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-969/ieu-a-969.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-969/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 11:34:05 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-969/ieu-a-969.vcf.gz ...
Read summary statistics for 104167 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, 47712 SNPs remain.
After merging with regression SNP LD, 47712 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: 1.5915 (0.5628)
Lambda GC: 1.2887
Mean Chi^2: 1.2985
Intercept: 1.1234 (0.0331)
Ratio: 0.4134 (0.1108)
Analysis finished at Wed Feb  5 11:34:15 2020
Total time elapsed: 9.83s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7587,
    "inflation_factor": 1.5186,
    "mean_EFFECT": -0.0233,
    "n": 4853,
    "n_snps": 104167,
    "n_clumped_hits": 10,
    "n_p_sig": 561,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 6058,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 2144,
    "n_miss_AF_reference": 724,
    "n_est": 4815.2115,
    "ratio_se_n": 0.9961,
    "mean_diff": 0.0921,
    "ratio_diff": 2.3211,
    "sd_y_est1": 2.3658,
    "sd_y_est2": 2.3566,
    "r2_sum1": 0.5624,
    "r2_sum2": 0.1005,
    "r2_sum3": 0.1013,
    "r2_sum4": 0.1015,
    "ldsc_nsnp_merge_refpanel_ld": 47712,
    "ldsc_nsnp_merge_regression_ld": 47712,
    "ldsc_observed_scale_h2_beta": 1.5915,
    "ldsc_observed_scale_h2_se": 0.5628,
    "ldsc_intercept_beta": 1.1234,
    "ldsc_intercept_se": 0.0331,
    "ldsc_lambda_gc": 1.2887,
    "ldsc_mean_chisq": 1.2985,
    "ldsc_ratio": 0.4134
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
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 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 104167 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 8.157027e+00 5.787488e+00 1.00000e+00 3.000000e+00 6.000000e+00 1.200000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.863407e+07 5.782478e+07 6.34110e+04 3.268696e+07 6.214506e+07 1.173961e+08 2.492107e+08 ▇▅▃▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.332200e-02 1.784252e+01 -1.87031e+03 -6.258050e-02 -1.939000e-04 6.351040e-02 3.198690e+03 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.023657e+00 1.581684e+01 4.47959e-02 5.100540e-02 6.232960e-02 1.062965e-01 1.929550e+03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.342843e-01 2.996177e-01 0.00000e+00 1.658365e-01 4.058682e-01 6.873422e-01 9.999960e-01 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.343035e-01 2.996027e-01 0.00000e+00 1.658720e-01 4.058892e-01 6.873434e-01 9.999974e-01 ▇▆▅▅▅
numeric AF 2144 0.9794177 NA NA NA NA NA 3.566348e-01 3.021991e-01 1.34000e-04 8.578000e-02 2.861000e-01 5.856000e-01 9.998660e-01 ▇▃▃▂▂
numeric AF_reference 724 0.9930496 NA NA NA NA NA 3.238299e-01 2.474769e-01 1.99700e-04 1.198080e-01 2.571880e-01 4.880190e-01 1.000000e+00 ▇▅▃▂▁
numeric N 0 1.0000000 NA NA NA NA NA 4.853000e+03 0.000000e+00 4.85300e+03 4.853000e+03 4.853000e+03 4.853000e+03 4.853000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1118275 rs61733845 C T -0.2076750 0.1067930 0.0517655 0.0518171 0.059290 0.185703 4853
1 1120431 rs1320571 G A 0.0071298 0.0667148 0.9148911 0.9148921 0.161100 0.185304 4853
1 1135242 rs9729550 A C 0.1015400 0.0758333 0.1805061 0.1805741 0.875200 0.551917 4853
1 1140435 rs1815606 G T 0.0906663 0.1056480 0.3907689 0.3907863 0.943800 0.712061 4853
1 1163804 rs7515488 C T 0.0358865 0.0587221 0.5411093 0.5411173 0.197100 0.186901 4853
1 1165310 rs11260562 G A -0.0605261 0.1538720 0.6940616 0.6940584 0.024330 0.101837 4853
1 1173611 rs6697886 G A 0.0481684 0.0608527 0.4286018 0.4286188 0.177500 0.220647 4853
1 1186502 rs6603785 A T 0.0416181 0.0549720 0.4489883 0.4490030 0.226000 0.246206 4853
