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-10/ieu-a-10.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-10/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 11:44:26 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-10/ieu-a-10.vcf.gz ...
Read summary statistics for 13871 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, 13612 SNPs remain.
After merging with regression SNP LD, 13612 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: 10.0915 (1.6126)
Lambda GC: 7.6358
Mean Chi^2: 11.971
Intercept: 3.2089 (0.3645)
Ratio: 0.2013 (0.0332)
Analysis finished at Wed Feb  5 11:44:34 2020
Total time elapsed: 7.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8771,
    "inflation_factor": 23.837,
    "mean_EFFECT": 0.0037,
    "n": 33000,
    "n_snps": 13871,
    "n_clumped_hits": 103,
    "n_p_sig": 2860,
    "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": 90,
    "n_est": 33209.6952,
    "ratio_se_n": 1.0032,
    "mean_diff": -0.0018,
    "ratio_diff": 11.7477,
    "sd_y_est1": 2.1178,
    "sd_y_est2": 2.1245,
    "r2_sum1": 0.7904,
    "r2_sum2": 0.1762,
    "r2_sum3": 0.1751,
    "r2_sum4": 0.1675,
    "ldsc_nsnp_merge_refpanel_ld": 13612,
    "ldsc_nsnp_merge_regression_ld": 13612,
    "ldsc_observed_scale_h2_beta": 10.0915,
    "ldsc_observed_scale_h2_se": 1.6126,
    "ldsc_intercept_beta": 3.2089,
    "ldsc_intercept_se": 0.3645,
    "ldsc_lambda_gc": 7.6358,
    "ldsc_mean_chisq": 11.971,
    "ldsc_ratio": 0.2013
}
 

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 21 0 13871 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 8.739601e+00 6.132504e+00 1.00000e+00 3.000000e+00 7.000000e+00 1.300000e+01 2.200000e+01 ▇▃▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.907289e+07 5.562832e+07 1.91843e+05 3.796476e+07 6.383187e+07 1.186147e+08 2.477826e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.693100e-03 6.983370e-02 -8.63698e-01 -3.536710e-02 1.000500e-03 4.114190e-02 5.658820e-01 ▁▁▆▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.109830e-02 1.222560e-02 1.62898e-02 1.698060e-02 1.840000e-02 2.165480e-02 6.547000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.605430e-02 1.449197e-01 0.00000e+00 4.000000e-07 9.910000e-04 3.291020e-02 9.998000e-01 ▇▁▁▁▁
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 2.345702e-01 3.014165e-01 0.00000e+00 2.527000e-04 6.494150e-02 4.227683e-01 1.000000e+00 ▇▂▁▁▁
numeric AF 0 1.0000000 NA NA NA NA NA 4.001287e-01 2.352702e-01 2.62000e-04 2.070000e-01 3.590000e-01 5.805000e-01 9.910000e-01 ▆▇▆▅▂
numeric AF_reference 90 0.9935116 NA NA NA NA NA 3.924793e-01 2.304843e-01 4.59260e-03 1.976840e-01 3.590260e-01 5.634980e-01 9.938100e-01 ▇▇▆▅▂
numeric N 0 1.0000000 NA NA NA NA NA 3.300000e+04 0.000000e+00 3.30000e+04 3.300000e+04 3.300000e+04 3.300000e+04 3.300000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1135242 rs9729550 A C 0.0411419 0.0188099 0.0003160 0.0287245 0.2620 0.5519170 33000
1 1140435 rs1815606 G T 0.0353671 0.0177280 0.0002186 0.0460445 0.3100 0.7120610 33000
1 1152631 rs11721 C A 0.0852598 0.0237003 0.0000052 0.0003214 0.0781 0.1585460 33000
1 1163804 rs7515488 C T 0.0843411 0.0229304 0.0000004 0.0002349 0.1470 0.1869010 33000
1 1165310 rs11260562 G A 0.0610951 0.0352196 0.0004346 0.0827957 0.0546 0.1018370 33000
1 1173611 rs6697886 G A 0.0852598 0.0237003 0.0000016 0.0003214 0.1310 0.2206470 33000
1 1174282 rs4970364 T C 0.0741794 0.0212300 0.0000003 0.0004757 0.2400 0.6581470 33000
1 1192515 rs7524470 A G 0.0324672 0.0310406 0.0254900 0.2955799 0.0390 0.0834665 33000
1 1193723 rs12072310 A C 0.0324672 0.0310406 0.0099850 0.2955799 0.0510 0.1743210 33000
