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-11/ieu-a-11.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-11/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 11:45:58 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-11/ieu-a-11.vcf.gz ...
Read summary statistics for 104069 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, 47724 SNPs remain.
After merging with regression SNP LD, 47724 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: 2.8657 (0.7862)
Lambda GC: 1.2584
Mean Chi^2: 1.4634
Intercept: 1.1397 (0.0384)
Ratio: 0.3015 (0.0828)
Analysis finished at Wed Feb  5 11:46:08 2020
Total time elapsed: 9.59s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7584,
    "inflation_factor": 1.4043,
    "mean_EFFECT": -0.0351,
    "n": 5409,
    "n_snps": 104069,
    "n_clumped_hits": 14,
    "n_p_sig": 465,
    "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": 2166,
    "n_miss_AF_reference": 721,
    "n_est": 5393.871,
    "ratio_se_n": 0.9986,
    "mean_diff": 0.0856,
    "ratio_diff": 2.5531,
    "sd_y_est1": 2.1857,
    "sd_y_est2": 2.1827,
    "r2_sum1": 0.9464,
    "r2_sum2": 0.1981,
    "r2_sum3": 0.1987,
    "r2_sum4": 0.1783,
    "ldsc_nsnp_merge_refpanel_ld": 47724,
    "ldsc_nsnp_merge_regression_ld": 47724,
    "ldsc_observed_scale_h2_beta": 2.8657,
    "ldsc_observed_scale_h2_se": 0.7862,
    "ldsc_intercept_beta": 1.1397,
    "ldsc_intercept_se": 0.0384,
    "ldsc_lambda_gc": 1.2584,
    "ldsc_mean_chisq": 1.4634,
    "ldsc_ratio": 0.3015
}

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 TRUE
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 104069 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 8.139436e+00 5.781963e+00 1.00000e+00 3.000000e+00 7.000000e+00 1.200000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.858037e+07 5.787212e+07 6.34110e+04 3.265643e+07 6.213066e+07 1.172815e+08 2.492107e+08 ▇▅▃▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.512490e-02 9.839166e-01 -2.85101e+01 -5.570200e-02 -1.310100e-03 5.497330e-02 1.702190e+01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.306632e-01 9.534398e-01 3.98436e-02 4.463740e-02 5.451580e-02 9.359860e-02 2.581000e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.375649e-01 3.019824e-01 0.00000e+00 1.615169e-01 4.241154e-01 6.928832e-01 9.999900e-01 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.375647e-01 3.019824e-01 0.00000e+00 1.615089e-01 4.241126e-01 6.928870e-01 9.999886e-01 ▇▅▅▅▅
numeric AF 2166 0.9791869 NA NA NA NA NA 3.568077e-01 3.021462e-01 1.34000e-04 8.604000e-02 2.865000e-01 5.858000e-01 9.998660e-01 ▇▃▃▂▂
numeric AF_reference 721 0.9930719 NA NA NA NA NA 3.235267e-01 2.469117e-01 1.99700e-04 1.198080e-01 2.569890e-01 4.872200e-01 9.992010e-01 ▇▅▃▂▁
numeric N 0 1.0000000 NA NA NA NA NA 5.409000e+03 0.000000e+00 5.40900e+03 5.409000e+03 5.409000e+03 5.409000e+03 5.409000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1118275 rs61733845 C T -0.1233060 0.0905262 0.1731650 0.1731654 0.059290 0.185703 5409
1 1120431 rs1320571 G A 0.0762884 0.0572258 0.1824652 0.1824951 0.161100 0.185304 5409
1 1135242 rs9729550 A C 0.1923320 0.0660160 0.0035740 0.0035750 0.875200 0.551917 5409
1 1140435 rs1815606 G T 0.2575370 0.0973482 0.0081559 0.0081564 0.943800 0.712061 5409
1 1163804 rs7515488 C T 0.1029490 0.0516031 0.0460416 0.0460412 0.197100 0.186901 5409
1 1165310 rs11260562 G A 0.0292938 0.1326200 0.8251810 0.8251818 0.024330 0.101837 5409
1 1173611 rs6697886 G A 0.0997558 0.0535264 0.0623677 0.0623674 0.177500 0.220647 5409
1 1186502 rs6603785 A T 0.1009180 0.0483175 0.0367418 0.0367399 0.226000 0.246206 5409
1 1194804 rs11804831 T C -0.8090590 0.3913100 0.0386768 0.0386809 0.998387 0.685903 5409
