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-1161/ieu-a-1161.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-1161/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 11:36:47 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1161/ieu-a-1161.vcf.gz ...
Read summary statistics for 191058 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, 136822 SNPs remain.
After merging with regression SNP LD, 136822 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: 0.4836 (0.0933)
Lambda GC: 1.2668
Mean Chi^2: 1.6928
Intercept: 1.1031 (0.0209)
Ratio: 0.1488 (0.0302)
Analysis finished at Wed Feb  5 11:36:56 2020
Total time elapsed: 9.58s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.403,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0.0003,
    "n": 69970,
    "n_snps": 191058,
    "n_clumped_hits": 46,
    "n_p_sig": 1703,
    "n_mono": 0,
    "n_ns": 1,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 1,
    "n_miss_AF_reference": 1152,
    "n_est": 70378.4281,
    "ratio_se_n": 1.0029,
    "mean_diff": -0.0001,
    "ratio_diff": 0.8599,
    "sd_y_est1": 2.1254,
    "sd_y_est2": 2.1316,
    "r2_sum1": 0.2419,
    "r2_sum2": 0.0535,
    "r2_sum3": 0.0532,
    "r2_sum4": 0.0496,
    "ldsc_nsnp_merge_refpanel_ld": 136822,
    "ldsc_nsnp_merge_regression_ld": 136822,
    "ldsc_observed_scale_h2_beta": 0.4836,
    "ldsc_observed_scale_h2_se": 0.0933,
    "ldsc_intercept_beta": 1.1031,
    "ldsc_intercept_se": 0.0209,
    "ldsc_lambda_gc": 1.2668,
    "ldsc_mean_chisq": 1.6928,
    "ldsc_ratio": 0.1488
}
 

Flags

name value
af_correlation TRUE
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 FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
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 22 0 191058 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 2 0 5 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.863780e+00 5.775955e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▆▅▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.855541e+07 5.659370e+07 5.0814e+04 3.160572e+07 6.887496e+07 1.160603e+08 2.491747e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.894000e-04 3.390980e-02 -1.6213e+00 -1.170000e-02 -1.000000e-04 1.180000e-02 9.342900e+00 ▇▁▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.752190e-02 1.107346e-01 1.1300e-02 1.190000e-02 1.370000e-02 1.840000e-02 4.819230e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.503383e-01 3.019048e-01 0.0000e+00 1.800002e-01 4.400003e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.550837e-01 3.022418e-01 0.0000e+00 1.811970e-01 4.414999e-01 7.174652e-01 1.000000e+00 ▇▆▆▅▅
numeric AF 1 0.9999948 NA NA NA NA NA 2.330795e-01 1.425261e-01 1.0000e-04 1.073000e-01 2.207000e-01 3.533000e-01 5.473000e-01 ▇▇▆▆▃