1 1194804 rs11804831 T C 0.0741794 0.0212300 0.0000006 0.0004757 0.1830 0.6859030 33000
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50312225 rs9616380 T C 0.0324672 0.0210098 0.0015270 0.1222650 0.197 0.2472040 33000
22 50313438 rs9616388 T C 0.0324672 0.0210098 0.0017920 0.1222650 0.196 0.2498000 33000
22 50314809 rs9616393 C T 0.0685928 0.0267604 0.0001076 0.0103706 0.117 0.1126200 33000
22 50317049 rs7410318 T C 0.0324672 0.0210098 0.0022690 0.1222650 0.199 0.2961260 33000
22 50317330 rs7410537 G A 0.0324672 0.0210109 0.0023810 0.1222846 0.195 0.2959270 33000
22 50318946 rs9616217 C T 0.0324672 0.0210109 0.0027780 0.1222846 0.202 0.2959270 33000
22 50319170 rs11545763 A G 0.0685928 0.0267600 0.0000798 0.0103695 0.108 0.0674920 33000
22 50321623 rs7287579 C T 0.0324672 0.0210109 0.0043390 0.1222846 0.219 0.3438500 33000
22 50333415 rs4073387 G A 0.0685928 0.0267604 0.0000842 0.0103706 0.141 0.0898562 33000
22 51171693 rs756638 G A 0.0049875 0.0202795 0.1626002 0.8057287 0.277 0.3049120 33000

bcf preview

1   1135242 rs9729550   A   C   .   PASS    AF=0.262    ES:SE:LP:AF:SS:ID   0.0411419:0.0188099:3.50031:0.262:33000:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.31 ES:SE:LP:AF:SS:ID   0.0353671:0.017728:3.66035:0.31:33000:rs1815606
1   1152631 rs11721 C   A   .   PASS    AF=0.0781   ES:SE:LP:AF:SS:ID   0.0852598:0.0237003:5.28693:0.0781:33000:rs11721
1   1163804 rs7515488   C   T   .   PASS    AF=0.147    ES:SE:LP:AF:SS:ID   0.0843411:0.0229304:6.44129:0.147:33000:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.0546   ES:SE:LP:AF:SS:ID   0.0610951:0.0352196:3.36191:0.0546:33000:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.131    ES:SE:LP:AF:SS:ID   0.0852598:0.0237003:5.8041:0.131:33000:rs6697886
1   1174282 rs4970364   T   C   .   PASS    AF=0.24 ES:SE:LP:AF:SS:ID   0.0741794:0.02123:6.55752:0.24:33000:rs4970364
1   1192515 rs7524470   A   G   .   PASS    AF=0.039    ES:SE:LP:AF:SS:ID   0.0324672:0.0310406:1.59363:0.039:33000:rs7524470
1   1193723 rs12072310  A   C   .   PASS    AF=0.051    ES:SE:LP:AF:SS:ID   0.0324672:0.0310406:2.00065:0.051:33000:rs12072310
1   1194804 rs11804831  T   C   .   PASS    AF=0.183    ES:SE:LP:AF:SS:ID   0.0741794:0.02123:6.23121:0.183:33000:rs11804831
1   1201640 rs11260570  T   C   .   PASS    AF=0.039    ES:SE:LP:AF:SS:ID   0.0324672:0.0310406:1.61852:0.039:33000:rs11260570
1   1206343 rs6667923   C   A   .   PASS    AF=0.0354   ES:SE:LP:AF:SS:ID   0.0324672:0.0310408:1.58137:0.0354:33000:rs6667923
1   1210471 rs11260577  T   C   .   PASS    AF=0.078    ES:SE:LP:AF:SS:ID   0.0324672:0.0310406:1.88107:0.078:33000:rs11260577
1   1218086 rs6603788   C   T   .   PASS    AF=0.0732   ES:SE:LP:AF:SS:ID   0.0324672:0.0310408:1.89722:0.0732:33000:rs6603788
1   1232319 rs604618    G   A   .   PASS    AF=0.0711   ES:SE:LP:AF:SS:ID   0.0440169:0.0316288:2.46168:0.0711:33000:rs604618
1   1233941 rs1739855   T   C   .   PASS    AF=0.072    ES:SE:LP:AF:SS:ID   0.0440169:0.0316299:2.55253:0.072:33000:rs1739855
1   1237036 rs2477782   T   C   .   PASS    AF=0.074    ES:SE:LP:AF:SS:ID   0.0440169:0.0316299:2.59125:0.074:33000:rs2477782
1   1239339 rs11260584  T   G   .   PASS    AF=0.9342   ES:SE:LP:AF:SS:ID   -0.0440169:0.0316288:2.55862:0.9342:33000:rs11260584
1   1247494 rs12103 T   C   .   PASS    AF=0.818    ES:SE:LP:AF:SS:ID   -0.0843411:0.0211594:7.15727:0.818:33000:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.811    ES:SE:LP:AF:SS:ID   -0.0620354:0.0206799:5.19132:0.811:33000:rs12142199
1   1254136 rs4970432   G   A   .   PASS    AF=0.931    ES:SE:LP:AF:SS:ID   -0.0440169:0.0316299:2.46878:0.931:33000:rs4970432