1 1218086 rs6603788 C T -0.0875708 0.0431856 0.0425843 0.0425829 0.634200 0.469449 5409
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50960682 rs140524 C T -0.0477988 0.0498388 0.3375289 0.3375245 0.22820 0.230232 5409
22 50966914 rs470119 T C 0.0219114 0.0470631 0.6415197 0.6415198 0.72920 0.554712 5409
22 50971752 rs131794 A C -0.1341300 0.0910773 0.1408209 0.1408306 0.95066 0.832668 5409
22 50988193 rs131779 A G -0.0248702 0.0439758 0.5716866 0.5717046 0.62410 0.580272 5409
22 50999182 rs140518 C T 0.0844444 0.1000570 0.3986943 0.3986901 0.95308 0.765575 5409
22 51078251 rs4040041 C T 0.0761860 0.0485616 0.1166931 0.1166823 0.74760 0.466653 5409
22 51094926 rs9616810 C T 0.0319468 0.0427614 0.4550027 0.4550066 0.46100 0.222444 5409
22 51105556 rs9616812 C T -0.1213240 0.0635004 0.0560519 0.0560557 0.13750 0.362819 5409
22 51109992 rs9628185 T C -0.1229160 0.0560570 0.0283505 0.0283292 0.18100 0.405351 5409
22 51156666 rs9628187 C T 0.0248134 0.1694060 0.8835489 0.8835480 0.01492 0.129992 5409

bcf preview

1   1118275 rs61733845  C   T   .   PASS    AF=0.05929  ES:SE:LP:AF:SS:ID   -0.123306:0.0905262:0.76154:0.05929:5409:rs61733845
1   1120431 rs1320571   G   A   .   PASS    AF=0.1611   ES:SE:LP:AF:SS:ID   0.0762884:0.0572258:0.73882:0.1611:5409:rs1320571
1   1135242 rs9729550   A   C   .   PASS    AF=0.8752   ES:SE:LP:AF:SS:ID   0.192332:0.066016:2.44685:0.8752:5409:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.9438   ES:SE:LP:AF:SS:ID   0.257537:0.0973482:2.08853:0.9438:5409:rs1815606
1   1163804 rs7515488   C   T   .   PASS    AF=0.1971   ES:SE:LP:AF:SS:ID   0.102949:0.0516031:1.33685:0.1971:5409:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.02433  ES:SE:LP:AF:SS:ID   0.0292938:0.13262:0.0834508:0.02433:5409:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.1775   ES:SE:LP:AF:SS:ID   0.0997558:0.0535264:1.20504:0.1775:5409:rs6697886
1   1186502 rs6603785   A   T   .   PASS    AF=0.226    ES:SE:LP:AF:SS:ID   0.100918:0.0483175:1.43484:0.226:5409:rs6603785
1   1194804 rs11804831  T   C   .   PASS    AF=0.998387 ES:SE:LP:AF:SS:ID   -0.809059:0.39131:1.41255:0.998387:5409:rs11804831
1   1218086 rs6603788   C   T   .   PASS    AF=0.6342   ES:SE:LP:AF:SS:ID   -0.0875708:0.0431856:1.37075:0.6342:5409:rs6603788
1   1227897 rs3737721   A   G   .   PASS    AF=0.5565   ES:SE:LP:AF:SS:ID   -0.068276:0.0421998:0.975999:0.5565:5409:rs3737721
1   1231656 rs1749951   G   A   .   PASS    AF=0.1202   ES:SE:LP:AF:SS:ID   0.0825033:0.0644712:0.697585:0.1202:5409:rs1749951
1   1233941 rs1739855   T   C   .   PASS    AF=0.6959   ES:SE:LP:AF:SS:ID   -0.0707594:0.0461123:0.903559:0.6959:5409:rs1739855
1   1241529 rs1536168   A   G   .   PASS    AF=0.8227   ES:SE:LP:AF:SS:ID   0.00598627:0.0549711:0.0393946:0.8227:5409:rs1536168
1   1242468 rs2274264   G   A   .   PASS    AF=0.5043   ES:SE:LP:AF:SS:ID   -0.0620229:0.0419662:0.855638:0.5043:5409:rs2274264
1   1247494 rs12103 T   C   .   PASS    AF=0.008604 ES:SE:LP:AF:SS:ID   -0.542546:0.26171:1.41834:0.008604:5409:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.008067 ES:SE:LP:AF:SS:ID   -0.46957:0.263526:1.12629:0.008067:5409:rs12142199
1   1254255 rs62623580  G   A   .   PASS    AF=0.06319  ES:SE:LP:AF:SS:ID   -0.165312:0.0893182:1.1925:0.06319:5409:rs62623580
1   1335790 rs1240708   A   G   .   PASS    AF=0.991799 ES:SE:LP:AF:SS:ID   0.47152:0.262094:1.14263:0.991799:5409:rs1240708
1   1493727 rs880051    G   A   .   PASS    AF=0.7324   ES:SE:LP:AF:SS:ID   0.129699:0.0492973:2.06963:0.7324:5409:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.3606   ES:SE:LP:AF:SS:ID   0.154517:0.0420523:3.62279:0.3606:5409:rs2296716
