018 0.0000018 0.791900 0.8326680 65642
22 50988193 rs131779 A G -0.0261271 0.0109060 0.0165901 0.0165903 0.657900 0.5802720 65642
22 50999182 rs140518 C T -0.0316416 0.0109425 0.0038327 0.0038326 0.696600 0.7655750 65642
22 51078251 rs4040041 C T -0.0017874 0.0104564 0.8642739 0.8642737 0.373100 0.4666530 65642
22 51094926 rs9616810 C T 0.0162246 0.0121480 0.1816896 0.1816873 0.218600 0.2224440 65642
22 51105556 rs9616812 C T -0.0077821 0.0102872 0.4493616 0.4493592 0.483200 0.3628190 65642
22 51109992 rs9628185 T C -0.0075342 0.0103902 0.4683721 0.4683738 0.484300 0.4053510 65642
22 51134186 rs8135777 A G -0.3165570 0.2543200 0.2132348 0.2132350 0.000446 0.0273562 65642
22 51156666 rs9628187 C T -0.0037510 0.0130736 0.7741765 0.7741758 0.203200 0.1299920 65642

bcf preview

1   1118275 rs61733845  C   T   .   PASS    AF=0.04416  ES:SE:LP:AF:SS:ID   -0.00500201:0.0255474:0.0732607:0.04416:65642:rs61733845
1   1120431 rs1320571   G   A   .   PASS    AF=0.04653  ES:SE:LP:AF:SS:ID   -0.00727888:0.0251118:0.112425:0.04653:65642:rs1320571
1   1135242 rs9729550   A   C   .   PASS    AF=0.2587   ES:SE:LP:AF:SS:ID   0.0474646:0.0117498:4.27133:0.2587:65642:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.3179   ES:SE:LP:AF:SS:ID   0.0417639:0.011396:3.60637:0.3179:65642:rs1815606
1   1163804 rs7515488   C   T   .   PASS    AF=0.1486   ES:SE:LP:AF:SS:ID   0.0874308:0.0138634:9.54471:0.1486:65642:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.0556   ES:SE:LP:AF:SS:ID   0.0914881:0.021053:4.85734:0.0556:65642:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.1373   ES:SE:LP:AF:SS:ID   0.0912882:0.0143832:9.65802:0.1373:65642:rs6697886
1   1186502 rs6603785   A   T   .   PASS    AF=0.1195   ES:SE:LP:AF:SS:ID   0.0943327:0.0152899:9.16453:0.1195:65642:rs6603785
1   1194804 rs11804831  T   C   .   PASS    AF=0.1856   ES:SE:LP:AF:SS:ID   0.0767614:0.0129065:8.56496:0.1856:65642:rs11804831
1   1218086 rs6603788   C   T   .   PASS    AF=0.07697  ES:SE:LP:AF:SS:ID   0.0511661:0.0186037:2.22521:0.07697:65642:rs6603788
1   1227897 rs3737721   A   G   .   PASS    AF=0.002436 ES:SE:LP:AF:SS:ID   0.0629665:0.0734371:0.407588:0.002436:65642:rs3737721
1   1231656 rs1749951   G   A   .   PASS    AF=0.04028  ES:SE:LP:AF:SS:ID   0.0371784:0.0264753:0.795229:0.04028:65642:rs1749951
1   1233941 rs1739855   T   C   .   PASS    AF=0.07333  ES:SE:LP:AF:SS:ID   0.0483781:0.0190326:1.95756:0.07333:65642:rs1739855
1   1241529 rs1536168   A   G   .   PASS    AF=0.95394  ES:SE:LP:AF:SS:ID   -0.0405752:0.024294:1.0228:0.95394:65642:rs1536168
1   1242468 rs2274264   G   A   .   PASS    AF=0.002467 ES:SE:LP:AF:SS:ID   0.0542622:0.0782352:0.311628:0.002467:65642:rs2274264
1   1247494 rs12103 T   C   .   PASS    AF=0.8166   ES:SE:LP:AF:SS:ID   -0.0867354:0.0130755:10.4841:0.8166:65642:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.8026   ES:SE:LP:AF:SS:ID   -0.0789884:0.0128081:9.15753:0.8026:65642:rs12142199
1   1254255 rs62623580  G   A   .   PASS    AF=0.007606 ES:SE:LP:AF:SS:ID   0.0695751:0.0562643:0.665054:0.007606:65642:rs62623580
1   1335790 rs1240708   A   G   .   PASS    AF=0.1737   ES:SE:LP:AF:SS:ID   0.0814097:0.0132196:9.13345:0.1737:65642:rs1240708
1   1493727 rs880051    G   A   .   PASS    AF=0.232    ES:SE:LP:AF:SS:ID   0.0571914:0.0117629:5.93482:0.232:65642:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.1208   ES:SE:LP:AF:SS:ID   0.0378595:0.0155007:1.836:0.1208:65642:rs2296716
1   1611995 rs4074196   A   G   .   PASS    AF=0.4414   ES:SE:LP:AF:SS:ID   -0.00916736:0.0116551:0.364977:0.4414:65642:rs4074196