1   1257593 rs1810745   A   G   .   PASS    AF=0.9469   ES:SE:LP:AF:SS:ID   -0.0440169:0.0316288:1.6751:0.9469:33000:rs1810745
1   1258246 rs3845293   A   C   .   PASS    AF=0.9345   ES:SE:LP:AF:SS:ID   -0.0440169:0.0316288:2.44117:0.9345:33000:rs3845293
1   1287127 rs307380    G   A   .   PASS    AF=0.933    ES:SE:LP:AF:SS:ID   -0.0440169:0.0316299:2.38796:0.933:33000:rs307380
1   1295323 rs34389364  G   A   .   PASS    AF=0.929    ES:SE:LP:AF:SS:ID   -0.0440169:0.0316299:2.37049:0.929:33000:rs34389364
1   1295403 rs34876581  T   C   .   PASS    AF=0.9326   ES:SE:LP:AF:SS:ID   -0.0440169:0.0316288:2.37161:0.9326:33000:rs34876581
1   1297422 rs2765021   C   T   .   PASS    AF=0.932    ES:SE:LP:AF:SS:ID   -0.0440169:0.0316299:2.36151:0.932:33000:rs2765021
1   1314015 rs2649588   C   T   .   PASS    AF=0.927    ES:SE:LP:AF:SS:ID   -0.0440169:0.0316299:2.28904:0.927:33000:rs2649588
1   1335790 rs1240708   A   G   .   PASS    AF=0.168    ES:SE:LP:AF:SS:ID   0.0723207:0.0216802:5.79697:0.168:33000:rs1240708
1   1365570 rs1695824   A   C   .   PASS    AF=0.218    ES:SE:LP:AF:SS:ID   0.0723207:0.0216802:5.32157:0.218:33000:rs1695824
1   1366830 rs873927    A   G   .   PASS    AF=0.218    ES:SE:LP:AF:SS:ID   0.0723207:0.0216802:5.32157:0.218:33000:rs873927
1   1665613 rs4648764   A   G   .   PASS    AF=0.457    ES:SE:LP:AF:SS:ID   0.0236781:0.01648:2.31336:0.457:33000:rs4648764
1   1684472 rs7407  C   T   .   PASS    AF=0.507    ES:SE:LP:AF:SS:ID   -0.0236781:0.01648:2.39287:0.507:33000:rs7407
1   1687625 rs34306661  T   C   .   PASS    AF=0.436    ES:SE:LP:AF:SS:ID   0.0236781:0.01648:2.52014:0.436:33000:rs34306661
1   1689164 rs2235536   C   T   .   PASS    AF=0.424    ES:SE:LP:AF:SS:ID   0.0236781:0.0164812:2.49812:0.424:33000:rs2235536
1   1689762 rs2235537   T   C   .   PASS    AF=0.439    ES:SE:LP:AF:SS:ID   0.0236781:0.01648:2.54046:0.439:33000:rs2235537
1   1691050 rs35672141  C   T   .   PASS    AF=0.487    ES:SE:LP:AF:SS:ID   -0.0236781:0.01648:2.4593:0.487:33000:rs35672141
1   1692321 rs1107910   T   C   .   PASS    AF=0.448    ES:SE:LP:AF:SS:ID   0.0236781:0.01648:2.58788:0.448:33000:rs1107910
1   1707740 rs12041925  T   G   .   PASS    AF=0.262    ES:SE:LP:AF:SS:ID   0.0188218:0.0184796:1.82102:0.262:33000:rs12041925
1   1708801 rs12044597  A   G   .   PASS    AF=0.497    ES:SE:LP:AF:SS:ID   -0.0236781:0.0164812:2.74642:0.497:33000:rs12044597
1   1712230 rs10907194  C   T   .   PASS    AF=0.261    ES:SE:LP:AF:SS:ID   0.0188218:0.0184812:1.77806:0.261:33000:rs10907194
1   1713869 rs7534617   T   G   .   PASS    AF=0.263    ES:SE:LP:AF:SS:ID   0.0188218:0.0184796:1.78861:0.263:33000:rs7534617
1   1715011 rs742359    C   A   .   PASS    AF=0.259    ES:SE:LP:AF:SS:ID   0.0188218:0.0184812:1.77806:0.259:33000:rs742359
1   1721479 rs2272908   C   T   .   PASS    AF=0.498    ES:SE:LP:AF:SS:ID   -0.0236781:0.01648:2.7948:0.498:33000:rs2272908
1   1722932 rs3737628   C   T   .   PASS    AF=0.496    ES:SE:LP:AF:SS:ID   -0.0258308:0.0164797:2.94424:0.496:33000:rs3737628
1   1723031 rs9660180   G   A   .   PASS    AF=0.494    ES:SE:LP:AF:SS:ID   -0.0258308:0.0164797:2.90728:0.494:33000:rs9660180
1   1748734 rs2180311   T   C   .   PASS    AF=0.498    ES:SE:LP:AF:SS:ID   -0.0236781:0.0164812:2.77006:0.498:33000:rs2180311
1   1759054 rs10907187  G   A   .   PASS    AF=0.261    ES:SE:LP:AF:SS:ID   0.0188218:0.0184812:1.79263:0.261:33000:rs10907187
1   1759213 rs9786942   A   G   .   PASS    AF=0.498    ES:SE:LP:AF:SS:ID   -0.0236781:0.0164812:2.70224:0.498:33000:rs9786942
1   1776269 rs4648727   C   A   .   PASS    AF=0.452    ES:SE:LP:AF:SS:ID   0.0236781:0.0164812:2.42713:0.452:33000:rs4648727