numeric AF_reference 1152 0.9939704 NA NA NA NA NA 3.488433e-01 2.521507e-01 1.9970e-04 1.393770e-01 2.885380e-01 5.265580e-01 9.996010e-01 ▇▆▃▃▂
numeric N 0 1.0000000 NA NA NA NA NA 6.997000e+04 0.000000e+00 6.9970e+04 6.997000e+04 6.997000e+04 6.997000e+04 6.997000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1018704 rs9442372 A G -0.0017 0.0115 0.8700001 0.8824800 0.4424 0.611022 69970
1 1062638 rs9442373 C A 0.0002 0.0114 0.9800000 0.9860027 0.4584 0.574281 69970
1 1094738 rs4970362 A G -0.0055 0.0120 0.6400000 0.6467130 0.3705 0.604034 69970
1 1099342 rs9660710 A C -0.0128 0.0220 0.5600000 0.5606892 0.0725 0.829872 69970
1 1106473 rs4970420 G A 0.0017 0.0145 0.9000000 0.9066688 0.1909 0.550319 69970
1 1110019 rs11260542 A G -0.0209 0.0195 0.2800000 0.2838122 0.0942 0.144569 69970
1 1119858 rs1320565 C T -0.0208 0.0214 0.3200000 0.3310691 0.0773 0.318690 69970
1 1135242 rs9729550 A C 0.0050 0.0130 0.6999999 0.7005224 0.2561 0.551917 69970
1 1138913 rs3819001 T C -0.0334 0.0247 0.1700000 0.1763028 0.0575 0.198482 69970
1 1156131 rs2887286 T C 0.0064 0.0154 0.6700003 0.6777141 0.1615 0.511182 69970
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50960682 rs140524 C T -0.0074 0.0151 0.6200004 0.6240870 0.1734 0.2302320 69970
22 50966914 rs470119 T C -0.0113 0.0117 0.3300000 0.3341383 0.3935 0.5547120 69970
22 50971266 rs140522 T C -0.0104 0.0122 0.3900004 0.3939594 0.3274 0.6190100 69970
22 50988062 rs140519 G T 0.0021 0.0114 0.8499999 0.8538483 0.5023 0.4051520 69970
22 50989326 rs131778 A G -0.0001 0.0114 0.9900000 0.9930011 0.4776 0.4984030 69970
22 51080760 rs134774 A G 0.0331 0.0203 0.1000000 0.1029870 0.0861 0.9536740 69970
22 51123505 rs9616816 G A 0.0102 0.0136 0.4499995 0.4532547 0.2273 0.3783950 69970
22 51151350 rs6009951 C T -0.0053 0.0116 0.6400000 0.6477454 0.4165 0.5559110 69970
22 51151724 rs6010061 C T -0.0020 0.0116 0.8600001 0.8631122 0.4126 0.6098240 69970
22 51178090 rs2285395 G A 0.0083 0.0251 0.7400005 0.7408883 0.0534 0.0666933 69970

bcf preview

1   1018704 rs9442372   A   G   .   PASS    AF=0.4424   ES:SE:LP:AF:SS:ID   -0.0017:0.0115:0.0604807:0.4424:69970:rs9442372
1   1062638 rs9442373   C   A   .   PASS    AF=0.4584   ES:SE:LP:AF:SS:ID   0.0002:0.0114:0.00877392:0.4584:69970:rs9442373
1   1094738 rs4970362   A   G   .   PASS    AF=0.3705   ES:SE:LP:AF:SS:ID   -0.0055:0.012:0.19382:0.3705:69970:rs4970362
1   1099342 rs9660710   A   C   .   PASS    AF=0.0725   ES:SE:LP:AF:SS:ID   -0.0128:0.022:0.251812:0.0725:69970:rs9660710
1   1106473 rs4970420   G   A   .   PASS    AF=0.1909   ES:SE:LP:AF:SS:ID   0.0017:0.0145:0.0457575:0.1909:69970:rs4970420