1 1194804 rs11804831 T C -0.7722910 0.4109880 0.0601631 0.0602297 0.998387 0.685903 4853
1 1218086 rs6603788 C T 0.0220566 0.0492276 0.6541103 0.6541146 0.634200 0.469449 4853
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50960682 rs140524 C T 0.1256130 0.0542198 0.0204748 0.0205181 0.22820 0.230232 4853
22 50966914 rs470119 T C -0.0932746 0.0519743 0.0726541 0.0727128 0.72920 0.554712 4853
22 50971752 rs131794 A C 0.0244393 0.1078310 0.8206969 0.8207002 0.95066 0.832668 4853
22 50988193 rs131779 A G -0.1115700 0.0475987 0.0190371 0.0190796 0.62410 0.580272 4853
22 50999182 rs140518 C T 0.2359830 0.1200330 0.0492550 0.0493004 0.95308 0.765575 4853
22 51078251 rs4040041 C T 0.0854419 0.0552508 0.1219501 0.1219990 0.74760 0.466653 4853
22 51094926 rs9616810 C T -0.0198366 0.0490924 0.6861657 0.6861637 0.46100 0.222444 4853
22 51105556 rs9616812 C T -0.0935125 0.0726904 0.1982362 0.1982864 0.13750 0.362819 4853
22 51109992 rs9628185 T C -0.0976082 0.0637377 0.1256501 0.1256695 0.18100 0.405351 4853
22 51156666 rs9628187 C T 0.0255535 0.1925110 0.8944000 0.8944007 0.01492 0.129992 4853

bcf preview

1   1118275 rs61733845  C   T   .   PASS    AF=0.05929  ES:SE:LP:AF:SS:ID   -0.207675:0.106793:1.28596:0.05929:4853:rs61733845
1   1120431 rs1320571   G   A   .   PASS    AF=0.1611   ES:SE:LP:AF:SS:ID   0.00712981:0.0667148:0.0386306:0.1611:4853:rs1320571
1   1135242 rs9729550   A   C   .   PASS    AF=0.8752   ES:SE:LP:AF:SS:ID   0.10154:0.0758333:0.743508:0.8752:4853:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.9438   ES:SE:LP:AF:SS:ID   0.0906663:0.105648:0.40808:0.9438:4853:rs1815606
1   1163804 rs7515488   C   T   .   PASS    AF=0.1971   ES:SE:LP:AF:SS:ID   0.0358865:0.0587221:0.266715:0.1971:4853:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.02433  ES:SE:LP:AF:SS:ID   -0.0605261:0.153872:0.158602:0.02433:4853:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.1775   ES:SE:LP:AF:SS:ID   0.0481684:0.0608527:0.367946:0.1775:4853:rs6697886
1   1186502 rs6603785   A   T   .   PASS    AF=0.226    ES:SE:LP:AF:SS:ID   0.0416181:0.054972:0.347765:0.226:4853:rs6603785
1   1194804 rs11804831  T   C   .   PASS    AF=0.998387 ES:SE:LP:AF:SS:ID   -0.772291:0.410988:1.22067:0.998387:4853:rs11804831
1   1218086 rs6603788   C   T   .   PASS    AF=0.6342   ES:SE:LP:AF:SS:ID   0.0220566:0.0492276:0.184349:0.6342:4853:rs6603788
1   1227897 rs3737721   A   G   .   PASS    AF=0.5565   ES:SE:LP:AF:SS:ID   0.00586954:0.0487515:0.0437509:0.5565:4853:rs3737721
1   1231656 rs1749951   G   A   .   PASS    AF=0.1202   ES:SE:LP:AF:SS:ID   -0.0611965:0.0768879:0.37051:0.1202:4853:rs1749951
1   1233941 rs1739855   T   C   .   PASS    AF=0.6959   ES:SE:LP:AF:SS:ID   -0.0287987:0.0537483:0.227615:0.6959:4853:rs1739855
1   1241529 rs1536168   A   G   .   PASS    AF=0.8227   ES:SE:LP:AF:SS:ID   0.103076:0.063863:0.972818:0.8227:4853:rs1536168
1   1242468 rs2274264   G   A   .   PASS    AF=0.5043   ES:SE:LP:AF:SS:ID   0.0351352:0.0483236:0.330533:0.5043:4853:rs2274264
1   1247494 rs12103 T   C   .   PASS    AF=0.008604 ES:SE:LP:AF:SS:ID   -0.710314:0.31534:1.61526:0.008604:4853:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.008067 ES:SE:LP:AF:SS:ID   -0.645999:0.317599:1.37772:0.008067:4853:rs12142199
1   1254255 rs62623580  G   A   .   PASS    AF=0.06319  ES:SE:LP:AF:SS:ID   -0.0866067:0.0981166:0.423211:0.06319:4853:rs62623580
1   1335790 rs1240708   A   G   .   PASS    AF=0.991799 ES:SE:LP:AF:SS:ID   0.636978:0.315035:1.36517:0.991799:4853:rs1240708
1   1493727 rs880051    G   A   .   PASS    AF=0.7324   ES:SE:LP:AF:SS:ID   0.0754173:0.0560135:0.749066:0.7324:4853:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.3606   ES:SE:LP:AF:SS:ID   0.109827:0.047464:1.68549:0.3606:4853:rs2296716