1   1706160 rs7531583   A   G   .   PASS    AF=0.77 ES:SE:LP:AF:SS:ID   -0.0357758:0.011644:2.67306:0.77:65642:rs7531583
1   1721479 rs2272908   C   T   .   PASS    AF=0.4974   ES:SE:LP:AF:SS:ID   -0.0506909:0.00995343:6.45246:0.4974:65642:rs2272908
1   1723031 rs9660180   G   A   .   PASS    AF=0.4974   ES:SE:LP:AF:SS:ID   -0.0516131:0.00997657:6.63858:0.4974:65642:rs9660180
1   1781220 rs6681938   T   C   .   PASS    AF=0.2996   ES:SE:LP:AF:SS:ID   -0.0249012:0.011141:1.59499:0.2996:65642:rs6681938
1   1838516 rs2377037   C   A   .   PASS    AF=0.2747   ES:SE:LP:AF:SS:ID   0.0362376:0.0113843:2.83656:0.2747:65642:rs2377037
1   1840038 rs2474461   T   C   .   PASS    AF=0.95331  ES:SE:LP:AF:SS:ID   -0.0692045:0.0237532:2.44681:0.95331:65642:rs2474461
1   1853288 rs1884454   G   T   .   PASS    AF=0.2694   ES:SE:LP:AF:SS:ID   0.0342632:0.0114288:2.56576:0.2694:65642:rs1884454
1   1855319 rs2295362   C   T   .   PASS    AF=0.0452   ES:SE:LP:AF:SS:ID   0.0452788:0.0244794:1.19138:0.0452:65642:rs2295362
1   1871337 rs16824543  G   A   .   PASS    AF=0.04241  ES:SE:LP:AF:SS:ID   0.0357672:0.0253662:0.79989:0.04241:65642:rs16824543
1   1873625 rs12758705  G   A   .   PASS    AF=0.2651   ES:SE:LP:AF:SS:ID   0.0340289:0.0115991:2.47511:0.2651:65642:rs12758705
1   1881070 rs4648596   G   A   .   PASS    AF=0.04073  ES:SE:LP:AF:SS:ID   0.0456525:0.0266091:1.06438:0.04073:65642:rs4648596
1   1888193 rs3820011   C   A   .   PASS    AF=0.2698   ES:SE:LP:AF:SS:ID   0.0329573:0.0116991:2.31458:0.2698:65642:rs3820011
1   2024064 rs2459994   C   T   .   PASS    AF=0.1824   ES:SE:LP:AF:SS:ID   0.0284659:0.0135275:1.45157:0.1824:65642:rs2459994
1   2146966 rs7512482   T   C   .   PASS    AF=0.1674   ES:SE:LP:AF:SS:ID   -0.0246049:0.0143806:1.06006:0.1674:65642:rs7512482
1   2202774 rs6673129   C   T   .   PASS    AF=0.1651   ES:SE:LP:AF:SS:ID   0.0166108:0.0144719:0.600235:0.1651:65642:rs6673129
1   2229478 rs12562937  C   T   .   PASS    AF=0.1998   ES:SE:LP:AF:SS:ID   0.0220428:0.0132813:1.01332:0.1998:65642:rs12562937
1   2283896 rs2840528   A   G   .   PASS    AF=0.4158   ES:SE:LP:AF:SS:ID   0.000250701:0.0104941:0.0083573:0.4158:65642:rs2840528
1   2290143 rs34587196  G   A   .   PASS    AF=0.01202  ES:SE:LP:AF:SS:ID   0.060328:0.0475885:0.68845:0.01202:65642:rs34587196
1   2404256 rs2494626   C   T   .   PASS    AF=0.2884   ES:SE:LP:AF:SS:ID   -0.00409066:0.0123399:0.130611:0.2884:65642:rs2494626
1   2407781 rs78504402  C   T   .   PASS    AF=0.06862  ES:SE:LP:AF:SS:ID   0.00566139:0.0213685:0.101793:0.06862:65642:rs78504402
1   2408471 rs115996655 G   A   .   PASS    AF=0.007814 ES:SE:LP:AF:SS:ID   -0.037422:0.0554724:0.301094:0.007814:65642:rs115996655
1   2408834 rs11588930  G   A   .   PASS    AF=0.101    ES:SE:LP:AF:SS:ID   0.0134586:0.018543:0.329793:0.101:65642:rs11588930
1   2409892 rs12727342  A   G   .   PASS    AF=0.6229   ES:SE:LP:AF:SS:ID   0.0200619:0.0110419:1.15969:0.6229:65642:rs12727342
1   2410789 rs11799501  C   T   .   PASS    AF=0.5834   ES:SE:LP:AF:SS:ID   0.0320413:0.0109856:2.45125:0.5834:65642:rs11799501
1   2412279 rs4648638   A   T   .   PASS    AF=0.388    ES:SE:LP:AF:SS:ID   -0.0243631:0.0110051:1.57118:0.388:65642:rs4648638
1   2412293 rs12731186  C   T   .   PASS    AF=0.1211   ES:SE:LP:AF:SS:ID   0.0168713:0.0157379:0.547123:0.1211:65642:rs12731186
1   2413166 rs115810747 A   G   .   PASS    AF=0.04094  ES:SE:LP:AF:SS:ID   0.0408929:0.0284886:0.820537:0.04094:65642:rs115810747
1   2413464 rs114424485 G   C   .   PASS    AF=0.008958 ES:SE:LP:AF:SS:ID   0.00992199:0.0545778:0.0676565:0.008958:65642:rs114424485