1   1110019 rs11260542  A   G   .   PASS    AF=0.0942   ES:SE:LP:AF:SS:ID   -0.0209:0.0195:0.552842:0.0942:69970:rs11260542
1   1119858 rs1320565   C   T   .   PASS    AF=0.0773   ES:SE:LP:AF:SS:ID   -0.0208:0.0214:0.49485:0.0773:69970:rs1320565
1   1135242 rs9729550   A   C   .   PASS    AF=0.2561   ES:SE:LP:AF:SS:ID   0.005:0.013:0.154902:0.2561:69970:rs9729550
1   1138913 rs3819001   T   C   .   PASS    AF=0.0575   ES:SE:LP:AF:SS:ID   -0.0334:0.0247:0.769551:0.0575:69970:rs3819001
1   1156131 rs2887286   T   C   .   PASS    AF=0.1615   ES:SE:LP:AF:SS:ID   0.0064:0.0154:0.173925:0.1615:69970:rs2887286
1   1162435 rs3766186   C   A   .   PASS    AF=0.0921   ES:SE:LP:AF:SS:ID   0.0094:0.0195:0.200659:0.0921:69970:rs3766186
1   1211292 rs6685064   C   T   .   PASS    AF=0.0682   ES:SE:LP:AF:SS:ID   -0.0151:0.0225:0.30103:0.0682:69970:rs6685064
1   1239953 rs10399878  A   G   .   PASS    AF=0.0476   ES:SE:LP:AF:SS:ID   -0.0467:0.0269:1.09691:0.0476:69970:rs10399878
1   1775175 rs11260622  A   G   .   PASS    AF=0.0402   ES:SE:LP:AF:SS:ID   0.0215:0.0286:0.346788:0.0402:69970:rs11260622
1   1978857 rs3121825   A   G   .   PASS    AF=0.3503   ES:SE:LP:AF:SS:ID   -0.0022:0.012:0.0705811:0.3503:69970:rs3121825
1   1980639 rs6683042   G   A   .   PASS    AF=0.2348   ES:SE:LP:AF:SS:ID   0.0015:0.0135:0.0409586:0.2348:69970:rs6683042
1   1981118 rs3795277   A   C   .   PASS    AF=0.0839   ES:SE:LP:AF:SS:ID   0.0066:0.0205:0.130768:0.0839:69970:rs3795277
1   1983160 rs28703783  C   A   .   PASS    AF=0.2581   ES:SE:LP:AF:SS:ID   0.03:0.0132:1.69897:0.2581:69970:rs28703783
1   1983421 rs4648795   T   C   .   PASS    AF=0.405    ES:SE:LP:AF:SS:ID   -0.0168:0.0116:0.853872:0.405:69970:rs4648795
1   1983701 rs28671574  G   A   .   PASS    AF=0.0825   ES:SE:LP:AF:SS:ID   -0.001:0.0207:0.0177288:0.0825:69970:rs28671574
1   1984227 rs3128319   C   T   .   PASS    AF=0.2385   ES:SE:LP:AF:SS:ID   -0.0025:0.0134:0.0705811:0.2385:69970:rs3128319
1   1985170 rs35020387  G   A   .   PASS    AF=0.3816   ES:SE:LP:AF:SS:ID   0.0031:0.0117:0.107905:0.3816:69970:rs35020387
1   1985553 rs13302968  T   C   .   PASS    AF=0.1459   ES:SE:LP:AF:SS:ID   0.0006:0.0163:0.0132283:0.1459:69970:rs13302968
1   1992977 rs17777295  G   T   .   PASS    AF=0.2472   ES:SE:LP:AF:SS:ID   -0.0055:0.0132:0.173925:0.2472:69970:rs17777295
1   1993722 rs13303346  C   T   .   PASS    AF=0.1339   ES:SE:LP:AF:SS:ID   -0.0052:0.0168:0.124939:0.1339:69970:rs13303346
1   1997150 rs2803294   G   A   .   PASS    AF=0.1879   ES:SE:LP:AF:SS:ID   0.0154:0.0146:0.537602:0.1879:69970:rs2803294
1   1997187 rs75227206  A   G   .   PASS    AF=0.1855   ES:SE:LP:AF:SS:ID   -0.0099:0.0151:0.29243:0.1855:69970:rs75227206
1   1999345 rs28523801  T   C   .   PASS    AF=0.1387   ES:SE:LP:AF:SS:ID   0.0018:0.0165:0.0409586:0.1387:69970:rs28523801