1   1611995 rs4074196   A   G   .   PASS    AF=0.6309   ES:SE:LP:AF:SS:ID   -0.0879633:0.0496473:1.11662:0.6309:4853:rs4074196
1   1706160 rs7531583   A   G   .   PASS    AF=0.7006   ES:SE:LP:AF:SS:ID   -0.0719158:0.0510816:0.798251:0.7006:4853:rs7531583
1   1721479 rs2272908   C   T   .   PASS    AF=0.5008   ES:SE:LP:AF:SS:ID   -0.0665416:0.0481244:0.778023:0.5008:4853:rs2272908
1   1723031 rs9660180   G   A   .   PASS    AF=0.5003   ES:SE:LP:AF:SS:ID   -0.0661935:0.0481458:0.771764:0.5003:4853:rs9660180
1   1781220 rs6681938   T   C   .   PASS    AF=0.167    ES:SE:LP:AF:SS:ID   -0.0265575:0.0660779:0.162568:0.167:4853:rs6681938
1   1838516 rs2377037   C   A   .   PASS    AF=0.2084   ES:SE:LP:AF:SS:ID   -0.00958394:0.0583577:0.0607044:0.2084:4853:rs2377037
1   1840038 rs2474461   T   C   .   PASS    AF=0.8669   ES:SE:LP:AF:SS:ID   -0.0660987:0.0689144:0.471761:0.8669:4853:rs2474461
1   1853288 rs1884454   G   T   .   PASS    AF=0.2116   ES:SE:LP:AF:SS:ID   0.0119762:0.0579062:0.0777158:0.2116:4853:rs1884454
1   1855319 rs2295362   C   T   .   PASS    AF=0.1342   ES:SE:LP:AF:SS:ID   0.0260813:0.0704195:0.148062:0.1342:4853:rs2295362
1   1871337 rs16824543  G   A   .   PASS    AF=0.1354   ES:SE:LP:AF:SS:ID   0.0165922:0.0703023:0.089682:0.1354:4853:rs16824543
1   1873625 rs12758705  G   A   .   PASS    AF=0.2123   ES:SE:LP:AF:SS:ID   0.0131508:0.0578185:0.0861475:0.2123:4853:rs12758705
1   1881070 rs4648596   G   A   .   PASS    AF=0.08483  ES:SE:LP:AF:SS:ID   -0.00195654:0.0843722:0.00811014:0.08483:4853:rs4648596
1   1888193 rs3820011   C   A   .   PASS    AF=0.299    ES:SE:LP:AF:SS:ID   0.0221263:0.0526822:0.171029:0.299:4853:rs3820011
1   2024064 rs2459994   C   T   .   PASS    AF=0.556    ES:SE:LP:AF:SS:ID   0.0583638:0.0503341:0.608611:0.556:4853:rs2459994
1   2146966 rs7512482   T   C   .   PASS    AF=0.1026   ES:SE:LP:AF:SS:ID   0.0457539:0.0789288:0.250172:0.1026:4853:rs7512482
1   2202774 rs6673129   C   T   .   PASS    AF=0.014    ES:SE:LP:AF:SS:ID   0.0260228:0.194994:0.0487431:0.014:4853:rs6673129
1   2229478 rs12562937  C   T   .   PASS    AF=0.4442   ES:SE:LP:AF:SS:ID   0.0274054:0.0499171:0.234336:0.4442:4853:rs12562937
1   2283896 rs2840528   A   G   .   PASS    AF=0.4063   ES:SE:LP:AF:SS:ID   -0.105067:0.0502414:1.43817:0.4063:4853:rs2840528
1   2404256 rs2494626   C   T   .   PASS    AF=0.2058   ES:SE:LP:AF:SS:ID   0.0203819:0.0603089:0.133475:0.2058:4853:rs2494626
1   2407781 rs78504402  C   T   .   PASS    AF=0.000269 ES:SE:LP:AF:SS:ID   0.51566:1.17489:0.179976:0.000269:4853:rs78504402
1   2408471 rs115996655 G   A   .   PASS    AF=0.02097  ES:SE:LP:AF:SS:ID   0.120153:0.155554:0.356694:0.02097:4853:rs115996655
1   2408834 rs11588930  G   A   .   PASS    .   ES:SE:LP:SS:ID  3.30642:2.33173:0.806525:4853:rs11588930
1   2409892 rs12727342  A   G   .   PASS    AF=0.864    ES:SE:LP:AF:SS:ID   -0.0596179:0.0690806:0.411037:0.864:4853:rs12727342
1   2410789 rs11799501  C   T   .   PASS    AF=0.8453   ES:SE:LP:AF:SS:ID   -0.0801095:0.0643508:0.671337:0.8453:4853:rs11799501
1   2412279 rs4648638   A   T   .   PASS    AF=0.1592   ES:SE:LP:AF:SS:ID   0.0863485:0.063414:0.761282:0.1592:4853:rs4648638
1   2412293 rs12731186  C   T   .   PASS    AF=0.1108   ES:SE:LP:AF:SS:ID   0.0330642:0.0766768:0.176316:0.1108:4853:rs12731186
1   2413464 rs114424485 G   C   .   PASS    AF=0.01143  ES:SE:LP:AF:SS:ID   0.259908:0.197699:0.724525:0.01143:4853:rs114424485
1   2413634 rs942817    G   C   .   PASS    AF=0.8471   ES:SE:LP:AF:SS:ID   -0.0799583:0.064653:0.665231:0.8471:4853:rs942817
1   2414928 rs4995304   G   A   .   PASS    AF=0.8415   ES:SE:LP:AF:SS:ID   -0.0669469:0.0638043:0.531595:0.8415:4853:rs4995304