1   1611995 rs4074196   A   G   .   PASS    AF=0.6309   ES:SE:LP:AF:SS:ID   -0.0440107:0.0437982:0.501565:0.6309:5409:rs4074196
1   1706160 rs7531583   A   G   .   PASS    AF=0.7006   ES:SE:LP:AF:SS:ID   0.00209556:0.0450489:0.0164197:0.7006:5409:rs7531583
1   1721479 rs2272908   C   T   .   PASS    AF=0.5008   ES:SE:LP:AF:SS:ID   -0.0364948:0.0418011:0.417194:0.5008:5409:rs2272908
1   1723031 rs9660180   G   A   .   PASS    AF=0.5003   ES:SE:LP:AF:SS:ID   -0.0354122:0.0417782:0.401571:0.5003:5409:rs9660180
1   1781220 rs6681938   T   C   .   PASS    AF=0.167    ES:SE:LP:AF:SS:ID   -0.077341:0.0581292:0.736546:0.167:5409:rs6681938
1   1838516 rs2377037   C   A   .   PASS    AF=0.2084   ES:SE:LP:AF:SS:ID   0.0133106:0.050622:0.100949:0.2084:5409:rs2377037
1   1840038 rs2474461   T   C   .   PASS    AF=0.8669   ES:SE:LP:AF:SS:ID   -0.0204077:0.061013:0.131932:0.8669:5409:rs2474461
1   1853288 rs1884454   G   T   .   PASS    AF=0.2116   ES:SE:LP:AF:SS:ID   0.0244949:0.0506298:0.201686:0.2116:5409:rs1884454
1   1855319 rs2295362   C   T   .   PASS    AF=0.1342   ES:SE:LP:AF:SS:ID   -0.00187481:0.0616943:0.0106583:0.1342:5409:rs2295362
1   1871337 rs16824543  G   A   .   PASS    AF=0.1354   ES:SE:LP:AF:SS:ID   -0.00708781:0.0615224:0.0417802:0.1354:5409:rs16824543
1   1873625 rs12758705  G   A   .   PASS    AF=0.2123   ES:SE:LP:AF:SS:ID   0.0198142:0.0506349:0.157667:0.2123:5409:rs12758705
1   1881070 rs4648596   G   A   .   PASS    AF=0.08483  ES:SE:LP:AF:SS:ID   -0.147342:0.0775674:1.24044:0.08483:5409:rs4648596
1   1888193 rs3820011   C   A   .   PASS    AF=0.299    ES:SE:LP:AF:SS:ID   -0.00607677:0.0458252:0.0484172:0.299:5409:rs3820011
1   2024064 rs2459994   C   T   .   PASS    AF=0.556    ES:SE:LP:AF:SS:ID   0.00886829:0.0431731:0.0771443:0.556:5409:rs2459994
1   2146966 rs7512482   T   C   .   PASS    AF=0.1026   ES:SE:LP:AF:SS:ID   -0.0407313:0.0707469:0.248109:0.1026:5409:rs7512482
1   2202774 rs6673129   C   T   .   PASS    AF=0.014    ES:SE:LP:AF:SS:ID   -0.102361:0.179125:0.245885:0.014:5409:rs6673129
1   2229478 rs12562937  C   T   .   PASS    AF=0.4442   ES:SE:LP:AF:SS:ID   -0.0358642:0.0435219:0.387202:0.4442:5409:rs12562937
1   2283896 rs2840528   A   G   .   PASS    AF=0.4063   ES:SE:LP:AF:SS:ID   0.042928:0.0433734:0.491663:0.4063:5409:rs2840528
1   2404256 rs2494626   C   T   .   PASS    AF=0.2058   ES:SE:LP:AF:SS:ID   0.0281118:0.0526687:0.226568:0.2058:5409:rs2494626
1   2407781 rs78504402  C   T   .   PASS    AF=0.000269 ES:SE:LP:AF:SS:ID   -1.99439:2.40658:0.390133:0.000269:5409:rs78504402
1   2408471 rs115996655 G   A   .   PASS    AF=0.02097  ES:SE:LP:AF:SS:ID   0.0891524:0.140989:0.278049:0.02097:5409:rs115996655
1   2409892 rs12727342  A   G   .   PASS    AF=0.864    ES:SE:LP:AF:SS:ID   0.0566026:0.0621605:0.440684:0.864:5409:rs12727342
1   2410789 rs11799501  C   T   .   PASS    AF=0.8453   ES:SE:LP:AF:SS:ID   -0.00471403:0.0577544:0.029213:0.8453:5409:rs11799501
1   2412279 rs4648638   A   T   .   PASS    AF=0.1592   ES:SE:LP:AF:SS:ID   0.00883468:0.056919:0.0571733:0.1592:5409:rs4648638
1   2412293 rs12731186  C   T   .   PASS    AF=0.1108   ES:SE:LP:AF:SS:ID   -0.0299019:0.0677828:0.181043:0.1108:5409:rs12731186
1   2413464 rs114424485 G   C   .   PASS    AF=0.01143  ES:SE:LP:AF:SS:ID   0.261235:0.17829:0.84508:0.01143:5409:rs114424485
1   2413634 rs942817    G   C   .   PASS    AF=0.8471   ES:SE:LP:AF:SS:ID   0.00911218:0.0581495:0.0577538:0.8471:5409:rs942817
1   2414928 rs4995304   G   A   .   PASS    AF=0.8415   ES:SE:LP:AF:SS:ID   0.000869099:0.057094:0.0053068:0.8415:5409:rs4995304
1   2416357 rs4648639   G   A   .   PASS    AF=0.8415   ES:SE:LP:AF:SS:ID   0.00179019:0.0571227:0.0109958:0.8415:5409:rs4648639