1   1999680 rs28479788  G   A   .   PASS    AF=0.2332   ES:SE:LP:AF:SS:ID   0.009:0.0135:0.30103:0.2332:69970:rs28479788
1   1999840 rs13303005  C   T   .   PASS    AF=0.1354   ES:SE:LP:AF:SS:ID   -0.004:0.0167:0.091515:0.1354:69970:rs13303005
1   2000592 rs2678939   C   A   .   PASS    AF=0.1754   ES:SE:LP:AF:SS:ID   0.0079:0.0149:0.229148:0.1754:69970:rs2678939
1   2001568 rs13303084  T   C   .   PASS    AF=0.1358   ES:SE:LP:AF:SS:ID   -0.0054:0.0167:0.130768:0.1358:69970:rs13303084
1   2002502 rs13302898  C   T   .   PASS    AF=0.3012   ES:SE:LP:AF:SS:ID   0.0037:0.0125:0.119186:0.3012:69970:rs13302898
1   2004947 rs2678942   T   C   .   PASS    AF=0.3136   ES:SE:LP:AF:SS:ID   0.0022:0.0123:0.0705811:0.3136:69970:rs2678942
1   2005740 rs2459986   T   C   .   PASS    AF=0.1524   ES:SE:LP:AF:SS:ID   -0.0003:0.0158:0.00877392:0.1524:69970:rs2459986
1   2006108 rs2254669   A   G   .   PASS    AF=0.3133   ES:SE:LP:AF:SS:ID   0.0044:0.0123:0.148742:0.3133:69970:rs2254669
1   2006127 rs16824697  G   A   .   PASS    AF=0.1706   ES:SE:LP:AF:SS:ID   0.0063:0.0151:0.173925:0.1706:69970:rs16824697
1   2006728 rs2678943   T   C   .   PASS    AF=0.3814   ES:SE:LP:AF:SS:ID   -0.0013:0.0117:0.0409586:0.3814:69970:rs2678943
1   2009551 rs72636371  C   T   .   PASS    AF=0.0496   ES:SE:LP:AF:SS:ID   0.0398:0.0263:0.886057:0.0496:69970:rs72636371
1   2011300 rs13303213  C   T   .   PASS    AF=0.1274   ES:SE:LP:AF:SS:ID   -0.0011:0.0172:0.0268721:0.1274:69970:rs13303213
1   2014196 rs28436686  G   A   .   PASS    AF=0.2915   ES:SE:LP:AF:SS:ID   -0.0004:0.0125:0.0132283:0.2915:69970:rs28436686
1   2024507 rs9729600   T   C   .   PASS    AF=0.0943   ES:SE:LP:AF:SS:ID   -0.005:0.0195:0.102373:0.0943:69970:rs9729600
1   2025607 rs61775405  G   A   .   PASS    AF=0.118    ES:SE:LP:AF:SS:ID   -0.0108:0.0177:0.267606:0.118:69970:rs61775405
1   2031342 rs2376802   T   C   .   PASS    AF=0.5123   ES:SE:LP:AF:SS:ID   -0.0005:0.0114:0.0177288:0.5123:69970:rs2376802
1   2037383 rs4648619   T   G   .   PASS    AF=0.2879   ES:SE:LP:AF:SS:ID   0.0052:0.0126:0.173925:0.2879:69970:rs4648619
1   2038824 rs908743    G   A   .   PASS    AF=0.4922   ES:SE:LP:AF:SS:ID   -0.001:0.0114:0.0362122:0.4922:69970:rs908743
1   2040096 rs6666117   T   C   .   PASS    AF=0.114    ES:SE:LP:AF:SS:ID   -0.005:0.0182:0.107905:0.114:69970:rs6666117
1   2045380 rs3107144   C   A   .   PASS    AF=0.3966   ES:SE:LP:AF:SS:ID   -0.0033:0.0116:0.113509:0.3966:69970:rs3107144
1   2047547 rs3107145   G   A   .   PASS    AF=0.399    ES:SE:LP:AF:SS:ID   -0.0052:0.0116:0.187087:0.399:69970:rs3107145
1   2048729 rs3107147   G   A   .   PASS    AF=0.4019   ES:SE:LP:AF:SS:ID   -0.0037:0.0116:0.124939:0.4019:69970:rs3107147